Podcasts about hmi

https://youtu.be/Ji1OZYu1r1Y Charles Fry, Founder and CEO of CODE Éxitos, is helping businesses hire AI in enterprise to transform software engineering, modernize product development, and build intelligent connected systems.  In this conversation, Charles introduces The Agentic Org Chart Framework: Hire Systems Thinker, Look for Failed Entrepreneurs, and Have AI Replace “Trade Skills”. He explains why AI is fundamentally changing software development, how organizations must redesign their structures for an AI-first workforce, and why systems thinking is becoming more valuable than technical specialization. Charles also discusses how the rise of agentic software development is reshaping the future of SaaS, why combining AI with connected hardware creates a stronger competitive advantage, and what business leaders must do to successfully navigate AI-driven transformation. — Hire AI in Enterprises with Charles Fry  Good day. Steve Preda here, and I’m talking with Charles Fry, the Founder and CEO of CODE Éxitos, building cyber-physical systems for mid-market and enterprise companies, as well as full-stack web, mobile, and SaaS development. Charles, welcome back to the show.  Hey, I’m happy to be here. It’s always great to see you, and I’m looking forward to our chat. Yeah. It’s so interesting to talk to you because the last time we had you on the show, three or four years ago, it was still before the AI age was fully upon us.  Right.  Your business was kind of a different business. I’ve been following you on LinkedIn, and I see that you’ve evolved your approach, and now you’re an AI-first company. So tell me a little bit about how that came about, this whole evolution, and how you found your new focus?  Yeah. Wow. It’s been that long since we were on the show. It was a lot of fun, but here we are. You’re right. AI really sort of came out of left field. I’ll skip all the technical things that suddenly made AI an achievable thing. But really, at the beginning of 2024—and somebody can fact-check my timeline—ChatGPT, if you were aware of it, was kind of passing the Turing test. It was giving pretty reasonable answers to natural-language questions.  And we were like, “Wow, this is interesting.” At first, we were helping our clients think about how to build those capabilities into their products, something we still do.Share on X But by mid-’24, late ’24, it became pretty obvious that one of the best applications of large language models—and expert systems, we used to call them that—is writing software. And so by early to mid-’25, the systems were suddenly not novelties. They were credible at what they were doing, and they were gaining momentum in the quality and credibility of the software they were producing.  Now, CODE Éxitos was started largely to create an opportunity for entrepreneurs and enterprises that needed, let’s call it, garden-variety, well-done software. We built that through the Americas to arbitrage labor rates in Latin America and leverage the time zones. So it was essentially an offshore, blended, hybrid-team model. Honestly, by the middle of 2025, the AI tools for software engineering were as good as, or better than, 50 percent of the human developers that we employed.  And at some point, as a business owner, when you’re out there representing yourself, and your product is yourself, and you’re representing that to clients, you have a moral and ethical obligation to say, “Hey, I think I can still give you the best product that you’re looking for, but I’m going to do it in a different way.” So beginning in late 2025, we were hard into the pivot. Today, all of our software development is done agentically. There are still people. It’s not a complete dark factory. But our mid-level performers and below, we exited them from the business, which caused a lot of human turmoil. I mean, we were at around 100 people. A lot of human turmoil. Our clients were going through the same thing. We were watching what was happening in their organizations and what the leadership demands were.  We just made the decision to lean into it. And here we are, almost mid-’26 now, and it’s actually going really well. Now, AI, of course, anyone who opens an internet browser anymore sees it. AI is everywhere. You read the newspaper. AI is going to change everything.  Every application has an AI layer to it.  Yeah.  Right? Every SaaS application has a button that says, “Use AI here.”  My view, at least—and these are the things people should probably give me some credibility on—I’m going to keep my views focused on how AI applies to the software industry, my industry, and its direct impact. We see, and we have clients working on, things like AI in customer service, the legal department, and the finance department. We do all of those things internally—agentic first, AI first. But those really aren’t my industry. I’m not ready to make a sweeping prognosis about how AI is going to change capitalism in the United States. But in the software industry, it’s a fundamental change. And it’s not done yet.  So what’s your vision? Where is everything going? What’s it going to look like three years from now?  Well, I’m not smart enough to know that. But I think the patterns we've seen—and again, within the world of writing software, and making that a broad category of activitiesShare on X —are going to continue to consolidate and converge to where humans are important, but they might be only 10 to 20 percent of the input to the process. I really do think we’re going to see a day, sometime in the three-to-five-year time horizon, where a large amount of software will be written and managed by other software systems.  There’s no technical reason to prevent that. For example, I was talking to one of our clients today, a CIO at a great company. A couple hundred million dollars in revenue. A really well-run business. A sizable internal IT team. But there’s a lot of ongoing maintenance and attention required. Building the software is just the beginning of a five-to-ten-year life cycle. So I think in the near term we’re going to see that building the software becomes, “Okay, we got that figured out.” That’s a largely solved problem.  We’ll then progress to the problem of: “Hey, this software has been in production for five years.” “It needs updates.” “It needs attention.” “It needs maintenance.” “It needs to scale.” More software systems will take care of that. Fewer and fewer humans will be involved in that kind of work. So I think that’s where the software industry is headed. I think it’s going to be 60 to 80 percent smaller in human capital than it is today. Sometime soon. Yeah. I really do think it’s about as close as I want to get to calling it an extinction event. Let’s put it that way. Some people say SaaS companies are going to go out of business, and it’s all going to be agents running around doing things for us. But other people say SaaS companies are actually the SOP for whatever activity is out there, and you need that structure. The SaaS application provides that structure. You don’t want agents running in an unstructured way. You’d rather have these SaaS applications. What’s your view?  I think that’s a good way of looking at it. If you’re a dinosaur like I am, back in the late 1980s or early 1990s, when you wrote software for a company, everything was custom software because there were no packaged software products, no SaaS platforms. But over the last 20 years, I think SaaS companies have become, for a lot of businesses, exactly what you said. They’re the embodiment of best practices. If you take something like HubSpot, which I’m sure you and many of your audience are familiar with, you really don’t need to customize it.  You just need to follow its baseline processes because they have thousands of customers who have helped refine the sales motions that work. So I think there’s some truth to that. The problem SaaS systems face is that the barrier to competitive entry is much, much lower. If you look at a company like Salesforce—and I think I’ve led three different Salesforce deployments back when I was a CIO or CTO—that software really shows its age. It’s layers and layers of complexity built to serve a wide audience. It’s great. It’s expensive. Emerging companies don’t need that. They can effectively vibe-code their own CRM system, and it works. I think the threat for big SaaS companies is twofold.  One is that the next generation of customers is going to onboard very differently into those systems than the previous generation.Share on X I don’t know what that onboarding ramp is going to look like. The second problem is there’s very little defensibility in having a pure software product. And the other part of our intro—you talked about cyber-physical systems. We’re spending more and more of our product development cycles on hardware-related products, things that have a nexus in the physical world. Here’s a good example. I’m wearing one of these health rings. This Oura Ring. Oura, yeah.  There’s a lot of amazing hardware in here that justifies my monthly subscription for the app. The app we could recreate pretty easily. But the development, manufacturing, and distribution of this physical item create a much higher barrier for a competitor to overcome. So more and more of our clients are companies that have a physical product they either want to make smarter or make more connected.  That’s really what it comes down to. And that’s a pretty exciting space. But for a pure-play SaaS company, I think it’s going to get tough. The competitive pressure is going to be intense. And the barrier to entry is going to be really low. It’s not even about engineering cost anymore because the cost of engineering has dropped so much with AI. It’s almost like it went full circle. You had all these product businesses that wanted to become service businesses to create recurring revenue. And now the service businesses—the SaaS businesses—want to become product businesses to create a barrier to entry, improve retention, or reduce disruption. Isn’t that interesting?  Yeah. I hadn’t thought about it exactly that way. Maybe the pushback would be that these professional services businesses wanted to have a technology play or a platform. That’s interesting. But I think we’re going to see AI, at least in technology, continue to lower the barrier to entry. It will allow much faster experimentation with pure software ideas. And we’re focused on the things where the AI robots can’t play. They’re not going to cut your grass.  They might guide the machine that cuts your grass, but they’re not going to cut your grass. So I think that while the turmoil is still sorting itself out in the pure software world, we’re going to see a whole new set of opportunities open up. We’ll be able to build truly smart devices. Devices that think for themselves. Devices that are aware of the world around them. They can participate with us in our day-to-day work. That’ll be a lot of fun. I think we still have some rough sailing ahead of us as AI sorts itself out.  Isn’t it true that people prefer to interact with a purpose-designed device rather than a software product? And maybe an app is kind of a device that is software, or maybe that’s the overlap there. But I know there are some things I’d rather have on my phone, even though it’s complicated because there are so many other things on it. But if I have a single-purpose device, like you have your Oura Ring, it’s easier to interact with. There’s no complexity, and then it lowers the accessibility.  Yeah. An area of active study is something called HMI, or Human-Machine Interface. Again, back in the ’80s and ’90s, it meant things like: Are the buttons big enough for someone to push? Does a red light always mean a bad thing, and a green light always mean a good thing? But now that’s expanded into the kind of research in psychology and sociology that you’re talking about, Steve. Some of that is really amazing.  I’m sure you’ve seen them, and your audience has seen them. You can find these videos on YouTube. There are humanoid robots. It took a while for researchers to figure out that a robot doesn’t actually need a head. It can have what is essentially a torso with arms and legs. The head doesn’t really need to be there. But a robot with no head freaks people out. Yes. People don’t like it. So the robotics engineers put heads on them. Then they thought, “Well, if we’ve got a head here, we’ll just put a face on it.” But if the face is too realistic, it gives people the creeps.  Yeah.  So people didn’t like faces on them. If you look at the current generation of humanoid autonomous robots, they have these, I don’t know, sort of pseudo-faces. They kind of look like Halloween jack-o’-lanterns or something. They’re not scary, but they’re somewhere in the middle. Anyway, the things you’re talking about are really fascinating.  I mean, Isaac Asimov wrote about humanoid robots and all the challenges that come with them. What happens when they have a human-like appearance? What happens when people think they are actually people, but they just don’t age? All those things have been explored. But listen, I’d like to switch gears here and ask you this. Right now, in this AI age, what drives your business? What drives growth in your business?  This part is truly fascinating to me. Everyone is working off the same timeline now, which isn’t a very long timeline. We don’t have a lot of experience to draw on. Much more quickly than when the internet became commercially available—I was there when that happened too— the adoption of AI as a fundamental change happened in a matter of months, compared to several years for the internet.Share on X Some people also compare it to the adoption of mobile phones, which you mentioned.  But this has happened very fast. A year ago, we were talking to sophisticated technical buyers who said, “Yeah, I’m still on the fence about whether I like agentic software development.” That doesn’t happen anymore. Everybody says, “Yeah, we’re using it too.” What we’re seeing now is that it’s evolved so quickly and had such a fundamental impact that people don’t know not only how to manage it inside their business, but also how to deploy it. It’s really disruptive. And this is where you’re a pro.  It’s really disruptive to organizations. So in less than a year, we’ve gone from, “Hey, should I let my developers use AI?” to now everybody using AI. And the leading teams, including ours, can produce high-quality commercial code faster than organizations can absorb it, and faster than org charts can adapt to the change. Our engineering teams have to adapt to the pace of the business, not the other way around. Because we get clients saying, “Hey, you guys are producing too much.” “We can’t check everything.”  “We haven’t finished testing last week’s new features and capabilities yet.” “We can’t take another batch of features and capabilities this week.” So we’re seeing a lot of organizational behavior change starting to come out of this. When we’re talking to C-level executives and senior leaders, that’s where most of the conversations are today. “How do I retool my organization to capture the benefits?”  Yeah. Because what I see is that the more AI you apply, the faster decision velocity becomes. And the complexity of understanding the whole picture, connecting the dots, increases. So you need a different kind of person who can operate at that higher level of contextualization. Do you see the same thing?  We do. Software engineering and product development had matured into a pretty predictable set of job descriptions and capabilities. The business processes were really well worn. We knew what the product owner did. We knew what a project manager did. We knew what a tech lead did. Et cetera, et cetera. A lot of these, frankly, became trade skills. “Hey, I’m really good at writing code.” Or, “I’m really good at doing QA, but I’m not really a systems thinker.” “I’m not an entrepreneur.” “I’m not a creator.” Pick your fuzzy lens of choice.  That’s really what AI displaces right now. AI displaces those trade skills and, frankly, does them better and cheaper. There’s no way to dispute that. What we look for now, and I think where the trend is going with our clients, is systems thinkers. We have enough agentic tooling built on our own internal platform that the people operating and building products for our clientsShare on X —we refer to our team as digital creators—come from a variety of backgrounds. You don’t have to be a computer science major. You do have to have some domain experience. You do have to be a systems thinker. You do have to understand what business value you’re trying to create. But as far as actually writing really good code, nobody’s really doing that now. It’s being done automatically.  If you have a couple of gray hairs like I do, you’ll remember back 20 years ago when we talked about the war for talent. That’s what everybody was looking for. They wanted people with these highly specialized engineering skills. I think there’s a new war for talent. It’s going to be harder to pin down because we’re going to be looking for whole-systems thinkers as opposed to technical specialists. Because AI will be the technical specialist we need, regardless of the business domain. So what do you do to infuse systems thinking in your business?  Wow. I wish I had a good answer for that. I don’t even know how to recruit these kinds of people right now. I’ll be that candid with you and your listeners. I was talking to a couple of my senior people, and I said, “Maybe we should go look for failed entrepreneurs.” Which is kind of a heretical thing to say. But as an entrepreneur, I know firsthand that it doesn’t always work. The fact that the business fails doesn’t necessarily mean you, as an entrepreneur, are a personal failure.  Entrepreneurs are about the only, I don’t know, primary source I can think of for people who have done a little bit of everything. They’re systems thinkers. Maybe they didn’t get it right, but they could. So we talked about that. I don’t know if Disney still does it, but Disney was phenomenal at producing these kinds of people through its internal training programs. We’re not big enough to compete with Disney. But to answer your question, how do we teach it? I can’t honestly say that we do. Because we’re still figuring out what it is that we would even teach.  Well, it’s a new type of SOP that’s needed in the business. So what are the best practices for building an AI workforce? That still needs to be defined.  Yeah. For larger organizations, our clients that are running larger organizations have the same problem. All of a sudden, their org chart is broken. What I mean by that is, if you look at the way we’ve traditionally built and scaled businesses, you have this pretty large cadre of managers who give you what Eliyahu Goldratt called the span of control, your degree of leverage. When you’re younger, you hear things like, “Ah, my manager doesn’t even do anything.” You’ve probably heard that before. “Oh, my manager doesn’t really do any work.” “He just comes in and bugs me.”  It’s not entirely wrong because we rely on that manager’s experience to be spread across six, eight, or ten other people and supervise their work. So managers don’t really do a whole lot of delivering the work themselves. I think AI is going to change that. I know AI is already changing that inside technical teams. All of a sudden, we have clients saying, “My org chart doesn’t translate to the way my business operates under this new agentic model.” That’s problem number one. Problem number two is, “I have people on my team who are good people and good contributors, but there’s no box for them in the new org chart that I think works with an agentic workflow.” Does that make sense?  Yeah.  So two things have happened suddenly. We see a lot of press—although I think it’s moderating a little bit now—about how kids coming out of university are having trouble getting entry-level jobs. True enough. I think the other area where org charts are collapsing is managers who don’t actually produce any output. Supervising other managers and compiling the weekly report of reports just isn’t a valuable job function, even at the best of times. And now—I hate to say this—but it’s useless. So I think there’s a lot more work we’re going to have to do with our clients, and ourselves, on what an org chart should look like. And what the expectations are for people doing work inside a company that’s moving aggressively toward leveraging AI capabilities in what we would normally call white-collar job functions. Yeah. Some years ago, I thought about the org chart being broken. The top-down hierarchical org chart—I think it’s completely broken. In my head, the org chart is more like an amoeba, where you have the entrepreneur and the manager in the middle as yin and yang. Different departments report to different people. And you’ve got these pizza teams all over, actually delivering teamwork. But that’s fascinating. Yeah, fascinating topic. So who are the ideal customers for you? If they have the right kind of projects, what are the right kinds of customers and the right kinds of projects for CODE Éxitos that would be interesting to look at?  There are two types of clients that we focus on and that we can help quite a bit. The first type of client is one that has a large, established internal software development and product development process, and they’re trying to figure out how to adapt, modernize it, and harness AI. We can come in, and we have a very opinionated point of view. We can have a couple of conversations, and they either like the direction our telescope is pointed in and want us to help, or they say, “No, we think we’re going to do it a different way.”  And that’s okay, too. Because right now, nobody really knows the final answer. We call those engineering transformation projects. Somebody says, “Hey, we have a team. Can you help us get better?” The second type of client we like is one that has this physical connection challenge. I’ll give you an example. We have a client that primarily makes pumps and motors. They put those pumps and motors into very specific industrial applications across North America. They wanted those pumps and motors connected to a network.  They wanted to collect data from those pumps and motors to help their customers. Once we built the data collection, the electronics, and the connectivity, the data started coming in. Now there are a lot of AI-related things we can do with that data. We’re beginning to work on what you can think of as supervisory agents that watch what’s going on. They’re much more robust than the old filters that just looked for exceptions and red lights. Those are the kinds of clients we really help on the product side.  Sometimes they come to us with an idea scribbled on a napkin. It’s like, “Hey, we have this system or this process that we envision, and we need somebody to help us build it.” We’ll do the electronics, the AI, and the software engineering. And that becomes a complete system. So, more systems thinking. Yeah. And then you combine software with hardware. Then you have AI agents doing much of the coding, management, and maintenance of these systems.  Yeah, that’s right. This is not a client of ours, by the way, but the story I’m going to tell is fascinating. It’s a second-degree connection that I chatted with. He runs a $100 million-a-year manufacturing company. I think he’s second or third generation—I can’t remember which. He knows the business. He grew up in the industry. He’s in the process of transforming the company so that he can basically run the whole business from his phone.  He’s applying AI to his internal business functions like finance and accounting. He’s done some really amazing stuff. He’s automating the manufacturing process, the machines, and the feedback systems. It’s just stunning what this guy is already able to do. He just picks up his phone and says, “Yeah, I want to run my company from here.” I think he’s going to be able to do it. I think we’re going to see more of that emerge. Yeah. That’s fascinating. The race is for the first one-person unicorn, right?  I think that’s already happened. I don’t know if you’ve seen this. I can send it to you. There was a New York Times article a couple of months ago about a guy—not a tech guy, a marketing guy. He and his brother run an online company that generates $1.8 billion a year in sales. And it’s just the two of them. Wow!  Spoiler alert: As I remember, they sell weight-loss drugs. He’s a marketing guy with a tech background. He figured out all these marketing channels where, if you order Ozempic or whatever online, it basically drop-ships from the pharmaceutical company to you, and he gets a cut. But he said in the article, “At one point, we were doing $300 million a month in sales.” He goes, “Well, technically, I’m not a one-man company because I had to hire my brother to help me out.” So it’s the two of them.  That’s pretty great. Yeah. That’s definitely a unicorn. So if you’re listening to this and you have an enterprise company, and you want to harness AI in your business, create agentic systems, streamline your operations, and make your company more efficient and productive, then reach out to Charles Fry at CODE Éxitos. Any last thoughts for listeners who are thinking about building a business in the AI age? What advice would you give them? I don’t know that it’s changed a whole lot. Building a business is always hard work. For any listener who wants to chat about any of these topics or see if we’re the right fit, they can always reach out and contact me. The conversation is free, and I usually learn something from it. But no, I would say that things are different. It doesn’t mean they’re wrong or better. I think they’re just different. It’ll be interesting to see how all of this unfolds over the next few years.  Yeah.  I’m in it for the journey.  We’re living in interesting times. So, Charles Fry, Founder and CEO of CODE Éxitos, thanks for coming on the show. And if you enjoyed this show, make sure you follow us on YouTube and Apple Podcasts. Give us a review, and stay tuned because every week I bring an amazing entrepreneur onto the show. Thanks for coming. Thanks for listening.  Thanks, Steve. Important Links: Charles's LinkedIn Charles's Website

Chinesische Automobilhersteller erobern den europäischen Markt und mit ihren Fahrzeugen kommen neue HMI-Konzepte nach Europa. In dieser Folge schaue ich hinter Displays, Sprachassistenten und digitale Ökosysteme und diskutieren, warum Nutzer in Shanghai oft andere Erwartungen an Technologie haben als Nutzer in Stuttgart oder Paris. Wir sprechen über Cultural UX, Vertrauen, Transparenz, Automatisierung und die Frage, warum Human-Centered Design immer auch den kulturellen Kontext berücksichtigen muss. Denn die Zukunft erfolgreicher HMIs liegt nicht in globalen Einheitslösungen, sondern in Technologien, die sich lokal menschgerecht anfühlen.

What if the biggest bottleneck in hardware design isn't your engineer's skill — it's the sheer volume of manual work standing between a great idea and a working schematic? And once you decide to embrace AI-assisted design, how do you make sure the output is actually trustworthy enough to build from? What you'll learn… (00:12) Why fragmented workflows hit SMB hardware teams hardest (02:39) The real cost of going from requirements to prototype without specialist support (07:33) How functional block-level design changes early decisions — including when a SOM beats building from scratch (12:04) Why system-level abstraction catches wrong-path decisions before they reach the schematic (14:39) The "rubber duck debugging" effect: how AI clarifies requirements before they become costly mistakes (17:54) The biggest AI misconception in hardware design — and why the engineer must own every decision (20:30) How CELUS's NXP collaboration delivers manufacturer-validated, human-in-the-loop solutions (25:05) Why abstraction-first tools help SMBs take on projects that would otherwise be out of reach (28:19) The CELUS Success Program: high-touch onboarding for SMBs on the Siemens instance More about the episode… In this episode of the Printed Circuit Podcast, host Steph Chavez welcomes back Antonio Becerra Esteban, VP of Customer Success at CELUS — a physicist-turned-engineer with experience at Infineon and Altium who now leads the team ensuring customers extract real value from the platform. The conversation tackles the fragmented, manual journey from requirements to schematic that burdens small hardware teams. Antonio explains how CELUS's functional block-level design approach lets engineers define system architectures, navigate component trade-offs with an AI assistant, and output fully-interconnected schematics — illustrating the point with a Linux-based HMI example where the right abstraction layer turns a complex MPU build into a simple SOM selection. On the trust question, Antonio is direct: the engineer must own every decision. CELUS backs this up with manufacturer-validated design blocks, transparent sourcing, and a human-in-the-loop process — putting engineers in the driving seat rather than asking them to ship whatever the model produces. SMBs can join CELUS' Success Program by sending an email to cs@celus.io. Connect with Steph Chavez: LinkedIn Website Connect with Antonio Becerra Esteban: LinkedIn CELUS Website

In this Fluid Power Forum episode, NFPA host Eric Lanke shares a recorded NFPA webinar on advancing technologies for controls, IoT, and data—featuring Scanreco Director of Sales Andy Gray.   Gray explains how Scanreco's professional radio remote controls serve OEMs and system integrators for mobile and industrial machinery in harsh environments, translating operator intent into hydraulic actuator motion from simple on/off to highly proportional control to improve safety, precision, and productivity. Discussion covers operating at safer distances, integrating camera feedback and Human Machine Interface, HMI, information onto remotes, and the growing role of assisted operation and autonomy across applications like agriculture, forklifts, drilling, demolition, forestry, and fire equipment.   Gray describes field research with operators, integration via CAN and software tools, OEM preference for open integration ecosystems, and progress to unify remote control, advanced displays, and onboard computing amid trends of digitalization, electrification, automation, and usability. Subscribe to the Fluid Power Forum today to never miss an episode. The podcast is available on all of your favorite podcast platforms, including YouTube, Apple Podcasts, Spotify, and iHeart Radio.   Connect with our host, Eric Lanke, at elanke@nfpa.com.   Connect with our guest, Andy Gray, at andy.gray@scanreco.com.   Learn more about the company at www.scanreco.com.   Find and share more interesting fluid power technologies and unique applications using #onlyfluidpowercan and follow podcast and other fluid power industry-related updates at @TheNFPA.   #FluidPowerForum #Controls #Safety #Autonomy #CID

This week Shawn Tierney meets up with Maria Santella and Robert Murao of ICP DAS USA to learn about their new Modbus RTU, TCP, and other products in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 274 Show Notes: Special thanks to Maria and Robert for coming on the show, and to ICP DAS USA for sponsoring this episode. To learn more about these products, please see the below links: Modbus Gateways  Modbus Touch Screen Controllers   Modbus RTU DAQ Serial Port Sharing Devices  Modbus over Cellular Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Industrial network protocols decide whether a machine talks or stays silent. Chuck from Horner Automation breaks down how they win, fade, and converge.Chuck has spent 36 years at Horner Automation and lived through what the industry once called the fieldbus wars. Before Horner became known for its all in one controllers, it spent a decade building specialty IO modules for GE Fanuc during the era of DeviceNet, SDS, InterBus S, PROFIBUS, and CANopen. His core argument is that most of those early protocols were technically fine. The ones that became standards won on the commercial weight of the companies backing them, not on superior specifications, with EtherCAT a rare exception that succeeded largely on technical merit.Trust is the recurring theme. Industry adopts slowly, and for years Ethernet was dismissed as too unreliable and not deterministic enough for control until Ethernet/IP, PROFINET, and Modbus TCP proved themselves. Today the market has settled around a big four set of protocols, and Chuck does not expect it to narrow further. For high speed motion he points to EtherCAT and PROFINET IRT as the implementations he most respects, since both step away from standard Ethernet at the device level to reach submillisecond timing.The episode is also a reality check on building your own hardware. Chuck and Dave describe how custom development routinely costs teams hundreds of thousands to millions of dollars, and how the real trap is obsolescence and maintenance rather than the first build. On the product side, the standout is FPD-Link, a serialization technology borrowed from automotive that carries video, touch, and power over one coaxial cable. Working with Safe Fleet, a maker of ambulances and fire trucks, Horner now mounts rugged displays up to seven meters from the PLC while still programming everything as one device.Looking ahead, Chuck argues that every PLC should now be treated as a data device first, because digitizing the process is the prerequisite for doing anything useful with AI. He also flags cybersecurity as the next burden for application engineers, with new mandates forcing both manufacturers and integrators to implement protections that were once optional. At Automate, Horner is showing HMI Connect and a 300 dollar CPU 151 that packs 18 IO points, wireless connectivity, and edge capability into a micro PLC.About Chuck and Horner AutomationChuck is a technical brand ambassador at Horner Automation, where he has spent 36 years across applications, product management, and education. An electrical engineer who started in the automotive industry, he now produces in depth tutorials on industrial protocols for the Horner APG YouTube channel. Horner Automation is a privately held controls manufacturer best known for its all in one PLC and HMI controllers, edge ready PLCs, and rugged hardware for industrial and mobile applications.Timestamps0:00 Introduction2:20 Chuck's Background and 36 Years at Horner Automation9:20 End User Engineer vs OEM Manufacturer Perspective13:20 New at Automate: HMI Connect and the CPU 151 Edge PLC21:30 The Fieldbus Wars and the History of Industrial Protocols24:20 What It Takes to Implement a Protocol Stack29:30 Why Protocols Win: Commercial Force vs Technical Merit32:40 Will Industrial Protocols Ever Converge?40:30 High Speed Motion: EtherCAT, PROFINET IRT, and Ethernet/IP44:40 FPD-Link: Rugged Remote HMI for Ambulances and Fire Trucks55:00 PLCs as Data Devices and the Push Toward AI1:02:40 Cybersecurity Mandates Coming for Application EngineersReferencesHorner Automation: https://www.hornerautomation.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Understanding Plant Networks: https://www.joltek.com/blog/understanding-plant-networks-how-industrial-connectivity-evolvedIndustrial Ethernet Reliability: https://www.joltek.com/blog/industrial-ethernet-reliabilityDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub

Das Fahrzeug war lange Zeit das Zentrum der Mensch-Maschine-Interaktion. Doch diese Welt verändert sich rasant. Automotive HMIs verlassen das Cockpit, verteilen sich über Smartphones, Tablets, Smartwatches und Cloud-Dienste und werden Teil eines umfassenden digitalen Ökosystems. In dieser Episode des Mensch-Technik Podcasts analysiere ich die nächste Evolutionsstufe der Automotive User Experience: Liquid HMIs, vernetzte Ökosysteme und die digitale Identität des Nutzers. Warum verlieren Interfaces ihre festen Grenzen? Weshalb wird das Fahrzeug zunehmend zu einem Knotenpunkt innerhalb eines größeren digitalen Netzwerks? Und warum kämpfen OEMs, Apple, Google & Co. letztlich um dieselbe Ressource: die Beziehung zum Nutzer? Die Zukunft des Automotive HMI liegt nicht in mehr Displays oder mehr Features – sondern in der intelligenten Organisation eines digitalen Ökosystems rund um den Menschen.

This week Shawn Tierney meets up with Nick Rosner of Schneider Electric to discuss VFD and HVAC Applications in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 273 Show Notes: Special thanks goes out to Nick Rosner of Schneider Electric for coming on the show, and to Schneider Electric for sponsoring this episode. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Shawn Tierney meets up with Rylan Pyciak of Cleveland Automation Systems to discuss Control System Migrations and more in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 272 Show Notes: Special thanks to Rylan for coming on the show, and to Cleveland Automation Systems for sponsoring this episode! Below you’ll find more information on what we discussed: Read “A Decade in the Automation Industry: Reflecting on 10 Years of Change” Read “The Lost Art of Industrial Troubleshooting: Why Real Problem Solving Still Matters” Explore “The ROI Calculator” – A Free Resource for Maximizing Your Investments with Data-Driven Insights Explore “How to Write a URS” – A Free Guide for Writing Specifications That Drive Automation Success Explore CAS Services – How Our Engineers Help You Keep Pace with Industry Changes Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Sprache, Touch, Gesten, Haptik, KI-Assistenten, moderne Fahrzeuge entwickeln sich zunehmend zu multimodalen Systemen. Doch genau hier beginnt eines der größten Missverständnisse aktueller HMI-Entwicklung: Mehr Interaktionskanäle bedeuten nicht automatisch bessere User Experience. In dieser Folge des Mensch-Technik Podcast geht es um die eigentliche Herausforderung multimodaler Automotive HMIs: nicht Technologie zu demonstrieren, sondern echten Wert zu schaffen. Warum sind physische Stellteile trotz Digitalisierung weiterhin relevant? Weshalb schlägt Kontext fast immer Technologie? Welche Rolle wird KI künftig bei der Orchestrierung von Interaktion spielen? Und warum entsteht gute Multimodalität häufig durch Reduktion statt Addition? Die beste Modalität ist nicht die modernste, sondern diejenige, die in einer konkreten Situation den größten Wert für den Menschen erzeugt. Fünf zentrale Themen der Folge: 1. Multimodalität als Systemarchitektur statt Feature-Sammlung 2. Kontext statt Technologie-Fetischismus 3. The Revenge of the Analog im Fahrzeugcockpit 4. KI als adaptiver Orchestrator von Interaktion 5. Warum echte UX durch Vereinfachung entsteht Eine Folge über Technologie, menschliche Wahrnehmung und die Frage, wie sich Interaktion im Fahrzeug der Zukunft wirklich anfühlen sollte.

This week Shawn Tierney meets up with Phillip Swinson and Mike Stoup of ISA Tampa to discuss the upcoming Florida Automation Expo in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 271 Show Notes: Special thanks to our Members who support our work! To learn more about memberships, checkout this link. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Change management decides whether your MES or digital transformation project lasts, or quietly gets shut off six months after go live.Vlad Romanov and Dave Griffith sit down with Logan Terry, who leads digital transformation at LSI, to dig into change management as the deciding factor in any automation or MES rollout. Logan defines change management as a methodical approach to moving an individual, team, or organization from a current state to a desired future state. The closer a system sits to where decisions are actually made, the more change management it requires, which is why MES is the single hardest place to land a project successfully.Much of the episode digs into why change management is rarely scoped properly. In competitive RFPs, the integrator who includes a robust change management line item often loses to the lowest bid, and end users frequently do not know how to evaluate that line item even when it is offered. Logan starts every client engagement with a direct question: what does your continuous improvement practice look like internally? If the client cannot sustain the change after handover, the project is on borrowed time no matter how clean the FAT and SAT looked.Logan walks through one of the most useful failure stories on the show this year. His team delivered a technically perfect OEE dashboard for a production line. Six to nine months later, every terminal was shut off. The postmortem surfaced two missed details. Maintenance was never folded into the design, and a single failed photo eye broke throughput calculations with no manual reconciliation path, which destroyed operator trust in the data. The second miss was behavioral. Showing a 30 percent OEE against a 90 percent ideal demotivates the floor, while reframing the same number as 80 percent of a realistic 36 percent target turned out to be a cleaner motivator.Looking forward, Logan sees vendors moving away from monolithic 14 function MES suites toward modular, use case specific deployments, which compresses change management scope from twenty five workflows to five or six. On AI, he argues that managing generative agents in production is closer to managing a team of people than managing software, with continuous validation replacing one time qualification. He cites the line that AI does not make bad data worse, it makes it more convincing. LSI now uses AI assisted coding agents and React based prototypes to shrink design cycles from three or four weeks of Figma work down to three or four days.About Logan TerryLogan Terry leads digital transformation at LSI, a multinational systems integrator with roughly 400 resources across 13 North American locations and offices in Asia Pacific. A mechanical engineer by training, Logan spent a decade in PLC, HMI, and SCADA development before moving into digital transformation consulting and joining LSI in late 2024. His work spans advanced SCADA, MES, analytics, and BI integrations.LSI: https://www.logicalsysinc.com/Timestamps0:00 Introduction2:15 Logan's background and the LSI digital transformation practice7:25 Defining change management9:00 Why MES requires the most change management13:00 How young engineers stumble into change management24:30 Starting with decisions and workflows before technology35:00 Internal CI capability as a project gating factor43:30 OEE dashboard turned off six months after go live46:30 Behavioral psychology of how operators read numbers54:50 Modular MES replacing monolithic platforms58:00 Generative AI and continuous validation1:11:00 AI assisted prototyping shrinking design cyclesAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladimirromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturingManufacturing Execution Systems and Business Strategy: https://www.joltek.com/blog/manufacturing-execution-systems-business-strategyDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub

This week Shawn Tierney meets up with Christine Bush of Schneider Electric to discuss What’s New and Next in Robotics in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 270 Show Notes: Special thanks goes out to Christine Bush of Schneider Electric for coming on the show, and to Schneider Electric for sponsoring this episode. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Automotive HMI steht an einem Wendepunkt. Was jahrzehntelang einem klaren Muster folgte, mehr Funktionen, mehr Technologie, gerät ins Wanken.cAutomatisierung verändert die Rolle des Fahrers.cKünstliche Intelligenz stellt das Interaktionsprinzip infrage. Und neue Player, insbesondere aus China, bringen völlig andere HMI-Logiken mit. Doch das ist nur die Oberfläche. Unter der Haube entstehen tiefgreifende Veränderungen: Software-Defined Vehicles, Peak Display, Multimodalität, HMI-Ökosysteme. Und mittendrin eine entscheidende Verschiebung: Es geht nicht mehr nur um Usability, sondern um Vertrauen, Kontrolle und kognitive Entlastung. In dieser Folge gebe ich einen strukturierten Überblick über: - Die 3 offensichtlichen Herausforderungen - Die 5 unterschätzten Entwicklungen - Die eine zentrale Meta-Herausforderung: den Menschen im System nicht zu verlieren Denn genau hier entscheidet sich die Zukunft: Bauen wir weiterhin Feature-Monster oder schaffen wir echten Mehrwert?

This week Shawn Tierney meets up with Chuck Ridgeway of Horner Automation to learn about their new Modular PLCs in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 269 Show Notes: Special thanks to Chuck Ridgeway of Horner Automation for coming on the show, and to Horner Automation for sponsoring this episode. To learn more about these products, please see the below links: Horner Automation’s YouTube Channel Horner Automation’s LinkedIn Horner Automation’s Modular Controllers Horner Automation’s OCS360 Cloud Service Horner Automation’s Academic Program Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

From building Applied Intuition from YC-era autonomy tooling into a $15B physical AI company, Qasar Younis and Peter Ludwig have spent the last decade living through the full arc of autonomy: from simulation and data infrastructure for robotaxi companies, to operating systems for safety-critical machines, to deploying AI onto cars, trucks, mining equipment, construction vehicles, agriculture, defense systems, and driverless L4 trucks running in Japan today. They join us to explain why “physical AI” is not just LLMs on wheels, why the real bottleneck is no longer model intelligence but deployment onto constrained hardware, and why the future of autonomy may look less like one-off demos and more like Android for every moving machine.We discuss:* Applied Intuition's mission: building physical AI for a safer, more prosperous world, powering cars, trucks, construction and mining equipment, agriculture, defense, and other moving machines* Why physical AI is different from screen-based AI: learned systems can make mistakes in chat or coding, but safety-critical machines like driverless trucks, autonomous vehicles, and robots need much higher reliability* The evolution from autonomy tooling to a broad physical AI platform: starting with simulation and data infrastructure for robotaxi companies, then expanding into 30+ products across simulation, operating systems, autonomy, and AI models* Why tooling companies came back into fashion: Qasar on why developer tooling looked unfashionable in 2016, why Applied Intuition still bet on it, and how the AI boom made workflows and tools central again* The three core buckets of Applied Intuition's technology: simulation and RL infrastructure, true operating systems for vehicles and machines, and fundamental AI models for autonomy and world understanding* Why vehicles need a real AI operating system: real-time control, sensor streaming, latency, memory management, fail-safes, reliable updates, and why “bricking a car” is much worse than bricking an iPad* Physical machines as “phones before Android and iOS”: Peter explains why today's vehicle and machine software stack is fragmented across many operating systems, and why Applied Intuition wants to consolidate the platform layer* Coding agents inside Applied Intuition: Cursor, Claude Code, internal adoption leaderboards, and how AI tools are changing engineering workflows even in embedded systems and safety-critical software* Verification and validation for physical AI: why evals get harder as models improve, how end-to-end autonomy changes simulation requirements, and why neural simulation has to be fast and cheap enough to make RL practical* From deterministic tests to statistical safety: why autonomy validation is shifting from binary pass/fail requirements toward “how many nines” of reliability and mean time between failures* Cruise, Waymo, and public trust: Qasar and Peter discuss why autonomy failures are not just technical issues, how companies interact with regulators, and why Waymo is setting a high bar for the industry* Simulation vs. reality: why no simulator perfectly represents the real world, how sim-to-real validation works, and why real-world testing will never disappear* World models for physical AI: hydroplaning, construction equipment, visual cues, cause-and-effect learning, and where world models help versus where they are not enough* Onboard vs. offboard AI: why data-center models can be huge and slow, but onboard vehicle models need millisecond-level latency, low power, small size, and distillation-like efficiency* Why physical AI is not constrained by model intelligence alone: the hard part is deploying models onto real hardware, under safety, latency, power, cost, and reliability constraints* Legacy autonomy vs. intelligent autonomy: RTK GPS in mining and agriculture, why hand-coded path-following worked for decades, and why modern systems need perception and dynamic intelligence* Planning for physical systems: how “plan mode” applies to robotaxis, mining, defense, and multi-step physical tasks where actions change the state of the world* Why robotics demos are not production: the brittle last 1%, humanoid reliability, DARPA Grand Challenge-style prize policy, and the advanced engineering gap between research and deployment* Applied Intuition's hard-earned lessons: after nearly a decade, Peter says they can look at a robotics demo and predict the next 20 problems the company will hit* Qasar's advice to founders: constrain the commercial problem, avoid copying mature-company strategies too early, and remember that compounding technology only matters if you survive long enough to see it compound* Why 2014 YC advice may not apply in 2026: capital markets, AI company dynamics, and the difference between building in stealth with a deep network versus building as a new founder today* What Applied is hiring for: operating systems, autonomy, dev tooling, model performance, evals, safety-critical systems, hardware/software boundaries, and engineers with deep curiosity about how things workApplied Intuition:* YouTube: https://www.youtube.com/@AppliedIntuitionInc* X: https://x.com/AppliedInt* LinkedIn: https://www.linkedin.com/company/applied-intuition-incQasar Younis:* X: https://x.com/qasar* LinkedIn: https://www.linkedin.com/in/qasar/Peter Ludwig:* LinkedIn: https://www.linkedin.com/in/peterwludwig/Timestamps00:00:00 Introduction: Applied Intuition, Physical AI, and 10 Years of Building00:01:37 Physical AI vs. Screen AI: Why Safety-Critical Changes Everything00:02:51 The Origin Story: Tooling, YC, and the Scale AI Comparison00:05:41 The Three Buckets: Simulation, Operating Systems, and Autonomy Models00:11:10 Hardware, Sensors, and the LiDAR Question00:14:26 The Operating System Layer: Why Vehicles Are Like Pre-Android Phones00:19:13 Customers, Licensing, and the Better-Together Stack00:21:19 AI Coding Adoption: Cursor, Claude Code, and the Bimodal Engineer00:26:41 Verifiable Rewards, Evals, and Neural Simulation00:31:04 Statistical Validation, Regulators, and the Cruise Lesson00:40:25 World Models, Hydroplaning, and Cause-Effect Learning00:43:34 Onboard vs. Offboard: Latency, Embedded ML, and Distillation00:50:57 Plan Mode for Physical Systems and Next-Token Prediction Universally00:53:04 Productionization: The 20 Problems Every Robotics Demo Will Hit00:58:00 Founder Advice: Constraints, Compounding Tech, and Mature-Company Mimicry01:05:41 Hiring Philosophy: Hardware/Software Boundary and Engineering Mindset01:08:50 General Motors Institute, Education, and the Curiosity MindsetTranscriptIntroduction: Applied Intuition, Physical AI, and 10 Years of BuildingAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: And today we're very honored to have the founders of Applied Intuition, Qasar and Peter. Welcome.Qasar [00:00:17]: You guys really know how to turn it on to podcast mode. That was, you guys are real pros at this.Qasar [00:00:23]: They were just joking around right before this, and then they flipped it pretty quick.Alessio [00:00:29]: Oh, yeah, it's good to have you guys. Maybe you just wanna introduce yourself so people know the voice on the mic and they'll know what they're hearing.Peter [00:00:33]: Oh, sure. Yeah, I'm Peter Ludwig. I'm the co-founder and CTO of Applied Intuition.Qasar [00:00:38]: And my name is Qasar Younis. I am the CEO and co-founder with Peter.Alessio [00:00:42]: Nice. Can you guys give the high-level overview of what Applied Intuition is? And I was reading through some of the Congress files, when you went out there, Peter, and eighteen of the top twenty global non-Chinese automakers, you two guys, you have customers in agriculture, defense, construction. I think most people have heard of Applied Intuition tied to YC when it was first started, and then you were kinda in stealth for a long time, so maybe just give people the high-level overview of what it is today, and then we'll dive into the different pieces.Peter [00:01:10]: Yeah. So at Applied Intuition, our mission is to build physical AI for a safer, more prosperous world. And so we work on physical AI for all different types of moving systems, everything from cars to trucks to construction and mining equipment, to defense technologies. And we're a true technology company, so we build and sell the technology, and we sell it to the companies that make the machines. We sell it to the government, really anyone that wants to buy a technology to make machines smart.Physical AI vs. Screen AI: Why Safety-Critical Changes EverythingQasar [00:01:38]: Yeah. And I think in the broader AI landscape, a lot of the focus, rightfully so in the last, three years has been on large language models, and so everything fits in a screen. Like, whether it's code complete products or things like that. And what's different about us is we're deploying intelligence onto a lot of things that don't have screens. they're physical machines. There are sometimes screens within the cabin or for example of a car or a truck or something like that, but most of the value we provide is putting intelligence that is in safety critical environments. So that those two words are really important because learn systems can make mistakes if you're asking for, like, some, so something like, “Tell me about these podcast hostsQasar [00:02:28]: that I'm about to go meet.” But you can't do that obviously when you run, like, as an example, we run driverless trucks in Japan right now, as we speak. We can't have errors. Those are L4 trucks. Yeah.Alessio [00:02:40]: Yeah. Was that always the mission? I remember initially, I think people put you and Scale AI very similarly for some things about being kinda like on the data infrastructure side of things. What was the evolution of the company?The Origin Story: Tooling, YC, and the Scale AI ComparisonPeter [00:02:51]: Well, from the very beginning, we always wanted to, really be a technology company that helped generally push forward the industrial sector. And so we started off working in autonomy. Our very first customers were robotaxi companies. And we started off doing a lot of work in simulation and data infrastructure. And then over the years, we've expanded our portfolios. Now we have, over thirty products, and it's a pretty broad technology play within the landscape of physical AI.Qasar [00:03:19]: Yeah, I think the Scale reason is because we're all YC Universe companies. But it was a very different company. Scale, was, is more of a services company, data labeling company fundamentally. We started and still are, do a lot of tooling. So like, you think developer tooling is now in vogue again, thanks to the AI boom. But honestly, ten years ago, it was out of vogue. It w Like, doing a tooling company in 2016, 2017 was not, like, the thing to do because, I don't know if you remember, the VCs generally, their views was that toolings are They're just workflows, and workflows ultimately are not really interesting. And we've gone and come, full circle with that. But when we started the company, our kind of it's kinda like in the periphery of what the company wants to be. It was like, from our earliest days, like, we wanna deploy software on physical machines, like on cars and on trucks and things like that. And obviously, we didn't know that the transformer boom was gonna happen. We didn't know that autonomy systems would become end-to-end. Those things we didn't know. And why that's important when autonomy systems become end-to-end, it is just now those models can be generalized to, multiple form factors. And so back nine, ten years ago, tooling was a great way, and still is a great way to, build the technology and sell technology to our end customers, a lot of them who wanna build this stuff themselves. And so we just offer like a spectrum of solutions from you can just use like one part of a development suite of tools all the way to buying the full thing. The way to think about the company, or at least the way we think about the company is, as Peter said, a technology provider. It's kinda like, what NVIDIA does or what an AMD, but we just don't do chips.Qasar [00:05:06]: We don't do silicon. But we're a technology provider fundamentally. And I think even, we used to joke when we started the company, like, we're not the guys to build, like, Instagram. Like that was just towards That's not our That's just not us in a most fundamental way. IAlessio [00:05:20]: You have thoughts.Qasar [00:05:21]: Yes.Qasar [00:05:22]: Well, it's, it's I mean, I think it's just like what And I mean, we worked on Maps and stuff, Google Maps. Consumer products are extremely difficult for a lot of different reasons. It just, I think doesn't scratch the itch. I think we're like Michigan guys who are kind of more of that traditional engineering kind of a realm, or lineage. we used to jokeThe Three Buckets: Simulation, Operating Systems, and Autonomy ModelsPeter [00:05:41]: I gotta say, though, what was clear ten years ago was that there was so much more that was possible with software and AI in vehiclesPeter [00:05:47]: and that was generally the space that we started in ten years ago.Peter [00:05:51]: And the precise path that we've taken over the years, I think we've been strategic, and we've adjusted to make sure that we're actually building stuff that's valuable to the market. And like, the technology has changed so much. Like our own technology stack has completely changed, I would say, roughly every two years. And so now we've probably done, let's say, four complete evolutions of our own technology stack. And I sort of see that cadence roughly keeping up.Peter [00:06:13]: And so the way even we think about engineering is almost on this two-year horizon, we're preparing ourselves that, hey, like, we wanna invest the appropriate amount, but then also be very dynamic as the research gets published and as our research team figures out new advancements and adapting to that.Qasar [00:06:27]: Yeah. One thing that has been consistent is the type of people we've, we've recruited. It's engineers who are fall into the sometimes very traditional, like, GoogleQasar [00:06:38]: -gen suite, but way different from, other companies. We are hiring folks who really know the intersection of hardware and software, who know really low-level systems. Obviously, traditional ML researchers and folks who've, actually, put ML systems into production. That's been pretty consistent. I think that, like, you look at the mix of our engineering, eighty-three percent of the company is engineering, so it's, like, a giant list.Qasar [00:07:05]: A lot of engineers.Alessio [00:07:06]: Which, by the way, a thousand engineersQasar [00:07:07]: Yeah. A thousand engineers.Alessio [00:07:08]: that's on your website, so I imagine it's up to date.Qasar [00:07:11]: It is, it is up to date, yes. Yes.Alessio [00:07:12]: okay. And then forty-plus founders.Qasar [00:07:15]: Yeah. We would tend to also, This was more luck than strategy. But we've recruited a lot of ex-founders. It's been a great place for founders, YC and non, ‘cause obviously I know a lot of the YC folks. It's kind of like we recruit a lot of Google people.Qasar [00:07:33]: For them to exercise both their technical and non-technical skills because, we're, we're, we're on the applied side. We have a research team that we do fundamental research, we publish, and we've, we've had great traction there. But fundamentally, the business wants to take this intelligence and deploy it into production and there's, like, a certain type of person that's more interested in that.Alessio [00:07:54]: Yeah. You mentioned the tech stack, Peter, so I just wanted to give you some rein to just go into it. I'm interested in where Wayve Nutrition, starts and ends in some sense, what won't you do? What, do you do that's common among all the verticals that you cover?Peter [00:08:10]: There's a few buckets of work that we do, and we've been at this for almost ten years now, so the technology's pretty broad. But we got startedQasar [00:08:17]: Yeah, with a thousand engineers, like, you could work on lots of things.Peter [00:08:19]: There's lots of stuff, yeah, espe-especially with AI tools to help.Peter [00:08:22]: So we got our start in simulation and simulation tooling and infrastructure. And so generally, if you're trying to build a very complex software system that involves moving machines, you need to test that, and the best way to test it is it's a combination of virtual developments, a simulation, and then also obviously real world testing.Peter [00:08:39]: And then there's a very careful process of that correlation between the simulation results and the real world results and ensuring that the simulator is in fact accurate to that. Simulation's a very deep topic.Peter [00:08:49]: We have a whole suite of products in that, and we could talk for many hours about that specifically. But that is one part of what we do as a company. Reinforcement learning as a subpart of that is also super critical. I think a lot of the a lot of the best advancements happening in a lot of these AI systems right now in some way relate to reinforcement learning, and with now we have lots of compute, and you can do tons of interesting things for reinforcement learning. The second bucket of work that we do is on operating systems technology. true operating systems. Like, think about, schedulers and memory management and middleware and message passing and highly reliable networking and data links. Like, the reality is, if you want to deploy AI onto vehicles, you need a really good operating system. And when we were getting deeper into that space, there wasn't really anything that we were happy with.Peter [00:09:39]: Like, things existed, absolutely, and we were using what was available in the market, and as an engineering organization, we roughly realized these things aren't great. We think we can do this better, and so let's, let's build something. And that was then the that was the moment of inspiration that started our operating systems business, which is now a very real business for us. And in order to write and run great AI, you need a great operating system, and so that-that's what got us into that. And then the third bucket that we work on, it's, it's true fundamental AI technology. Models, we do a lot of work in, as mentioned, the foundational research, but then the also the world models and the actual autonomy models that are running on these physical machines, and that's across cars, trucks, mining, construction, agriculture, and defense, and so that's both land, air, and sea.Qasar [00:10:31]: And also, a smaller subsector of that third bucket is the interaction of humans with those machines.Qasar [00:10:38]: So that's a multimodal, experience. Historically, if you're moving a dirt mover or any of these machines, there are, like, buttons you press, whether they're actual physical tactile buttons or something like a touch screen. That's just That fundamentally is changing to where you're just talking to the machine and the machine and you're teaming with the machine.Alessio [00:10:58]: Voice?Qasar [00:10:59]: Yeah, voice, absolutely, yeah.Alessio [00:11:00]: Oh.Qasar [00:11:00]: And also the machine just being aware of who is in the cabin, what their state is. you can think from a safety systems perspective, the most simple version of this is, like, the driver is tired, right? They're, they're if you get those alerts when you're driving your car and saysHardware, Sensors, and the LiDAR QuestionQasar [00:11:15]: -maybe take a coffee break, that take that times, a couple of order of magnitudes up. But this concept of teaming man and machine is important. When you think about running agents or just running, different instances of, Claude and doing work for you in the background, you can take that analogy out, almost copy and paste and put it into, like, a farm, where you have a farmer who's running a number of machines. So where they interact with the machine is where there's maybe a critical decision or a disengagement or something like that, but generally speaking, the agent on the physical machine is running and making decisions on the behalf of the farmer until there's something maybe critical. And that's also what we work on. So that's not pure autonomy. It's a little bit of a mix, but it falls under, autonomy. In the automotive sense, that's typically defined in SAE levels as an L2++ systemQasar [00:12:05]: -with a human in the loop. But just take that idea, to other verticals.Alessio [00:12:09]: Yeah. You've not mentioned hardware at all, like sensors or obviously we you mentioned you don't do chips. I think even in AV there's, like, a big, cameras versus lidars. Like, what are, like, in your space maybe some of those design decisions that you made, and are they driven by the OEM's ability to put things on the machinery? And like, how much influence do you guys have on co-designing those?Peter [00:12:32]: Yeah. So we don't make sensors. Like, we're, we're not a manufacturer. Obviously, we use a lot of sensors in our autonomy products. in terms of what actually goes on the vehicles, we have a preferred set of sensors that we, let's say fully support, and then our customers, they can sort of choose from those. And obviously if there's a very strong opinion on supporting something else, we'll add that to the platform as well. And the lidar question is at this point sort of the age-old,Peter [00:12:59]: topic in autonomy, and the state of the industry right now is lidar is hands down a useful sensor, specifically for data collection and the R&D phase of autonomy development. if you see, for example, a Tesla R&D vehicle, it actually has lidar on itPeter [00:13:17]: to this day, right? In the Bay Area we see these. you'll see, like, Model Ys or Cybercab that have lidars on them just driving around. So it's, it's useful because it gives you per pixel depth information. So if you can pair a lidar with a camerand you can say that, well, this camera's looking this direction, this lidar's looking this direction, and now for each pixel of the camera I can see how far away is that pixel. you can actually then use that as a part of your model training, and then the that depth information then becomes a learned, a learned state of the camera data. And then when you're doing the production system, you can now remove the lidarPeter [00:13:52]: and now you can actually get depth with just the camera. And so that difference between, like, a highly sensored R&D vehicle and then the down-costed production vehicle, we use that across our whole portfolio of products. And of course the end goal is you want super low cost and super reliable.Peter [00:14:08]: And then in certain use cases you have some more, bespoke things. Like in defense as an example, you do things at night oftentimes, and so you care about sensors like infrared, more so than And you don't, you don't wanna be putting energy out, so you don't wanna use lidar or radar.Peter [00:14:23]: but you still need to be able to see at nighttime. So yeah, we work the whole gamut.The Operating System Layer: Why Vehicles Are Like Pre-Android PhonesAlessio [00:14:27]: Cool. So that's kinda like on the hardware level. Then on the OS level, how does that look like? What is, like, unique? my drive- I drive a Tesla. Whenever I drive some other car that has a screen, it always sucks.Alessio [00:14:38]: It's on, like, cheap Android tablet. It's like, it's laggy and all of that. What does the OS of, like, the autonomy future look like?Peter [00:14:46]: When most people, it's really what you just described. When you think about operating system in a vehicle, you're thinking about the HMI, right? The human machine interface, and absolutely that's a an important part of it, but that's actually only one thin layer on top. So when we talk about operating systems for, like, AI in vehicles, there's many layers that go deep into the CPU critical realm and embedded systems, and you're talking about the real time control ofPeter [00:15:13]: let's say the electric motors or the engine and the actuators, and you have different redundancies for different, let's say, the steering actuation in the vehicle. And all of these things, need very core support in the in the operating system. And then of course for autonomy you have real time sensor data that's streaming in, and the latencies there are really important, right? If you try to Imagine you try to run Microsoft WindowsPeter [00:15:35]: like streaming your sensor data in or controlling the vehicle. Like, the latencies are gonna be absurd. Like, you can never do that. And so what's special about what we do is we really have this system level thinking, right? So we're looking at, we care about every performance characteristics of the entire system, and then we also, because we're doing a lot of the software or all of that software, we can fine-tune and control all of those things. So we can very carefully tune in the latencies for every aspect of the system. We can carefully tune in the memory management. We can have the right, fail-safes and fallbacks, for different things. ‘Cause you have to account for what if, what if there is a critical failure? What if there's a cosmic ray that flipsPeter [00:16:14]: a bit in the middle of the processor that causes some, malfunction? And you have to have a fail-safe to all of that, and so the core operating system is a part of that. And then the one last thing, which is a lot less exciting but is, actually a very big topic, is reliability of updates.Peter [00:16:30]: so the I have a Tesla and you get updates fairly frequently, right?Peter [00:16:36]: Once a month. Most companies that are making vehiclesPeter [00:16:40]: are basically never doing updates, and they're And even if they are doing updates, they're usually only updating maybe one module. Maybe they're updating the HMI module. But they're not able to update, let's say, the CPU critical parts of the system.Peter [00:16:51]: You have to go into the dealer for that. And so with our operating system now we can actually enable highly reliable updates of any system in the vehicle, and that's way easier said than done. Like, there's lots of technical, technically deep stuff, in the tech stack to do that in a way that you're not going to accidentally brick a vehicle.Peter [00:17:08]: And right? If, imagine yourAlessio [00:17:10]: That would be bad.Alessio [00:17:11]: Bad.Peter [00:17:11]: Bricking a car is a very expensivePeter [00:17:13]: and honestly, like across the industry maybe one of the most just pure impactful things that we've done is we've just, we're, we're now enabling the industry to actually do software updates.Alessio [00:17:22]: Just to clarify as well, who is the customer for this? Like, I assume a lot of hardware manufacturers have their own firmware, and I'm sure some of them would just have you write it for them because you're experts. And others would have their own. Like, who pays for this? Who invites you into the house? Is it, is it the end user, or is it, is it the manufacturer?Peter [00:17:41]: Yeah. So let me make an analogy firstly on the on the fragmentation of software. So physical machines today are more akin to the state of the phone market before Android and iOS existed, right? So I worked on Android at Google by the way many years ago, and part of the reason that Larry at Google decided to get into Android was they wanted to run Google products on a bunch of phones, and they bought all of these phones from the industry, and it turned out they had like 50 different operating systems on these phones. And it was virtually impossiblePeter [00:18:17]: for Google to make their app run on all 50 devices equally well. And so the solution was, well, actually what if, what if they created-A really great operating system and made it attractive to all of these phone makers, and that was sort of the genesis for what Android was and why Android existed. It was a way for Google to get their products onto really wide diversity of devices. The state of the physical, industry right now, it's a little bit like that. Like, there's yes, these companies have firmware, but they have so many different operating systems, it's so fragmented, and to actually get a modern AI application to run on these vehicles, you actually, you first have to consolidate the operating system, and so that's, that's why we've done that. And then, your specific question was who are our customers? It's, it's, generally it's the companies that are making these machines.Peter [00:19:06]: And we're, we're, we're selling our technology to them to really simplify the architecture and then enable these AI applications to run on them.Customers, Licensing, and the Better-Together StackSwyx [00:19:13]: How much is reusable across? Like, do you have, like, one OS that is just configured for everything, or is there some more customization that is needed?Peter [00:19:22]: Yeah, highly reusable. So the fundamental technology is quite universal, right? So things that we do have to think about though are, like, chipset support. And so if you're, if you're coding, let's say, an LLM and you have start with an assumption that, “Hey, oh, I'm gonna, I'm gonna use CUDA, and I'm gonna run this, on an NVIDIA chip,” then you don't really have to think about the hardware in that sense. Like, you're just, “Okay, I'm just I'm in the CUDA/NVIDIA ecosystem, and I'm, I'm going to use that.” But the hardware, especially in safety critical systems, it's a lot more diverse. There's not one or one or two players. There's a bunch of different chipsets that we have to support. And so our operating system doesn't just run on, like, the equivalent of X86. It has to, it has to run on a number of different architectures from chips from a bunch of different companies. But again, we've been working on this for a long time now, so we have, we have support for all of those chipsets. And then when you want to then run the AI applications, we can then do that reliably across now a variety of providers.Qasar [00:20:19]: And I think that is, like, heavily inspired by Android, right? Android has a huge suite of testing and it's a reliable operating system that runs on thousands of devices. And we think we can, we can do the same in all these physical moving machines, with the difference that we're really in a safety critical realm. Android isn't.Alessio [00:20:40]: So on Android, I don't need to use Gmail, I can use Superhuman. Like, what about your machinery? Like, can people bring somebody else's automation to it, or is it kinda like all-in-one?Qasar [00:20:50]: You have to use us. No. Yeah. we're If, Yeah. Yeah, it's totally open. Yeah.Peter [00:20:56]: Yeah. our philosophy is that we are a technology company, and so we license our technology to customers to use how they want. And so if a customer wants to If they wanna license our autonomy tech and our operating system, then great, we'll license those. If they just wanna license the operating system and then use different autonomy tech, that's fine also, and we have great documentation andSwyx [00:21:17]: Or if they wanna use developer tooling.Peter [00:21:18]: Yeah, exactly.AI Coding Adoption: Cursor, Claude Code, and the Bimodal EngineerSwyx [00:21:19]: It's, like, a better together if, obviously, if you, if they work together. Is it all C++ I assume is with different compile targets?Peter [00:21:27]: We use a lot of C++.Peter [00:21:28]: Rust is sort of a hot, the new hot kid on the blockPeter [00:21:32]: for a bunch of things as well. But yeah, the lower level you get, especially when you get to real-time constraints, you hit C++ at some point, and at some point maybe you work your way into assembly when needed.Swyx [00:21:44]: Oh, damn.Alessio [00:21:46]: I'm curious about the coding agent adoption, just, like, since you're mentioning more esoteric languages. Like, what's the adoption internally? What have you learned?Peter [00:21:55]: Yeah. We use everything. So Cursor was, I think the hottest tool in the company for a good while. Now Claude Code, I think has taken the reign on that. We have a internal leader, leaderboard that we use just to sort of encourage adoptionPeter [00:22:09]: with-within the company. And yeah, it's, they're phenomenally useful. it's, Honestly, we take inspiration from some of those tools also in how we're adapting some of that mindset of thinking to the physical realm. Like if it's so easy to build an app for this or that thing that lives just on a screen, we can We're taking now a lot of the same ideas and applying that to, “Okay, well, if you wanted a physical machine to do something, how easy can we make that, using our own tooling and platform as well?”Alessio [00:22:40]: Are you changing any of, like, the OS architecture, kinda like the way you expose services to, like, be more AI friendly or?Peter [00:22:48]: Yeah, absolutely. The in the early days of our tools infrastructure work, it was a lot about, You had engineers that were experts in certain topics, but the things that you're dealing with, they're oftentimes more mathematical or more abstract, where actually GUI tools are very useful for certain things. Like as an example, we have a product we call Sensor Studio, which is, it helps you design the sensor suite for your autonomous vehicle, whether, again, it could be a car, it could be a drone, could be a mining equipment, could be a robot. And you place sensors in different places. You There's different, There's a library. You can understand what are the trade-offs that you're making in the design of that system, and that was, like, a very, a very GUI intensive, thing ‘cause it's a little more like a CAD tool in that senseSwyx [00:23:37]: YepPeter [00:23:37]: if you've seen CAD tools. Nowadays, though, right, we expose all of the underlying APIs for that and now using, AI agents, you can actually configure a sensor suite with just text and likely reach a better result than you could've through the GUI in the past, and we're taking that thinking now through the whole product portfolio.Swyx [00:23:57]: Another thing I was thinking about is just in terms of, like, AI, adoption, does it change your hiring at least a little bit, or how do you, how do you sort of manage engineers, differently?Peter [00:24:08]: Yeah. absolutely, it does. we, I think like every company in the Valley right now, are evolving our hiring practicesPeter [00:24:16]: because the skills required to be effective are changing so fast, right? you used to really select for just rote implementation ability and now it is more the AI engineer skill set, right? Where it's like, yeah, how to implement, but actually-Just banging out code is no longer the core job, right? It's, it's actually knowing what questions to ask, knowing how to tie, how to tie together these different AI tools. And so the interviews that we give now I think are way harder than they've ever been.Peter [00:24:46]: But we also allow, right, selective use of AI tools to solve the problems. And I think in that you start to see more of a bimodal distribution of engineers, right? You start to see like wow, there's, there's this subset of people that they really get it. Like they're, they're all in and they've, they've clearly invested the hours needed to learn these tools and how to be effective.Peter [00:25:09]: And then there's sort of the group of people that haven't done that, and that the productivity gap is just enormous. And so we're, we're trying to obviously select for the people that are really into this.Qasar [00:25:20]: I first wrote the my AI engineer piece three years ago, and when I first wrote about it, I was like, “Actually, not everyone should be an AI engineer,” ‘cause I think there's a there's an extremist stance where well, every software is an engineer is an AI engineer. And my actual example of people who should not be adopting AI was embedded systems and operating systems, and database people. Are they adopting AI?Peter [00:25:41]: I think it's the classic bitter lesson, topic, which is the Six months ago I would've said the same thing, but it's, it's becoming super useful for every domain.Qasar [00:25:53]: I'm sure.Peter [00:25:54]: Right? Like,Peter [00:25:56]: there was, I think six months ago, or maybe a year ago, if you tried to use, let's say the latest Claude model for writing shaders, GPU shaders, the results were probably underwhelming. And if you use the latest model now to do that kind of task, you're a little bit blown away, like, “Wow, that actually worked. That's amazing.” And we see the same thing in the embedded realm. No question though, especially when you get into safety critical systems, the human validation isPeter [00:26:25]: is 100% key. Like I You're not gonna trust your life to a an AI written software that's, that's not been very carefully, checked by humans. And so I think now the really the challenge is about that appropriate level of human validation for these safety critical systems.Verifiable Rewards, Evals, and Neural SimulationAlessio [00:26:41]: How do you think about, yeah, touching on the simulation side, I think verifiable reward and reinforcement learning is, like, the hottest thing. What have you done internally to build around that? And like, what gives you What makes you sleep at night? Like, if somebody's like, just web coding something or likeAlessio [00:26:57]: wants to try something new, you have like a good enough system. Because I think the opposite is also true, is like if it's super easy to write anythingAlessio [00:27:04]: then it puts a lot of work on like the verifiableAlessio [00:27:07]: side of it. Like, what does that look like for people?Peter [00:27:10]: Yeah. So verifiability, a broader bucket of like evaluations, right? Like how do you evaluate the results that you're, you're getting? I think this is probably the hardest problem right now, because the As the models get better, it can be harder and harder to find the faults on the system.Peter [00:27:29]: And so like the problem of doing proper eval to find those faults, like that problem also keeps getting harder as the models get better. But it's no less important than it's ever been, right? You still there are still going to be edge cases that are not met and whatnot. And so it's, it's a big area of investment for us. On the reinforcement learning topic, the key thing is there's all these new requirements that come to be in the latest generation of these technologies. So for example, end-to-end is the big thing right now in autonomy and physical AI, which is you can now train these models that can effectively take sensor data in and then put control signals out, and get really good results out of that. But the way that you train and improve those models is really different from the previous generations. And so to do reinforcement learning on an end-to-end model, you now need to actually simulate all the sensor data, right? So then this becomes a we call our, work in this neural simulation, but it'sPeter [00:28:26]: think of it like a hybrid of Gaussian, splatting and diffusion methods, and where you really care about performance. Like performance is everything. If you can't do enough simulation fast enough and cheap enough, you actually can't get results that are worthwhile, in the end. It also gets to a lot of our work in embedded systems, which is like performance critical work, and that performance optimization, performance criticality, it carries over to a lot of the model training work. because, like, the only way to make it affordable is it has to be really fast.Qasar [00:28:58]: I think it's worth a few minutes talking about our own, evolving thoughts on verification and validation withinQasar [00:29:05]: kind of, traditional simulators, which are, you can think of like vehicle dynamics or something like that, which you're just taking textbooks and taking those formulasQasar [00:29:13]: and putting them into software, to like now this neural sim/world model universe. I think that's an interesting topic.Peter [00:29:20]: Yeah. So in more traditional development, right, you oftentimes would have, more black-and-white answers to questions.Peter [00:29:28]: And so the in Europe as an example, there's, a regulatory, system, it's called Euro NCAP. It's the European New Car Assessment Program, and as part of that, the vehicles have to pass a bunch of tests, and those tests actually, include, safety systems. So automatic emergency braking for a child that runs in front of a carPeter [00:29:51]: or let's say an occluded child that runs out and you hit it. And so you have You end up with sort of these binary answers of like, well, did the car under test pass this specific test? And there's a very well-known set of test casesPeter [00:30:05]: that the vehicle has to pass. And that was how the industry worked, let's say, until 10-ish years ago. But what's changed now is with these models, everything is statistics, right? Like you no longer have a black-and-white answer, but it's like, well, how many orders of magnitude or how many nines of reliability can I get in the system, and how can I, how can I prove that to be true? And the big unlock honestly for physical AI as an industry is that these models are just becoming much more reliable. Right? Things like things actually work a lot better. It's like the number of nines you can get out of these systems are now good enough that it actually becomes cost effective to really deploy these things. And so the big shift in, so verification and validation has been from a little bit more of a Again the past it was strictly requirements, and are you meeting or not? And now it's more of a statistical, verification and validation case where it's all about how many nines of reliability and meantime between failures, that sort of thing.Statistical Validation, Regulators, and the Cruise LessonSwyx [00:31:04]: And is the target audience regulators or even the customers are yeah, if you I imagine the customers are bought in, and it's mostly regulators that need to be satisfied.Peter [00:31:15]: We do work with the US government, we do work of course with the European governments and the government of Japan, and the government is not like an AI lab by any means.Peter [00:31:25]: So Swyx [00:31:26]: They just care about the outcome.Peter [00:31:27]: They care about the outcome.Peter [00:31:28]: And so we do education, in that regard, and like so sort of teaching about, “Hey, this is how we think validation should be done, and this is an approach that we think is reasonable,” and how to think about like when is a driverless system actually safe enough to go on the roads and that sort of thing. But I wouldn't say that the government is asking for it. It's like we're more teaching the government in that, in that sense. It's honestly, it's more so for our own, our own comfort, right? Like, we want to build very safe systems, and then of course our customers care deeply about that as well. But in that context we're also typically educating our customers.Qasar [00:32:01]: Yeah. Our first, our first core value is on round safety. So I think we can't underline enough that, us also verifying and validating that the systems that we're deploying are safe to us is probably as important as, like, some regulator or a customer saying,Swyx [00:32:19]: Of course. Okay. Yeah.Swyx [00:32:20]: You have to satisfy yourselves.Peter [00:32:22]: As I say, as a whole across the world, regulation oftentimes it's like a almost lowest common denominator. But like, you really have to substantially exceed what the regulators are expecting to make good products.Swyx [00:32:33]: Yeah. One thing I often talk about, I think and I try to make this relatable to the audience also, is Cruise, where they had an accident that basically ended the company. I wonder if people overreact to single incidents, because incidents are going to happen regardless, right? ‘Cause it's a statistical thing, but as long I don't know if regulators understand that, you cannot extrapolate from a single incident, but we do because that's all we have to go on. And your sample sizes are necessarily gonna be lower than, I don't knowSwyx [00:33:00]: consumer driving.Qasar [00:33:01]: Yeah. I think the Cruise example wasn't a technology failure. there was The real, compounding issue there was just how did the company talk to the regulators and what was their kind of behavior, and I think that became more of the issue. If you look,Peter [00:33:19]: It isn't It definitely was a technology failure, but it was made much worse by theSwyx [00:33:23]: Put the car back on the woman.Qasar [00:33:25]: Yeah. And let me put it another way. There is a version where Cruise still exists.Swyx [00:33:29]: right. Right.Qasar [00:33:30]: Right. It'sSwyx [00:33:30]: It was like the last strawQasar [00:33:31]: ItSwyx [00:33:31]: in like a long chain ofSwyx [00:33:33]: like issues.Qasar [00:33:33]: So do you feel like ATG had that horrific accident or someone actually dying, because, that was a homeless person crossing the street? So yeah, I think we can't understate enough that ultimately, like, statistical validation of something, that's one part of it, but it's not the only part of it. Like, consumer and let's say, mainstream adoption of these technologies is also gonna be part of that conversation. I think companies like Waymo are doing a lot of service positively to the industry in the sense of they're, they're setting a high benchmark and they're showing, kind of in a very responsible way how to, how to deal with these. There have been Waymo incidences as well. They've just not been as significant as the Cruise one that you mentioned. But yeah, so I think you'll just continue to see that. I think probably the long term question is really gonna be, again, around Like it is very clear humans are way worse drivers statistically.Qasar [00:34:29]: Like, there's no, there's no debate. And so at what point But we're emotional animals.Swyx [00:34:34]: Yeah. So my thing is, like, we have to get to a point as a society where we accept horrific accidents that would never happen by a human because statistically we understand that it is safer overall. In the same way that planes, they're safer, than I think they're the safest mode of transport that we have.Qasar [00:34:50]: Yeah. it's more dangerous to drive to the airport than it is to get on a flight.Qasar [00:34:53]: So if you're everQasar [00:34:54]: if you're ever getting nervous about getting on a plane, just think “I just gotta get to the airport.”Swyx [00:34:58]: Yes, we're flying.Qasar [00:34:59]: If I get to the airportQasar [00:35:00]: I'll be good.Swyx [00:35:00]: But then it's, planes also concentrate the tail risk if planesQasar [00:35:03]: Yeah. AndPeter [00:35:04]: And I was, I don't think we honestly have to worry about there ever being, accidents from these systems that are like much worse than what humans would cause, ‘cause humans do terrible things.Peter [00:35:14]: Like, people fall asleep at the wheel all the time.Swyx [00:35:16]: I have.Swyx [00:35:17]: Like, I'll call, I've been a drowsy driver.Peter [00:35:19]: Kinda drunk drivers, and that'sPeter [00:35:20]: that's the extreme end of the example. But these AI systems, you have redundancies, you have fallbacks. Like, there's many things have to go wrong for there to actually be a something catastrophic because there's, there's so many, fallbacks that these systems have.Alessio [00:35:36]: your simulation is like so vast because there's so many use cases. What are, like, maybe things that worked in a simulation and then you put it out and it's like, “F**k, this isAlessio [00:35:45]: this just did not work at all?”Peter [00:35:47]: Yes.Alessio [00:35:47]: IsPeter [00:35:47]: That's maybe a bit of a misconception, about simulation there. So let me go a little bit, more technical on this. So at first go, no simulation is going to represent the real world. There's always a process of this, sim to real matchingPeter [00:36:02]: where you actually, you need the real world feedback to basically feed into the parameters that are being used in the simulator, and you have to do that, it's like this validation flow, a number of times until you can get some confidence that, like I think the simulator is now accurately representingPeter [00:36:19]: what's gonna happen in the real world. Now, if you have a situation where you've done that full validation and you thought that it was accurate and then there's something different, those are much trickier cases, and that's, that absolutely can happen, but really I think the validation process is a really important part. You can never skip the simulation validation process, like where you're actually ensuring that, hey, the actual, my sim to real gap here is small enough that I can trust these simulation results. And there's, there's so many fun things that you can do when you get into it. Like, I'll, I'll give one fun example that came up recently is like in these humanoid robotics, systemsOverheating actuators is a real problem, right? So obviously phenomenal demos. IPeter [00:37:01]: The most amazingAlessio [00:37:02]: For 10 minutes.Peter [00:37:03]: The most amazing I can get. I love, I love watching robots do acrobatics like everybody but the these systems actually overheat, right? If, like, And one of the ways you can use simulation though is you can actually have that, the temperature of those actuators be one of the parameters that's representedPeter [00:37:18]: in the simulation. And if you're doing reinforcement learning over a certain task, then the robot can actually adjust its motions in the simulation to account for the fact that, oh, it knows that as it's moving, it's actually beginning to overheat this motor. But if you didn't have that parameter of, let's say, the heat of that motor represented in the simulation initially, then your RL policy might It will disregard that. And now you run that on the robot and the robot will overheat and fail.Alessio [00:37:43]: I guess the question is, like, how do you have all of these parameters taken care of while also understanding the deployment environment? Like, temperature is like a great example, right? WellAlessio [00:37:53]: why did you make my robot worse when it runs in like a freezer?Alessio [00:37:57]: So it actually shouldn't worry about that. it's like, yeah, how do you design these simulations?Peter [00:38:02]: This is honestly the This is what makes simulation so hard, right? it's because you Simulation is fundamentally about you're trying to optimize the development of a system, right? Like, how can I build this system faster and better and cheaper and what are all the levers that I have to actually accomplish that? And because simulation's just a software program, you can, you can change it a lot more easily than you can hardware systems. And then what's particularly awesome about the let's say, world models and using that as a part of simulation is now the simulation doesn't just scale with, let's say, adding new math equations inPeter [00:38:36]: but we can actually scale the simulation environment now with additional real world data and that also unlocks a whole new field of robotics.Qasar [00:38:46]: There is a meniscus line where you cross where still doing real world testing is better. there's, in this, sim-to-real gap, you can reproduce reality at exceedingly expensive costs and this So nothing is free. So really you have to you're finding that line where you're getting great performance, you're getting great feedback, whether it's on the training side or on the eval side, but it's way cheaper than doing it in the real world. At some point it, that doesn't make sense. And so even, from our earliest days in autonomy, our view was you're still gonna do real world testing. You There's, there's not, there's not this, magical land where you're not gonna do that. And maybe even like a more nuanced version of this in like traditional software development is, most of your testing for software in a vehicle, 95% of that can be like traditional CI/CD kind of, flows that you would have in traditional web development. But once you have Now you, let's say you have a truck. Well, you can do like 4% of those in like a rig which has all the components, the electrical and electronics of a truck, but doesn't have, it doesn't have the tires and it doesn't have the And then you have the 1%, which is actually the vehicle. There's something There's a similar analogy in terms of using simulation for intelligent systems. You can do a lot in a simulator, but in using world models, but ultimately it's, it's physical AI. So you're gonna deploy it on physical machines andQasar [00:40:17]: the freezer example comes to, comes to light.Alessio [00:40:20]: The world model thing has been to me the hardest thing toAlessio [00:40:22]: wrap my head around. Like we have Faith Eliyon on the podcast.World Models, Hydroplaning, and Cause-Effect LearningQasar [00:40:25]: We've been doing a small series with like another Intuition company, General Intuition as well.Qasar [00:40:31]: yeah, and I mean, lots of, lots of coverage on NeRFs and yes.Alessio [00:40:34]: Yeah. It feels like we talk with about, the heliocentric system, right? It's like in a world model, if you just feed visual data, the model might learn that the sun spins around the Earth. It makes sense, right? And it's like, well, not really. And I think what are like some of these other things that like hydroplaning is one thing I think about, is like can a world model understand hydroplaning and like what amount of water like causes it to happen? And it's like, yeah, to me it's like I don't understand how you guys do it. I guess it's like the real thing is like when you're doing both cars and the highway in Japan versus the excavator in a mine in,Qasar [00:41:13]: ArizonaAlessio [00:41:13]: wherever you're Arizona, wherever you're deploying them.Alessio [00:41:15]: How much of it are you relying on the world models to like generate the simulations for you and then try and close the gap after versus like giving the world models as a tool to your engineers to like curate the simulations if that makes sense?Peter [00:41:28]: Yeah, totally. So yeah, I can say at a pure engineering level, I think if you're hoping to do real world deploys and you're purely relying on a world model approach, you probably won't get to something that works, before you go bankrupt. So there is just a very practical mindset of like, world models are amazing and they're extremely useful for a lot of use cases, but there are a lot of other things that you need to do to actually get something started and something deployed and working. most fundamentally, world models are all about It's understanding the world, but also understanding what's going to happen. It's like the cause-effect relationship.Peter [00:42:01]: Right? And so like it, right, if you have a take some sort of construction tool, and that construction tool is gonna be doing some work on the Earth in some way, it's gonna be moving earth, the world model needs to understand that cause-effect relationship. Like, okay, when I, when I take this material from here and put it over there and now I have things that are over here and not over there anymore and that cause-effect, relationship. data obviously is a is a big problem. The hydroplaningPeter [00:42:26]: one is actually a really great example because it's actually quite non-obvious sometimes. Right? It's like, well, it's, it's raining and well this road, has, let's say the appropriate curvature to it so the water is running off the road and cars are driving faster here and then you approach a road that's very flat and water is now puddling on that road and all of a sudden cars are driving slower because when they were driving faster they were starting to lose control. And there are a lot of visual nuance, very nuanced visual cues in the scene and so I do think in the world model concept there's a good chance that the model actually would learn that you should just drive slower when these visual cues exist, and that's obviously the beautiful-The beauty of, these kinds of models where they just, they learn these non-obvious things.Swyx [00:43:14]: It doesn't need to know about hydroplaning to know that it needs to drive slower.Peter [00:43:17]: Yes.Swyx [00:43:17]: I guess it's Yeah. I wanna ask questions about, also deploying models. I presume, like, you use a lot of these world models for training data and simulation, but what about deploying it onto the systems in production? Presumably you have you have, like, GPUs on deviceOnboard vs. Offboard: Latency, Embedded ML, and DistillationSwyx [00:43:36]: but they're I keep saying on device. What's the what's the right term for that?Peter [00:43:40]: On machine.Swyx [00:43:41]: On machine.Peter [00:43:41]: Or embedded, yeah.Swyx [00:43:42]: Yeah. What is the embedded world like? because for people who are not used to that world, this is very alien.Peter [00:43:49]: Yeah. So it's actually We call it onboard and off board.Peter [00:43:52]: So like, onboard software and off board software.Peter [00:43:54]: And the great thing about off board software is you don't have to care about time, and you can run really large models, right? So you can, you can say, “Well, this model, I don't care if it takes one second for it to give me a result or 10 seconds for it to give me a result, because we have time.” And the models can be really big, and they can run, in a data center or on a on a huge GPU and you can obviously have distribute to compute, et cetera. But onboard you don't have any of those benefits. You're like, “Well, I need I have this many milliseconds where I need an answer from this model.” And so a lot more of the energy then is about, think of it more like distillation and it's like truly efficiency and like, literally every fraction of a millisecond counts. And you can't have a situation where the model takes too long because then the vehicle can't actually function.Peter [00:44:42]: And so you can, you can still use a lot of the same techniques, and the models themselves you can think of as like a derivative of larger models that you can run offline, and then you're, you're trying to just get a model that is still performs really well but it's, it's a it's smaller, small enough version that you can then run on this embedded system where you care about latency and power.Qasar [00:45:03]: Yeah. And I think like, the broader point I think which, maybe is not obvious but it's worth saying is in physical AI world, we're not really constrained right now by, like, the intelligence of the models. It's actually what Peter's talking about, it's actually deploying them inSwyx [00:45:19]: The hardware they give you.Qasar [00:45:21]: Yeah. On the hardware you give you.Qasar [00:45:22]: And so And there's just a reality is of safety critical systems. So those end up being the your limiting factorsQasar [00:45:29]: rather than, let's say, a limiting factor for, a foundation model companyQasar [00:45:34]: is gonna be just capital maybe or researchers.Qasar [00:45:38]: So we're, we're in that way dealing with, for us as people who kind of come in that realm with like a very interesting Those constraints force creativity.Swyx [00:45:47]: And I imagine, nobody was deploying or giving you the hardware for transformers back in 2018, whatever, but now they are. What's the evolution like? just peel back the curtains a little bit.Peter [00:45:59]: Yeah. Transformers first off, I think the paper was originally published in 2017.Swyx [00:46:02]: 2017.Swyx [00:46:02]: So there's no time.Peter [00:46:04]: And ISwyx [00:46:05]: But I'm just saying I guess I'm saying, like, embedded ML systems usually, like, a lot less parameters, a lot less compute, and now, like, orders of magnitude more.Peter [00:46:14]: Yeah. absolutely. what I was gonna say though was I think in the in the original paper in 2017, maybe it's in the last paragraph, somewhere in the paper they talk about, like, “Oh, by the way, this technique might be useful for, like, images and videos as well.”Peter [00:46:30]: These last subjects.Peter [00:46:31]: And it took a few years for that impact to really hit. But like, now, we're seeing transformers are everywhere.Swyx [00:46:39]: Yeah. Vision transformers.Peter [00:46:40]: And then then the compute just keeps getting better and better. But you do have this fundamental trade-off, right? It's like you have power, you have cost, and performance and like, getting the right, getting the right mix of those things in an embedded package that can also be, like, shaken and baked in all thePeter [00:47:00]: conditions that these things have to have to operate in. But yeah, I think that they're only going to keep getting better and so we also try to plan our strategy understanding that, we know the rate of improvements of these systems.Swyx [00:47:11]: Yeah. So like, Google just released the Gemma 2B modelSwyx [00:47:15]: that effective 2B model. Is that useful to you guys or is that too big?Peter [00:47:18]: You can run that model on an embedded system, definitely.Peter [00:47:21]: the So yes, it's, it's useful in that regard. The bigger question is, like, what do you use it for in an embedded system? Like, you actually need to customize it quite a bit to make it useful for something. But yeah, you could run a two billion parameter model, definitely.Swyx [00:47:35]: It also interesting, like, what percent is a custom ML model that only does that thing versus a generalist LLMSwyx [00:47:41]: which probably is not that useful actually for your context.Peter [00:47:46]: Like, you, like, you can imagine different use cases, right?Peter [00:47:48]: So theSwyx [00:47:49]: The voice stuff, yes.Peter [00:47:49]: Yeah, the voice test. Totally, yes.Peter [00:47:51]: So for the actual, autonomy elements, that's 100% in-house. We do every bit of that, the data simulation, the model, everything. But when you get into the more generic use cases like voice or voice assistant kind of thing, that's where these more generalist models like Gemma actually can be quite, can be quite useful.Swyx [00:48:09]: Yeah. And then there's also obviously a trade-off between, like, what percent must you do on machine, versus just call home.Peter [00:48:16]: Yeah. It's all about latency.Swyx [00:48:17]: Latency.Peter [00:48:17]: It's all about latency. Yeah.Swyx [00:48:18]: Yeah. Well, like, I think actually in a lot of contexts, especially in the US, you can just have a connection to the web.Qasar [00:48:26]: Yeah. I think though most of our universe is everything has to be fairly, embedded and local because just the nature of Even in the US there's a lot of likeSwyx [00:48:39]: PatchinessQasar [00:48:40]: don't haveQasar [00:48:41]: have coverage, right? And if you look at, like, the old world of autonomy within mining, which is, like, long before transformers and kind of, neural networks, in the like CNN and kind of a universe, they were really just hand-coded, systems. They were just like, this machine is gonna run to that place with thisPeter [00:49:03]: That was our GPS, like very accurate GPS.Qasar [00:49:05]: Yeah. And so that worked, and that worked for 20 years, so why would we actually need to use transformers or kind of more modern end-to-end systems? Mainly because you can only really run a path and run backwards. That provided a lot of value, but m-Not as much as you get when the machine is actually intelligent. It's, it's seeing, it's perceiving, it's acting in a dynamic world.Alessio [00:49:28]: I looked up RTK, real-time kinematic, one to two-centimeter accuracy.Qasar [00:49:32]: Yeah. Fantastic. But the and fantastic in faraway lands where there's not gonna be cell phone coverage.Peter [00:49:39]: Yeah, so it's widely used on the legacy mining and agricultural autonomy systems today. So like, for example, a combine that can be precise within one or two centimeters as it's driving down the field, they use RTK.Qasar [00:49:53]: Yes.Peter [00:49:53]: But it's, it's expensive.Qasar [00:49:54]: Yeah. And it's, it's, it's autonomy, but it's not intelligent in the way that I think all of usQasar [00:49:58]: if in twenty-six we'd be talking about intelligence.Alessio [00:50:00]: In one of your blog posts, you mentioned research on large scale transformers that are similar to those doing modern generative AI. What are, like, the big differences other than, “You're absolutely right. I should steer the car, so you probably wanna remove that?”Peter [00:50:14]: We have a diversified bet strategy internally, and the reason we've done that is because we operate in now a bunch of industries, a bunch of geographies, and each of the approaches has, obviously a different risk to them.Peter [00:50:27]: And so like, we're not going to put all of our eggs in a single basket for a single approach because that approach may no

This week Shawn Tierney meets up with Felipe Polido of Reframe Systems to learn how they are using Automation to change the process of building homes in this episode of #TheAutomationPodcast. Unlock access to the ad free EXTENDED EDITION by joining our channel at https://TheAutomationBlog.com/join or https://youtube.com/@InsightsIA/join. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast, Free Edition: Note: Below member’s will also find an ad-free and extended edition of this episode. To unlock the ad free extended episode, you can become a member here. Watch the Members’ Extended Edition: Listen to The Automation Podcast from The Automation Blog: Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Discover industrial AI at Hannover Messe with SAP's Matthias Deindl, covering embodied AI, productivity-boosting agents, and demos like ginger-shot packaging, digital twins, warehouse robots and partner integrations. Download the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠episode transcript⁠⁠⁠⁠===== This episode explores industrial AI at Hannover Messe (20–24 April) with SAP's Matthias Deindl. Key topics include embodied AI (robots in production, logistics, asset management) and AI agents that enhance productivity and reduce errors. The SAP booth at HMI features a ginger-shot packaging demonstrator, digital twins, humanoid warehouse handling, CNC machining, and partner integrations. Matthias emphasises the importance of accurate, timely data, using SAP Business Data Cloud to enable autonomous tasks like AI-assisted tendering and robot-led inspections. The SAP booth at HMI features a ginger-shot packaging demonstrator, digital twins, humanoid warehouse handling, CNC machining, and partner integrations. The episode envisions seamless disturbance response, improved productivity for an ageing workforce, and stronger human–AI collaboration.  ===== Guest: Matthias DeindlMatthias Deindl is a digital transformation leader focused on discrete industries and supply chains, with more than 17 years of leadership in dynamic, cross-functional environments. At SAP, he currently leads end-to-end product management for Discrete Industries. Previously, he headed supply chain management initiatives across the global SAP Experience Centers network and oversaw the SAP S.Factory Walldorf, helping customers in process and discrete industries accelerate their digital transformation. Before joining SAP, Matthias served as a Group Leader and Product Owner in a corporate IoT startup at Bosch and worked as an Innovation Manager in Corporate Logistics. Earlier in his career, he was a Project Lead and Head of Department in R&D at RWTH Aachen. He has collaborated with customers across automotive, aviation, pharmaceuticals, mechanical engineering, and logistics. Matthias holds a Diplom in industrial engineering from the Karlsruhe Institute of Technology and a doctorate in mechanical engineering from RWTH Aachen.Host 1: Richard Howells⁠⁠⁠⁠Richard Howells⁠⁠⁠⁠ has been working in the Supply Chain Management and Manufacturing space for over 30 years. He is responsible for driving the thought leadership and awareness of SAP's ERP, Finance, and Supply Chain solutions and is an active writer, podcaster, and thought leader on the topics of supply chain, Industry 4.0, digitization, and sustainability.Host 2: Sin ToSin brings over 15 years of experience in the digital media and technology industry – primarily in marketing, business development, thought leadership, and editorial. At SAP, they ensure that SAP's supply chain solutions are properly visible with a focus on future trends and sustainable innovations as part of the Thought Leadership & Awareness Supply Chain Team.===== Show Links:SAP Digital Supply Chain: www.sap.com/scm Visit us at Hannover Messe (HMI): Hall 15, Booth F08Follow Us on Social Media : Matthias Deindl:LinkedIn: https://www.linkedin.com/in/mdeindl/   Richard Howells:LinkedIn: www.linkedin.com/in/richardjhowells Sin To: LinkedIn: www.linkedin.com/in/sin-to-5334208 SAP Digital Supply Chain:LinkedIn: www.linkedin.com/showcase/sapdsc/ Please give us a like, share, and subscribe to stay up-to-date on future episodes!  ===== Chapters: 00:00:00 Vision for AI Supply Chains00:01:51 Meet Matthias and Industrial AI Today00:02:14 Two AI Tracks Robots and Assistants00:03:30 Data Foundations and Business Data Cloud00:05:04 Deployment Challenges and Quick Win Use Cases00:06:46 Embodied AI Inspection Robots00:09:51 Resilience Roadmap Transparency to Agents00:12:25 Human Machine Collaboration at the SAP Booth00:15:41 Ecosystems and Partner Integration00:19:17 Closing and How to Find SAP at Hannover Messe

Nikki Gonzales has built a career at the intersection of industrial automation, software, and systems thinking, and in this episode, she makes the case that the next chapter of manufacturing won't be defined by AI alone. It will be defined by how well people understand process, data, machines, and the interfaces that connect them. The future of automation is as much about human judgment and lifelong learning as it is about smarter technology. A big part of that story runs through the human-machine interface. The HMI has evolved from a control screen into a communication layer between machines, operators, plant systems, and increasingly, AI-enabled tools. The conversation explores how open standards, AI assistants, scripting support, and emerging protocols like MCP could expand what industrial systems can do, while also lowering the barrier for more people to work with them. But the episode is not a story about technology replacing expertise. We also discuss technology raising the premium on real understanding. Gonzales argues that even as AI becomes more capable, foundational knowledge of physics, process, controls, and manufacturing systems still matters. She also makes the case that careers in this space are built not just through technical skill, but through curiosity, relationships, mentorship, and the willingness to keep learning.In this episode:How NVIDIA's Inception program is helping a 30-year-old HMI company innovate like a startupWhy HMIs are a great starting point for applied AI projectsWhat MCP can make possible in industrial automation that a standard API connection cannotHow AI could lower the barrier to entry in automation while raising the bar for process knowledgeWill the future of skills be more specialized, or more generalized?3 Big Takeaways:The HMI may be one of the best places to start with applied AI in manufacturing. The HMI already sits at the intersection of the machine, the PLC, plant systems, and operator decision-making, which makes it a natural place to aggregate data and connect AI tools. In that sense, the future of applied AI in manufacturing is about smarter interfaces that can translate, contextualize, and move information where it needs to go. AI will make automation more accessible, but not less demanding. Nikki argues that AI can reduce the barrier to entry by helping newer users with scripting, debugging, and development workflows, especially on the HMI side. But she is equally clear that these tools raise the premium on people who understand process, physics, controls, and how manufacturing systems actually work, because the consequences of getting it wrong are too high. The future automation workforce will be built as much through community as through technology. Through Automation Ladies and OT SCADA CON, Nikki makes the case that technical careers are shaped not only by tools and training, but also by mentorship, relationships, and exposure to the full range of roles in the industry.Resources in this Episode:Connect with Nikki on LinkedInLearn more about Automation LadiesMore links & resources: https://techeWe want to hear from you! Send us a text.Instagram - Facebook - YouTube - TikTok - Twitter - LinkedIn

This week Shawn Tierney meets up with Mohua Ghosh of Schneider Electric to learn about their AI Assistant for PLC Code Generation in this episode of #TheAutomationPodcast. Unlock access to the ad free EXTENDED EDITION by joining our channel at https://TheAutomationBlog.com/join or https://youtube.com/@InsightsIA join. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast, Free Edition: Note: Below member’s will also find an ad-free and extended edition of this episode. To unlock the ad free extended episode, you can become a member here. Listen to The Automation Podcast from The Automation Blog: Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

This week Shawn Tierney meets up with Steven Mustard to talk about his new book on Operational Technology (OT) System Risk Management in this episode of #TheAutomationPodcast. To learn more about becoming a member, visit https://TheAutomationBlog.com/join or https://youtube.com/@InsightsIA/join. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast: Note: To support our work and keep new episodes coming, consider becoming a member here. Listen to The Automation Podcast from The Automation Blog: Links to Steven’s Book: Amazon Link Publisher Link Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Carl Gould, CTO and co-founder of Inductive Automation, joins hosts Phil Seboa and Ed Fuentes for an in-person conversation recorded in Australia ahead of the Ignition Everywhere event in Brisbane.Carl traces Ignition's journey from FactorySQL in 2003 to the 8.3 release, which introduces file-based configuration, Git and GitOps compatibility, Perspective offline mode, and a new architecture for managing distributed OT systems at scale. He breaks down the three design principles that have guided the platform from day one (cost, convenience, and capability), shares his evolving take on AI in industrial automation, and explains why he calls the IT/OT divide "a fictional line."In this episode, we discuss:The 8.3 release: file-based config, GitOps, deployment modes, and Perspective offlineScaling from thousands of tags to millions with distributed, decoupled architecturesWhy AI in industrial automation is a means to an end, not a product in itselfThe community and culture behind Ignition's worldwide growth---------------------------This episode is proudly made possible by PLCnext TechnologyPLCnext Technology is the ecosystem for industrial automation consisting of open hardware, modular engineering software, a global community, and a digital software marketplace.Learn more at:⁠⁠⁠https://www.plcnext-community.net/news/synergy-edge-cloud/---------------------------FlowFuse at Hannover Messe 2026Discover how FlowFuse empowers you to build, deploy, and scale industrial automation -- your way. Visit FlowFuse at Hall 014, Stand K26 during Hannover Messe (April 20-24, 2026) and experience live demonstrations of FlowFuse connecting the entire industrial stack -- from PLCs on the shop floor to MES, ERP, and cloud services -- enabling real-time industrial connectivity, data integration, and AI-powered operations.Let's transform industrial data together -- live, integrated, and in real time.Claim your free pass and learn more: https://flowfuse.com/events/hannover-messe-2026/---------------------------Carl Gould is the CTO and co-founder of Inductive Automation. He has been building and guiding the Ignition platform since 2003. Under his leadership, Ignition has grown from a SQL connectivity tool into a comprehensive platform used across industries worldwide for SCADA, HMI, MES, and IIoT applications.Connect with Carl Gould on LinkedIn: https://www.linkedin.com/in/carl-gouldLearn more about Inductive Automation: https://inductiveautomation.comConnect with Phil on LinkedIn: ⁠https://www.linkedin.com/in/philseboa/⁠Connect with Ed on LinkedIn: ⁠https://www.linkedin.com/in/edfuentes/

This week Shawn Tierney meets up with Johann Kotze of Rockwell Automation to learn what’s new in FactoryTalk View 15 & 16 in this episode of #TheAutomationPodcast. Unlock access to the ad free EXTENDED EDITION by joining our channel at https://TheAutomationBlog.com/join or https://youtube.com/@InsightsIA join. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast, Free Edition: Note: Below member’s will also find an ad-free and extended edition of this episode. To unlock the ad free extended episode, you can become a member here. Listen to The Automation Podcast from The Automation Blog: Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

In this episode of Manufacturing Hub, Vlad and Dave sit down with Travis Cox and Kevin McCluskey from Inductive Automation to unpack what was actually proven at ProveIt and why it matters for teams trying to modernize plants without building a fragile mess of point to point integrations. If you have ever looked at a shiny demo and wondered what the real architecture looks like, how it scales beyond a single line, and what it takes to roll out across multiple sites without turning every change into a high risk event, this conversation is for you.Travis and Kevin walk through their ProveIt Enterprise B build and the thinking behind it. The core idea is simple but powerful: treat the factory like a system that needs a shared digital infrastructure, built on open standards, where data is contextualized and reusable. They break down how they used Ignition Edge close to PLCs for resiliency, local HMIs, and disciplined data modeling, then moved data through MQTT into a Unified Namespace so multiple applications can consume the same trusted signals and context. This is the difference between “we can connect to anything” and “we can scale without rewriting everything every time the business changes.” Open standards show up repeatedly in the conversation because ProveIt is specifically designed to force interoperability and practical implementation tradeoffs. Inductive Automation has also written about ProveIt as a place where MQTT, OPC UA, and SQL show up as real foundations rather than slogans.From there, the episode gets into the part that should make both OT and IT teams pay attention: modern deployment practices applied to industrial applications. Kevin outlines a clear maturity path from a single designer workflow to version control, then to containerized deployments, and finally to full GitOps style promotion across dev, staging, and production using tools like Argo CD, Helm, Kubernetes, and release promotion concepts that look like what the software world has used for years. Argo CD is explicitly built around Git repositories as the source of truth for desired state, which is exactly why it fits this style of deployment. The live portion of the conversation demonstrates how fast this can get when the infrastructure is treated as code: they spin up a brand new “site four” by submitting a form, generating a pull request, merging it, and letting the pipeline do the rest.Timestamps00:00 Welcome back and why this ProveIt recap matters01:35 Meet Travis Cox and Kevin McCluskey from Inductive Automation03:10 What ProveIt is and the key vendor questions it forces05:20 Enterprise B architecture overview from PLC to Edge to site to enterprise07:30 HMI walkthrough across liquid processing, filling, packaging, palletizing09:05 Why deploy Ignition Edge instead of only a centralized site gateway12:05 Design once, reuse everywhere and what that means for scaling quickly14:35 On prem realities versus cloud infrastructure in the ProveIt environment17:10 MCP, n8n workflows, and bringing live operational context into AI20:40 i3X style API access to models, history, and alarms for interoperability23:15 GitHub, Docker Compose, Helm, Kubernetes, Argo CD, Cargo and GitOps promotion36:55 Spinning up a new site live and what it changes for multi site rolloutsAbout the hostsVlad Romanov is an electrical engineer and MBA who has spent over a decade building and modernizing manufacturing systems across industrial automation, controls, and plant operations. Through Joltek, Vlad works with manufacturers to assess current state OT foundations, reduce modernization risk, improve reliability, and build internal capability through practical training and standards that stick.Dave Griffith co hosts Manufacturing Hub and brings a practitioner lens focused on what works on the plant floor, how architectures survive real constraints, and how industrial teams can modernize without breaking production.About the guestsTravis Cox is Chief Technology Evangelist at Inductive Automation and has spent over two decades helping customers and partners design scalable architectures, apply best practices, and deliver real solutions with Ignition.Kevin McCluskey is Chief Technology Architect at Inductive Automation and works with organizations on architecture decisions, platform direction, and enabling the next generation of industrial applications.Learn more about Joltekhttps://www.joltek.com/serviceshttps://www.joltek.com/book-a-modernization-consultation

This week Shawn Tierney meets up with Hany Fouda of Schneider Electric to discuss What’s Driving Open Automation initiatives in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 264 Show Notes: Special thanks goes out to Hany Fouda of Schneider Electric for coming on the show, and to Schneider Electric for sponsoring this episode. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

In this episode, we dive deep into the fascinating world of neurocardiology with Jeff Goelitz, Director of Education at the HeartMath Institute. For over 35 years, HeartMath has been at the forefront of researching the "heart-brain" connection, proving that the heart is far more than just a mechanical pump. Jeff explains the revolutionary concept of "coherence"—a state of physiological balance where the heart, brain, and nervous system work in harmony to reduce stress and improve mental clarity. We explore the practical applications of HeartMath techniques for high-stress professions, including first responders, professional athletes, and the military. Jeff shares insights into how "heart rate variability" (HRV) serves as a key measure of our resilience and how simple breathing techniques can help us reset our nervous systems after trauma or daily stress. Whether you are a parent, an educator, or someone looking to manage anxiety, this episode provides the scientific foundation and actionable tools to tap into your heart's intelligence. Key Takeaways: ·         Beyond the Pump: Understand why the heart is now classified as an endocrine gland and a sensory organ with its own "brain" of 40,000 neurons. ·         The Power of Coherence: Learn how a state of heart coherence facilitates better decision-making and "cortical facilitation" in the brain. ·         Resilience for First Responders: Discover how HeartMath is being used to help firefighters and soldiers manage PTSD and maintain a "baseline of calm" in dangerous situations. ·         Measuring Inner Balance: An overview of HRV technology and how biofeedback sensors like the "Inner Balance" help track emotional stability. ·         The Heart-Brain Dialogue: Why the heart sends more neural traffic to the brain than the brain sends to the heart. About Jeff Goelitz   Jeff Goelitz has gained vast knowledge, experience and understanding of behavior and social and emotional learning in the many years he has been with HMI. His 35 years of experience, including five as a private school teacher, have helped him become a leader in the development of stress management and education solutions for children and adults. He has spent two decades practicing and teaching the HeartMath System of tools and technology, and his expertise has helped HMI find practical solutions for lowering student test anxiety and improving test score   Social links for Jeff Goelitz https://www.facebook.com/jeff.goelitz.1/ https://www.facebook.com/HeartMathMyKids https://www.heartmath.org/   Social links for Doug Beitz Facebook: https://www.facebook.com/dougbeitz/ Instagram: https://www.instagram.com/dougbeitz/ Website: https://buymeacoffee.com/dougbeitz Spotify: https://open.spotify.com/show/6mQ258nugC3lyw3SpvYuoK?si=7cec409527d34438 Apple Podcasts: https://podcasts.apple.com/au/podcast/intuitive-conversations-with-doug/id1593172364 LinkedIn: https://www.linkedin.com/in/doug-beitz-472a4b338/ TikTok: https://www.tiktok.com/@dougbeitz178  

In this episode of the Harvest Growth Podcast, Jon LaClare sits down with Scott Brown, founder of Snax Depot and VendingAd.com, to explore a surprising but powerful advertising opportunity hiding in plain sight: vending machines.Most advertising today competes in speed mode — scrolling, swiping, skipping, and digital fatigue. But what happens when you reach people in a true moment of pause?Scott shares how modern, AI-powered vending machines equipped with 15-inch HMI screens are transforming everyday snack stops into high-attention marketing moments. With 10-second visual ads placed directly at eye level, local businesses can reach a captive audience in gyms, warehouses, apartment complexes, and office spaces — where repetition, frequency, and exclusivity drive real brand recall.This isn't about chasing clicks. It's about being remembered.You'll learn why physical-world visibility still matters in a digital-first era, how QR codes bridge real-world impressions with measurable online results, and why limiting each machine to just 10 advertisers dramatically increases brand impact.If you serve local customers and want repeated, real-world exposure in places where people actually pause — this conversation may change how you think about marketing.In today's episode of the Harvest Growth Podcast, we cover:Why “paused attention” is more valuable than endless digital impressionsThe psychology of repetition and frequency in local advertisingHow vending machine screens create credibility in physical spacesWhy limiting advertisers per screen increases impactHow QR codes make offline ads measurable and retargetableWhich types of businesses benefit most from vending machine advertisingWhy exclusivity (no competitors per machine) strengthens brand recallHow physical and digital marketing can work together seamlesslyVisit VendingAd.com to learn more or schedule a strategy call to see if this opportunity is a fit for your business — especially if you serve customers in the Boston market.To be a guest on our next podcast, contact us today!Do you have a brand you'd like to launch or grow? Visit HarvestGrowth.com and set up a free consultation with our team.

This week Shawn Tierney meets up with John DeTellem of Siemens to walk through the steps of migrating an existing S7 PLC and its Program to TIA Portal v21 in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 263 Show Notes: Special thanks to John DeTellem of Siemens for coming on the show, and to Siemens for sponsoring this episode. For more information please see the below links: TIA Portal V21 Sales & Delivery Release TIA Portal V21 Technical Slides TIA Portal V21 Trial Download TIA Portal in the Cloud TIA Portal Documentations Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

This week Shawn Tierney meets up with Soroush Karimzadeh of Novarc to discuss their AI-Powered Autonomous Welding Robotics in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 262 Show Notes: Special thanks goes out to Soroush Karimzadeh for coming on the show, and to Novarc for sponsoring this episode. To learn more about their AI-Powered Autonomous Robotic Welding solution, see the below links: Soroush Karimzadeh, LinkedIn, CEO & CoFounder, Novarc Technologies Inc.: https://www.linkedin.com/in/soroushkarimzadeh Novarc Technologies, LinkedIn: https://www.linkedin.com/company/novarc-technologies-inc- Novarc Technologies Website: https://www.novarctech.com/ NovAI™ – Adaptive Welding: The full power of AI and machine vision in welding automation: https://www.novarctech.com/products/novai/ Spool Welding Robot (SWR™): https://www.novarctech.com/products/spool-welding-robot/ Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

【节目简介】大屏，算力，HMI已然成为汽车的兵家必争之地然而，无论你再喜欢你的车，你每天用它的时间也不过2小时。有些人，却会在他的车上一呆就是一天，甚至好几天。他们的头衔是卡车司机然而又有多少卡车升级了自己的仪表和车机呢？本期《孤岛车谈》新熠和三位HMI专家聊聊这个使用时间最长、需求最特殊、被车企了解却最少的群体的诉求该如何满足的问题。美国一卡车司机的五个屏美国一卡车司机的五个屏美国一卡车司机的五个屏2022 Tesla Semi内饰2022 Tesla Semi内饰2025 Peterbilt 579EV 内饰查尔姆斯大学的低科技卡车HMI提议查尔姆斯大学的低科技卡车HMI提议 查尔姆斯大学的低科技卡车HMI提议苇渡卡车的内饰吉利远程星瀚卡车的内饰起亚PV5的屏幕基于Google Automobile【话题成员】高峰 商用车智能座舱和交互软件开发经理June 交互设计师侯依萱 人因工程师剪辑 PSC，猫又，许新熠，罗新雨片尾曲 All I do is drive by Johnny Cash (1974)【时刻文稿】26:38 特斯拉Semi的内饰49:45 HMI的一致性是基操1:17:57 收集用户需求1:28:43 如何用HMI给卡车司机情感慰藉1:39:12 卡车的大屏该如何分配空间1:46:12 功能的门槛不能太高1:49:10 账号体系打通【参考链接】【【专属】乘用车底盘系统开发 车辆动力学原理应用与正向开发工程实践 吴旭亭 系统构建车身动力学底盘知识体系书籍】#小程序://机械工业出版社旗舰店/商品/I4N8mLuPmjWkmRt【官网 车用动力电池系统设计与制造 中国汽车工程学会 电芯产品设计 电池系统产品设计 动力电池产品设计制造方法技术书籍】#小程序://机械工业出版社旗舰店/商品/P8isKji8jO5DkNc【汽车创新：前沿技术背后的科技原理】#小程序://机械工业出版社旗舰店/商品/7tltQzCQfJUWRVi【官网 广义车规级电子元器件可靠性设计与开发实践 左成钢 系统介绍汽车电子零部件的可靠性设计与开发 汽车电子 汽车工业技术书籍】#小程序://机械工业出版社旗舰店/商品/dBujAN68sEk1Rzl【智能驾驶：产品设计与评价】#小程序://机械工业出版社旗舰店/商品/Q8KWriuNDGdzlSs【官网 智能底盘关键技术及应用 线控执行 融合控制 失效运行 张俊智 智能底盘核心线控执行系统关键技术书籍】#小程序://机械工业出版社旗舰店/商品/5R5ZjdGhScib14ALow-Tech HMI for trucks - A study in driver-centered interaction. (Chalmers University of Technology, 2025): https://odr.chalmers.se/items/53fad8f4-c580-4436-b2cc-667f91610c86

This week Shawn Tierney meets up with Karim Kozman of Schneider Electric to discuss What’s Next for Industrial Automation in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 261 Show Notes: Special thanks goes out to Karim Kozman of Schneider Electric for coming on the show, and to Schneider Electric for sponsoring this episode. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

This week Shawn Tierney meets up with Manish Sharma of Emerson to learn about the Next Generation of PACSystems Industrial PCs in this episode of #TheAutomationPodcast. Unlock access to the ad free EXTENDED EDITION by joining our channel at https://youtube.com/@InsightsIA/join or https://TheAutomationBlog.com/join For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast: Note: Below is an ad-free extended edition of the show that’s a member perk. To unlock the extended episode, become a member here. Listen to The Automation Podcast from The Automation Blog: Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

This week Shawn Tierney meets up with John DeTellem of Siemens to learn what’s new in TIA Portal v21 in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 259 Show Notes: Special thanks to John DeTellem of Siemens for coming on the show, and to Siemens for sponsoring this episode. For more information please see the below links: TIA Portal V21 Sales & Delivery Release TIA Portal V21 Technical Slides TIA Portal V21 Trial Download TIA Portal in the Cloud TIA Portal Documentations Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Technology modernization in manufacturing is not a list of shiny tools. It is a sequencing problem. In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith break down why the executive vision for AI often collides with the reality of the plant floor, and what a practical path forward actually looks like when you account for data quality, legacy controls, networking, and the true cost of integration.A core theme in this conversation is imperfect information. Leaders often believe the data already exists because reports exist. But a stack of paper, a few spreadsheets, or a single counter value is not the same as contextualized, trustworthy history that can drive decisions or support advanced analytics. Vlad and Dave walk through why foundational work matters, what teams usually miss during modernization, and how quickly the bill grows when you discover your architecture is outdated, undocumented, or full of dependencies you cannot see until you open panels and start tracing signals.You will also hear a grounded debate on how to think about SCADA, MES, historians, dashboards, and what it would actually mean to “feed data into AI” in a manufacturing context. The takeaway is simple. If you want better outcomes, you need a better understanding of your current state, a clear business case, and a roadmap that prioritizes what matters operationally. Modernization is not one big upgrade. It is a series of decisions that either reduce friction or create it.About the hostsVlad Romanov is an industrial automation and manufacturing expert focused on plant assessments, controls and data architecture, IT and OT integration, and workforce upskilling. Vlad has over 10 years of experience across large manufacturers and complex multi site environments, working from PLC and HMI layers up through SCADA, MES, and ERP integration programs. He is the founder of Joltek, where the mission is to help manufacturers modernize safely, build internal capability, and deliver results that actually survive handoff to operations.Learn more about Joltekhttps://www.joltek.comhttps://www.joltek.com/servicesDave Griffith is an industrial automation practitioner and consultant who works closely with manufacturers to modernize legacy environments, improve reliability, and build practical systems that operators and maintenance teams can support. Dave brings a strong perspective on what is feasible in real plants, where uptime, risk, budget, and organizational readiness drive every decision.Timestamps00:00:00 Welcome and why this month is about technology modernization00:02:10 The real problem with “just add AI” in manufacturing00:04:15 Quick background on Vlad and Dave and the work they do00:05:25 The disconnect between the perfect factory vision and the plant floor00:06:25 Vlad on business cases, integration reality, and infrastructure gaps00:09:05 Dave on imperfect information and why reports are not data00:14:35 What executives actually want from AI and why it is often about people constraints00:20:25 How to get there, hardware first, data normalization, and context00:22:05 Vlad on assessments, legacy hardware, and why upgrades get complicated fast00:39:00 New facility planning mistakes and why early decisions lock you in00:45:10 You have the data, now what, OEE baselines, bottlenecks, and root causes00:58:10 Final takeaways, inventory your architecture and treat data like an assetReferences and links mentionedManufacturing Hub Podcasthttps://www.manufacturinghub.liveProveIt Conferencehttps://www.proveitconference.comAutomate Showhttps://www.automateshow.comIgnition Community Conferencehttps://icc.inductiveautomation.comIf you are watching on YouTube, subscribe so you do not miss the rest of this month's deep dives on hardware, data teams, and practical applications that actually work on real plant floors.

This week Shawn Tierney meets up with Dante Vaccaro of Schneider Electric to discuss Digital Transformations and Trends in Industrial Automation in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 258 Show Notes: Special thanks goes out to Dante Vaccaro of Schneider Electric for coming on the show, and to Schneider Electric for sponsoring this episode. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Send us a textOn this episode of Embedded Insiders, Jim McElroy, Senior Director Sales and Market Development, and Janez Ulcakar, R&D Manager at TASKING, discuss what developers, especially in mission-critical spaces such as aerospace and automotive, need to do to produce efficient and productive safety and security-critical applications. TASKING recently acquired LDRA, and the companies have consolidated under the TASKING brand. Next, Rich and Vin are back with another Dev Talk discussing what it takes to properly design a great HMI, as well as how much effort needs to go into it. They also get some assistance from Renesas, who are making HMIs one of the company's core enabling technologies. Renesas will host a webinar on this topic on February 25th. But first, Editor-in-Chief Ken Briodagh is back from CES 2026. He's giving us a recap on the top trends and technologies on show at the event. For more information, visit embeddedcomputing.com

This week Shawn Tierney meets up with Matthew Dulcey of PRONETIQS, and Stefan Hild of Spur Insights, to learn how PRONETIQS helps Measure, Monitor, and Maintain Control Systems in this episode of #TheAutomationPodcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 257 Show Notes: Special thanks goes out to Matthew Dulcey of PRONETIQS, and Stefan Hild of Spur Insights, for coming on the show, and to PRONETIQS for sponsoring this episode. If you’d like to learn more, please visit the below links: Follow on LinkedIn: https://www.linkedin.com/company/pronetiqs SID 5: https://pronetiqs.com/sid5 IntraVUE: https://pronetiqs.com/intravue Service & Support: https://pronetiqs.com/service-and-support Trainings: https://pronetiqs.com/trainings Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Finding the root cause of an erratic signal can feel like chasing a ghost, especially when your trend lines show noise that shouldn't be there. In this session, we walk through a real-world troubleshooting scenario involving a Yamaha robot simulation where the A3 axis exhibited mysterious spikes. While it initially looked like signal noise or a math error in Studio 5000, the investigation led deep into the interaction between the PLC and the Ignition SCADA system. We explore why a standard cross-reference in the PLC didn't reveal the culprit and how switching to read-only communications finally exposed a hidden bidirectional tag write.We also discuss the common trap of "patching" problems with software filters instead of identifying the source. Whether it is a bad shield on an analog line or an accidental setting in your HMI, understanding the "why" behind the spike is what separates a technician from a parts changer. Additionally, we touch on the challenges of modern Ethernet troubleshooting, the limitations of Wireshark without port mirroring, and why the "View Diagnostics" tool in Ignition is a game-changer for identifying communication conflicts.Helping you become a better technician so you will always be in demandNot sure what video to watch next? Enhance your skills and track your progress at https://controls.tw/yt-courses!Items used in this video:PLC Trainer https://controls.tw/yt-plc-trainersThe above links make these videos possible. Please use them!

Podcast: ICS Arabia PodcastEpisode: Pharma OT Security | 64Pub date: 2025-12-26Get Podcast Transcript →powered by Listen411 - fast audio-to-text and summarizationWe're joined by Andre Froneman, OT Solutions Specialist at Datacentrix — a cybersecurity professional with hands-on experience across the pharma, mining, automotive, and energy sectors.In this episode, we dive deep into pharmaceutical OT cybersecurity, exploring how one of the world's most sensitive industries protects its operations, data, and intellectual property from cyber threats.

Shawn Tierney meets up with Drew Allen of Grace Technologies to discuss Automation, Safety, the history of Grace, and more in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 256 Show Notes: To learn about becoming a member and unlocking hundreds of our “member’s only” videos, click here. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Shawn Tierney meets up with Erik Nieves of Plus One Robotics to discuss Robotics in Warehouse Automation in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Note: As mentioned above, this episode was not sponsored so the video edition is a “member only” perk. The below audio edition (also available on major podcasting platforms) is available to the public and supported by ads. To learn more about our membership/supporter options and benefits, click here. Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 255 Show Notes: To learn about becoming a member and unlocking hundreds of our “member’s only” videos, click here. Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Industrial Talk is talking to Nikki Gonzales, Director of Business Development at Weintek USA about "HMI - Human Machine Interface". Scott Mackenzie hosts Nikki Gonzales on the Industrial Talk Podcast to discuss the human-machine interface (HMI). Nikki shares her background, including her Icelandic roots and career journey in sales engineering and AI startups. She highlights Win Tech, a Taiwanese company specializing in HMIs, which manufactures over 2 million HMIs annually. Win Tech's HMIs are known for their durability, connectivity, and cost-effectiveness. Nikki emphasizes the importance of continuous learning and the challenges in industrial B2B sales. She also mentions her podcast, Automation Ladies, and encourages listeners to connect with her on LinkedIn. Action Items [ ] Check out the Wintec website at automation.io[ ] Listen to Nikki's podcast "Automation Ladies"[ ] Reach out to Nikki Gonzales Outline Introduction and Welcome Scott Mackenzie introduces the Industrial Talk Podcast, emphasizing its focus on industry professionals and innovations.Scott welcomes listeners and expresses gratitude for their support, highlighting the importance of continuous learning in the industry.Scott introduces Nikki Gonzales , the guest for the episode, and mentions the topic of discussion: the human-machine interface (HMI).Scott shares his personal experience with learning Spanish and the importance of passion and desire for continuous learning in the industry. Scott's Journey and Podcast Insights Scott discusses his journey into podcasting, starting eight years ago to understand marketing better.He mentions the importance of communicating company stories in an approachable and human way.Scott introduces two of his podcasts: "Ask Molly" and "Business Beatitudes," highlighting their focus on marketing insights and the soul of the industrial sector, respectively.Scott encourages listeners to check out these podcasts for valuable industry insights. Nikki Gonzales's Background and Career Journey Nikki shares her background, mentioning her move from Iceland to the U.S. in middle school and her father's career as an electrical engineer.She describes her early work experiences, starting with her father's small business and progressing through various roles in sales engineering and marketing.Nikki discusses her career path, including her work with sensor manufacturers, machine vision, motion control, software design, and AI startups.She highlights her recent role with a startup focused on supply chain software and inventory management, and her current position with Win Tech, an HMI manufacturer. Challenges in Industrial B2B Sales Scott and Nikki discuss the challenges of industrial B2B sales, particularly the complex landscape shaped by historical laws and regulations.Nikki explains the historical context of industrial sales, including the restrictions on manufacturers selling directly to consumers and the reliance on regional distributors.They discuss the differences in sales practices between the U.S. and Europe, where such restrictions are considered anti-competitive.Nikki shares her experiences with the complexities of industrial B2B sales, including the difficulties in digitalizing and simplifying the buying process. Win Tech and HMI Technology Nikki provides an overview of Win Tech, a Taiwanese company specializing in HMIs, and its history of innovation in touchscreen technology.She explains the role of HMIs in industrial automation, describing them as the interface between humans and machines.Nikki highlights Win Tech's...

Shawn Tierney recaps his trip to Schneider Electric’s Innovation Summit Las Vegas in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 254 Show Notes: Special thanks to Schneider Electric and their Marketing Partners for sponsoring my trip to this year’s Innovation Summit! Below are all the links I mentioned in this episode: Innovation Summit 2025 – All Videos and Images Modicon Edge I/O NTS: Unbox, Setup & Use with Logix First Time Programming a Modicon M262 PLC Schneider's Altivar Solar ATV320 VSD (P218) Pro-face HMIs & IPCs by Schneider Electric (P195) Schneider Altivar Machine Drives (P187) Harmony HMIs and iPCs from Schneider Electric (P176) TeSys Island: Smart Motor Starters from Schneider Electric (P170) Modicon Machine Level PLC Product Line Update (P161) Next Generation Automation with Schneider Electric (P96) Read the transcript on The Automation Blog: (automatically generated) Shawn Tierney (Host): coming Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Shawn meets up with Travis Cox of Inductive Automation to learn about the new features found in Ignition 8.3 in this episode of The Automation Show. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Show from The Automation Blog: Listen to The Automation Show on The Automation Blog: The Automation Show, Season 2 Episode 37 Show Notes: Special thanks to Travis for coming on the show, and to Inductive Automation for sponsoring this episode so we could release it ad free! To learn more about Ignition, please see the below links: What’s New in Ignition 8.3 Download Ignition 8.3 Ignition User Manual 8.3 Documentation Learn Ignition and earn a free credential   Schedule an Ignition demo Travis’ first appearance back in episode TAP 124 Read the transcript on The Automation Blog: (automatically generated) Shawn Tierney (Host): coming later Vendors: Would you like your product featured on the Podcast, Show or Blog? If you would, please contact me at: https://theautomationblog.com/contact Until next time, Peace ✌️ If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

#384 In this episode, Guy interviewed Rollin McCraty, one of HeartMath's founders. They delved into the concept of the energetic heart and its impact on our lives, emotions, and connections. They discussed how the heart's energy field affects and is affected by the global field environment, especially during events like the COVID-19 pandemic. Rollin explained the research behind HeartMath and its tools designed to help people tap into their heart's intuitive guidance. The conversation also focused on the importance of coherence and how individual energy fields can contribute to global consciousness. Rollin provided practical advice and resources for listeners interested in exploring HeartMath and its techniques for inner growth and emotional regulation. About Rollin: Rollin McCraty, Ph.D., director of research at the HeartMath Institute, is a professor at Florida Atlantic University. McCraty is a psychophysiologist whose interests include the physiology of emotion. One of his primary areas of focus is the mechanisms by which emotions influence cognitive processes, behavior, health and the global interconnectivity between people and Earth's energetic systems. He has been with HeartMath Institute since its founding in 1991 by Doc Childre. He has worked closely with Childre to develop HMI's research goals and has been instrumental in researching and developing the HeartMath System of tools and technology.  McCraty and the members of his research team have worked in joint partnership with research groups at Stanford University, Claremont Graduate University, Dalhousie University in Halifax, Nova Scotia, Prince Sultan Cardiac Center in Saudi Arabia and the University of Lithuania among many others.  He has been interviewed for many feature articles in publications that include Prevention, Natural Health, Men's Fitness and American Health magazines, and has appeared in television segments for CNN Headline News, ABC World News Tonight, ABC's Good Morning America, NBC's Today Show, PBS's Body & Soul and the Discovery Channel. He has been featured in many documentary films, including I Am, The Truth, The Joy of Sox, The Power of the Heart, Solar Revolution, and The Living Matrix among others. Key Points Discussed:  (00:00) - When Billions Felt Fear — The Earth Responded. Proof we can take our power back! (00:54) - Welcome to the Let It In Podcast (03:40) - Meet Rollin McCraty: HeartMath Founder (11:45) - The Science Behind HeartMath (21:23) - HeartMath and Trauma Resolution (27:11) - Heart Coherence and Emotional Regulation (34:19) - Understanding Magnetic Fields and Their Properties (35:04) - The Heart's Magnetic Field and Its Measurement (36:04) - Emotional States and Their Vibrational Signatures (39:29) - Global Coherence and Human Interconnectivity (40:41) - Earth's Magnetic Fields and Human Resonance (44:52) - Schumann Resonances and Their Impact (50:51) - The Global Consciousness Project (59:39) - Practical Steps for Personal and Global Coherence How to Contact Rollin McCraty:www.heartmath.org   About me:My Instagram: www.instagram.com/guyhlawrence/?hl=en Guy's websites:www.guylawrence.com.au www.liveinflow.co

Get Automation World's insights on four key news items showcasing automation hardware and software successes: a game-changing industrial AI partnership led by Siemens, 177% throughput gains at Balluff using AutoStore's automated storage tech, a combination of Körber's MES and Pepperl+Fuchs' HMI tech for on-site and remote global pharma production oversight and compliance, and compelling survey data from Verizon showing IoT investments driven by measurable returns within months.

Shawn Tierney meets up with Mark Berger of Siemens to learn how Siemens integrates SIRIUS ACT devices (push buttons, selector switches, pilot lights) with PROFINET in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 253 Show Notes: Special thanks to Mark Berger of Siemens for coming on the show and sending us a sample! Read the transcript on The Automation Blog: (automatically generated) Shawn Tierney (Host): Thank you for tuning back in to the automation podcast. My name is Shawn Tierney from Insights. And today on the show, we have a special treat. We have Mark Berger back on from Siemens to bring us up to speed on serious act. He’s gonna tell us all about the product, and then we’re even gonna do a small demo and take a look at it working live. So with that said, let’s go ahead and jump into this episode with Mark Burger from Siemens and learn all about their push buttons on PROFINET. Mark, it’s been a while since you’ve been on the show. Thank you for coming back on and agreeing to talk about this. Mark Berger (Siemens): Oh, thank you so much. I truly appreciate you letting me be on. I appreciate your channel, and I enjoy watching it. And I’m excited to show you some of this great technology. So I’ve got, the PowerPoint up here. We’ll just do a simple PowerPoint to kinda give you an overview, and then we’ll dive into the hardware. Shawn Tierney (Host): Appreciate it. Thank you. Mark Berger (Siemens): No problem. So as we stated, the Sirius X over PROFINET, let me emphasize that, the, actuators, the push buttons, the estops, the selector switches, they are all standard, when you use these. So if you have those on the shelf, the only thing that PROFINET does is that it adds, removes the normal contact blocks and adds the PROFINET, terminal blocks on the back. So every all the actuators that we’re showing are just standard actuators for the 22 millimeter push button line. So easy to use, modern design, performance and action, and extremely rugged and flexible. The, 22 millimeter is out of the box IP 69 k, which for those who are maybe in the food and beverage, verticals would understand what that is. And that’s for direct hose down, wash down, able to handle a high pressure washing and not able to leak past the actuator into the panel. So IP 69 k is a a great place for dust and wash down and hosing and where you’re having rain and so forth, to be able to protect for a keep of any, water passing into the panel. So introduction wise, it’s, the PROFINET push buttons for us. It it is, again, the same actuators, the same, connections, and so forth, but what we’re going to exchange is the terminal blocks, for it. So on there, I stated it’s, IP 69 k is standard. You don’t need any, extra covers forward or anything to fulfill that requirement, But it’s, it’s insensitive to dust and oil and caustic solutions, you know, like citric acid where you’re hosing down some stainless steel parts and so forth. Now what we have here is, changing out the terminal blocks that have wiring. So usually on a push button, you have two wires coming in, and then you have, for illuminated, you have two wires coming in and so forth and going out. And after you have 20 or 30 push buttons or 10 or 15 push buttons, you’ve got a substantial little bit of wiring or cabling that will be passing from the door over into the main cabinet of your control cabinet. What we’re going to do with PROFINET push buttons is we’re going to eliminate all that wiring. And then in addition, eliminate the input and output cards that you will need for your PLC and take it down to a pro, Ethernet cable, an r j r j 45 cable, and then down to a 24 volts. And that’s all that will pass from the cabinet onto the door where you’re mounting your push buttons. So, huge, safe and cost of wires. We’re reducing all the wire outlay. And, you know, back in the day when I build panels, it was an art how you got all the wires all nice and pretty and got them laid out and wire tied them down and so forth and just made the a piece of art on the backside. And then, it it was all done. You got it all wired. And then, of course, there was somebody that said, hey. We forgot to add another selector switch. So you had to go back and cut all that stuff and redo the whole layout and so forth. So with PROFINET, it’s extremely flexible and easily, to adapt to if you need something, more because you’re not taking all that wiring back to the panel, passing it across the hinge of the door and so forth. It is also with a safety PLC. You do have PROFIsafe, so we can do estops on the door as you can see here in the picture, but then we can do non safe applications also. So today, we’ll be just doing some non safe applications. And then the communications again is PROFINET. But then also just to touch real quick, we do have it on IO Link and on Aussie with our push buttons. So what is SiriusACT with PROFINET? There we go. So what you have is the first, block or interface module that you put on the back of your push button, that’s where the, Ethernet is plugged into and your 24 volts is plugged into. And then after that, subsequently, then the push buttons that you have is that you have what we call a terminal module. And in between the, the interface module to a terminal module or from terminal module to terminal module, you can go up to one meter of cabling, and it’s a ribbon cable. And we’ll show that here shortly. And then if you have up to we can do up to 20 push buttons, terminal modules, with a total of 21 push buttons. And then so from the first interface module all the way to the last push button, you can go up to 10 meters. And then it gives, again, 24 volt power supply for it. And we have, again, as I stated, as nonsafe, talking just PROFINET, and then the safety version, talking PROFISAFE on PROFINET. So serious act, we can go up on the the safety up to seal three and performance level e as an echo. We have, again, the the standard interface module without safety. You have the PLC, the interface module, and then the subsequent terminal modules for it. And then the cabling that goes from the interface module to out to the terminal modules is a simple ribbon cable that comes into the back of the terminal modules. The only tool that you need is simply it’s just a screwdriver, and, you, push it into the terminal module, push down. It uses, vampire connections, insulation displacement, vampire connections, and you push it down in. There’s no stripping of the wires. There’s no mix up. The indicator you can see on the wires here in a minute will show you that there’s a little red line that shows you, which way it, enters into the terminal, and then that’s it. It’s very straightforward. It’s, very simple with tools. And, as I stated, it’s, just like a normal push button that you’d put on, but then we’re gonna add, remove the contact block and add the terminal module or the interface module in the place of the contact block. Just to emphasize again, we can do PROFISAFE on, with a safety PLC and a safety controller, and we can give you all the safety, requirements for the either the ISO or the IEC specifications for safety out there in the field. Here’s some of the part numbers. First one, of course, is the interface module, and that has the ability to do PROFIsafe. It has also, additionally, four digital inputs, one digital output, and then one analog input. And we’ll talk about that a little bit more just in a few minutes. And then the non safe version, 24 volts. You have a, two versions of this one, one with just with just a standard, 24 volts input, but then there’s an additional one that has the four digital in, one digital out, and one analog in. So there’s two different part numbers. One where you don’t need the additional, digital inputs and outputs and analog, and then the and then the part number with the the additional inputs and outputs. But the safety one comes there’s no other version, just the one. Then you have what we call the terminal modules, and there’s three versions. One terminal module is just the command module only. It’s mounted with two mechanical signaling blocks to signal. So you have two contact blocks built in. Then you have one that’s a terminal module with the command, the terminal blocks, and then also an integrated LED. And then you can put what color you want the LED to be, and you can see there the the part number changed for red, blue, amber, so on. And then you have a just an LED module to where it’s no contactors. It’s just LED. And, I think with our demo we’re gonna show today, we’re just gonna show the contact block and LED module and only the LED module today. There’s some other, accessories with the safety. There’s a memory module to where that you, is all the configurations are put into the memory module, and something happens to that interface module. Everything’s put in there, the IP address, the configuration, and everything. If something gets broke and so forth or you have to replace it, you pull the memory module out, put the new terminal or interface module in, plug in the memory module, cycle the power, and it’s up and running. All the configurations, the IP address, everything’s already there. And then on the interface module, it does not come with an LED, so you’re required to buy this this, LED right here if you need it for it, and that’s what you use for the interface module. And then, of course, the ribbon cable that goes between the interface module to the terminal block or terminal module and terminal module and so forth come in five meter length and 10 meter length. K. So what’s it provide for you? Well, the benefits are, I’ll I’ll be very blunt. If it’s just one or two buttons on a panel, it won’t be that cost effective. Yes. We’re reducing the IO, the IO inputs and outputs, but for the savings, it’s not the best. Now when you get up to about three or four push buttons, then that cost saving is, very realized. Now when you go up to 20 push buttons, yes, you’re saving a lot of money, especially in the IO cards that you’re not gonna be required to have. And then, of course, all the wiring and the labor, getting it all wired up and doing all the loop checks to make sure that when you push this button, it’s wired into the right terminal block on the IO card, so on and so forth. So about, the break is about two to three push buttons to where it will become very cost effective for you to use it. But like I said yesterday, without PROFINET push buttons, it was all the wiring you brought across and putting them into all your IO cards and so forth. And now with PROFINET push buttons, all that goes away, and all you’re bringing across is an Ethernet cable and 24 volts positive and 24 volts negative across that hinge into the door. And that’s it. K. And then emphasizing again, we can do PROFIsafe and those, push buttons and estops. The estop can be part of your safety circuit and give you the, safety levels that you’re required from either sill and or performance level safeties depending on the specification, IEC, or ISO that you’re following within your plant. K? And then hardware configuration. Now this is where we step into reduction of engineering and helping you guys get going, quicker and making sure engineering is done properly. You know, back in the day, we’d wire up all the wires, coming from the push buttons, you know, a selector switch, a start button, stop button, indicator lights, and so forth. And and all those wires sometimes just, you know, the what we’re working with, all the wires look the same. You’ve put labels on them. You may have labeled it wrong, and you wired into an input card or an output card. So there’s some time where you’re over there doing some loop checks where you’re trying to say, yes. That’s coming into input byte dot bit, and that should be the selector switch. Well, with the PROFINET push buttons, we’re able to not have to worry about that, and we’re gonna demonstrate that just here in a minute. But you also have a full lineup of the push buttons coming into portal so that you can see the lineup and verify that it is the parts that you want. In TI portal, you can see that, of course, the first, button is the interface module, and then sequentially is the terminal modules that have either just contactors, LED and contactors, or just LEDs. And we’ll we’ll show that just here momentarily. But it’s all integrated into TIA portal. It has a visual representation of all the push buttons, and it’s simple and fast, to, configure. We’ll show you that here in just a moment. And there’s no addressing, for it. So some of the stuff that you have out there, you have addressing, making sure what the address is right, and so on. This is a standardized data management, and it’s extremely time saving and engineering saving for, the user. Shawn Tierney (Host): Well, let me ask you a question about that. If the snow addressing, do the items show up, in the order that they’re wired? In other words, you know, you’re daisy chasing the you’re you’re going cable to cable from device to device. Is that the order that they show up? Mark Berger (Siemens): That’s exactly right. Shawn Tierney (Host): Okay. Mark Berger (Siemens): So if you don’t know which ones are what, you just literally put run your hand from the interface module, follow that cable, and the next one that will be visually saw in portal will be the one that it lands on first. Perfect. And then there’s a cable that leaves that one and goes into the next one, daisy chained, and then that’s what’ll be represented in that lineup. And here in just a minute, we’ll we’ll show that. Alright. Thank you for that question. Okay. Now once I got it wired up, how do I know that I got it wired properly? And we’re gonna show that here in just a minute. But just graphically wise, you have the ability to see if it is all wired up. You do not need to plug it into the PLC. This all it needs is 24 volts. The PLC can come later and plugging it in later and so forth. There’s no programming. This all comes out of the box. So once you plug it in, if all on the backside looking at the terminal blocks and the daisy chain ribbon cable, if it’s all green, you wired it up properly, and it’s working properly. But then if you see a red light flashing either at the terminal module because that will that will bubble up to the terminal module. So if you have a problem somewhere pardon me, the interface module. If you have some problem with the terminal modules, a push button like number two or three or four, it will bubble up into the, interface module to let it know, hey. We got a problem. Can you look to see where it’s at? And as you see here, we have maybe a device that’s defective. And so it bubbles up into the interface module to let you know, and a red light lets you know that we have maybe a defective module. You know, something hammered it pretty hard, or, it may have been miswired. Then the second one down below, we’ve got a wiring error to where you don’t have the green lights on the back and everybody else’s there’s no green light shown. That means you have a wiring error. Or if everything works great, it’s green lights across, but then the next level of this is is my push button working? So then we you’ll push or actuate the push button or actuate the selector switch, and the green light will flash to let you know that that terminal module or interface module is working properly. And we’ve done our our, loop checks right there before we’ve even plugged it into the PLC or your programmer has come out and sat down and worked with it. We can prove that that panel is ready to roll and ready to go, and you can set it aside. And if you got four or five of the same panel, you can build them all up, power it up, verify that it’s all green lights across the board. It is. Great. Set it down. Build up another one and go on from there. So it shows you fast fault detection without any additional equipment or additional people to come in and help you show you that. When we used to do loop checks, usually had somebody push the button, then yell at the programmer, hey. Is this coming in at I zero dot zero? Yeah. I see it. Okay. Or then he pushed another one. Hey. Is this coming in on I 0.one? No. It’s coming in on i0. Three. So there was that two people and then more time to do that loop check or the ring out as some people have called it. So in this case, you don’t need to do that, and you’ll see why here in just a minute. And then, again, if we do have an interface module that, maybe it got short circuited or something hit it, it you just pull the ePROM out, plug it into the new one, bring in the ribbon cable, and cycle the power, and you’re up and running. Alright. And then this is just some of the handling options of how it handles the data, with the projects and so forth, with basic setups, options that you can be handling with this, filling bottles. What we wanna make sure to understand is that if maybe push buttons, you can pick push buttons to work with whatever project you want it to do. So if you have six push buttons out there, two of them are working on one, bottle filling, and then the rest of them are working on the labeling, you can separate those push buttons. Even though that they’re all tied together via PROFINET, you can use them in different applications across your machine. Shawn Tierney (Host): You’re saying if I have multiple CPUs, I could have some buttons in light work with CPU one, PLC one, and some work with PLC two? Mark Berger (Siemens): Yep. There’s handling there. There’s programming in the backside that needs to be done, but, yes, that can happen. Yep. Oh, alright. So conclusion, integrated into TI portal. We’re gonna show that here in a minute. So universal system, high flexibility with your digital in, digital outs, analogs, quick and easy installation, one man, one hand, no special tooling, and then substantially reducing the wiring and labor to get it going. And then, again, integrated safety if, required for the your time. So with that, let’s, switch over to TI portal. So I’ve already got a project started. I just called it project three. I’ve already got a PLC. I’ve got our, new g, s seven twelve hundred g two already in. And then what I’m gonna do is I’ve, already built up the panel. And, Shawn, if you wanna show your panel right here. Shawn Tierney (Host): Yeah. Let me go ahead and switch the camera over to mine. And so now everybody’s seeing my overhead. Now do you want me to turn it on at this point? It’s off. Yeah. Yeah. Mark Berger (Siemens): Let’s do it. Shawn Tierney (Host): Gonna turn it on, and all the lights came on. So we have some push buttons and pilot lights here, but the push buttons are illuminated, and now they’ve all gone off. Do you want me to show the back now? Mark Berger (Siemens): Yep. So what we did there is that we just showed that the LEDs are all working, and that’s at the initial powering up of the 24 volts. Now we’re gonna switch over and, you know, open up the cabinet and look inside, and now we’re looking on the backside. And if you remember in the PowerPoint, I said that we’d have all green lights, the everything’s wired properly. And as you look, all the terminal modules all have green lights, and so that means that’s all been wired properly. If you notice, you see a little red stripe on the ribbon cable. That’s a indication. Yep. To show you that. And then if you look on the on the out on the, the interface module, Shawn, there’s it says out right there at the bottom. Yeah. There’s a little dot, and that dot means that’s where the red stripe goes, coming out. So that little dot means that’s where the red stripe comes. Yep. Right there. And that’s how it comes out. And then if you look just to the left a little bit, there’s another, in, and there’d be a red dot underneath that ribbon cable showing you how the red the the red goes into it. Notice that everything’s clear, so you can see that the wire gets engaged properly all the way in. And then all you do is take a screwdriver and push down, and then the vent, comes in. The insulation displacement comes in and, and, makes the connections for you. So there’s no strip tie cable stripping tools or anything special for doing that. Another item, just while we’re looking, if you look in the bottom left hand corner of that terminal module, you see kind of a a t and then a circle and then another t. That’s an indicator to let you know that that’s two contactors and an LED that you have on the backside. Shawn Tierney (Host): We’re talking about right here? Mark Berger (Siemens): Yep. Yep. Right there. Shawn Tierney (Host): Okay. Mark Berger (Siemens): So that’s an indicator to tell you what type of terminal block it is a terminal, block that it is. That’s two contactors and LED. And then if you look at one in the bottom left hand corner, there’s just a circle. That means you just have an LED. So you have some indicators to show you what you’re looking at and so forth. So today, we’re just using the two, LED only, and then we’re doing the contactor and LED combination. I I don’t have one there on your demo that’s just the contactor. So Shawn Tierney (Host): Now you were telling me about these earlier. Yeah. Mark Berger (Siemens): So yeah. The so if you look there on that second row of the terminal blocks, you have a UV and an AI, and I’ll show that in the schematic here in just a little bit, but there, that is a 10 volt output. If you put a 250 ohm or 250 k ohm, potentiometer and then bring that signal back into AI, you have an analog set point that comes in for it that will automatically be scaled zero to 1,000 count or zero to 10 volts. Mhmm. And then you can use that for a speed reference for a VFD. And it’s already there. All you have to do, you don’t have to scale it or anything. You can put it towards, you know, okay. Zero to 1,000 count means zero to 500 PSI or or zero to 100 feet per second on a conveyor belt, and I’m I’m just pulling numbers out. But that’s the only real scalability scaling you have to do. So it’ll be a zero to 1,000 count is what you’ll see instead of, like, yep. Then you got four digital ins that you can use and then a one digital out. Now the four, I, kinda inquired wife just four, but let’s say that you have a four position joystick. You could wire all four positions into that interface module, and then the output could be something else for a local horn that you want or something to that case with it. So you in addition to the, push buttons, you also have a small, distribution IO block right there in the in your panel. Shawn Tierney (Host): Which is cool. Yeah. I mean, maybe yeah. Like you said, maybe you have something else on the panel that doesn’t fit in with, you know, this line of push buttons and pilot lights like a joystick. Right? And that makes a lot of sense. You were saying too, if I push the button, I can test to see if it’s working. Mark Berger (Siemens): Correct. So if you yep. Go right ahead. Shawn Tierney (Host): I’m pushing that middle one right there. You can see it blinking now. Mark Berger (Siemens): And that tells you that the contacts have been made, and it’s telling you that the contacts work properly. Shawn Tierney (Host): And now I’m pushing the one below it. So that shows me that everything’s working. The contacts are working, and we’re good to go. Mark Berger (Siemens): Yep. Everything’s done. We’ve done the loop checks. We know that this is ready to be plugged into the PLC and handed off to whomever is going to be, programming the PLC and bring it in, in which means that we’ll go to the next step in the TI portal. Shawn Tierney (Host): Yeah. Let me switch back to you, and we’re seeing your TI portal now. Mark Berger (Siemens): Awesome. Okay. So I’ve got the PLC. I’ve plugged it in to if if I needed an Ethernet switch or I’ve plugged it directly into the PLC. Now I have just built up that panel. I haven’t had anything, done with it for an IP address because it is a TCP IP protocol. So we need to do a IP address, but it’s on PROFINET. And then I’m gonna come here to online access, and I wanna see that I can see it out there that I’m talking to it. So I’m gonna do update accessible devices. It’s gonna reach out via my, Ethernet port on my laptop. And then there’s our g two PLC and its IP address. So that’s that guy right here. Mhmm. And then I have something out there called accessible devices, and then this is its MAC address. So what I and I just have those two items on the network, but, you know, you could have multiples as, you know, with GI portal. We can put an entire machine in one project. So I come here and drop that down, and I go to online diagnostics. I I go online with it, but I don’t have really a lot here to tell me what’s going on or anything yet. But I come here, and I say assign IP address. And I call one ninety two, one sixty eight, zero zero zero, and zero ten zero, and then our usual 255, two fifty five, two fifty five, and then I say assign IP address. Give it a second. It’s gonna go out and tell it, okay. You’re it. Now I wanna see if it took, and you look right there, it took. And I’m I’m kinda anal, so I kinda do it again just to verify. Yep. Everything’s done. It’s got an IP address. Now I’m gonna come up, and I’m going to go to my project, and I’m gonna switch this to new network view. Here’s my PLC. I’m gonna highlight my project. Now there’s two ways I can go about it, and I’m sure, Shawn, you’ve learned that Siemens allows you to kinda do it multiple ways. I could come in here and go into my field devices, and I could come into my commanding and interface modules, and I’d start building my push button station. But we’re gonna be a little oh and ah today. We’re gonna highlight the project. I’m gonna go to online, and I’m gonna come down here to hardware detection and do PROFINET devices from network. Brings up the screen to say, hey. I want you to go out and search for PROFINET industrial Ethernet. Come out via my, NIC card from my laptop, and I want you to start search. Shawn Tierney (Host): For those of you who watched my previous episodes doing the e t 200 I o, this is exactly the same process we used for that. Mark Berger (Siemens): Yep. And I found something out there that I know I gave the IP address, but it doesn’t have a PROFINET name yet. So that’s okay. I’ve I got the IP address. We’ll worry about the PROFINET name. So we’ll hide check mark this, and this could be multiple items. Shawn Tierney (Host): Mhmm. Mark Berger (Siemens): K. So now add device. Shawn Tierney (Host): And this is the sweet part. Mark Berger (Siemens): And right here, it’s done. It went out, interrogated the interface module, and said, okay. Are you there? Yep. I’m here. Here’s my IP address. And it also shared with it all of come in here, double click on it now. Shawn Tierney (Host): The real time saver. Yep. Mark Berger (Siemens): Yep. And then now here’s all the push buttons in your thing. And let me zoom that out. It’s at 200%. Let’s go out to a 100. And now it already interrogated the interface module and all the terminal modules to tell me what’s in my demo. Yep. And again, as you stated in your questions, how do I know which one’s the next one? You just saw the ribbon cable Mhmm. And then it brings you so forth and so on. So that’s done. We’re good. I’m gonna go back to my network view, and I’m gonna say, hey. I want you to communicate via PROFINET to there, which I’m done. And then it also gives you here’s the PLC that you’re gonna do because, you know, if we have a big project, we may have four or five of these stations, and you wanna know which PLC is the primary PLC on it. And then we’ve done that. I’m going to quickly just do a quick compile. And next, I’m gonna come here. I’m gonna click here. Now I could just do download and and let the PROFINET name, which is here, go into it. But I’m gonna right click, and I’m gonna say assign device name and say update list. It’s gonna go interrogate the network. Takes a second. No device name assigned. No PROFINET name. So this is how we do that time determinism with PROFINET. So I’m gonna highlight it, and I say assign the name, and it’s done. Close. So now it has a PROFINET name and IP address. So now I’m able to go in here and hit download and load. And we’re going to stop because we are adding hardware, so we are putting the CPU in stop and hit finish. Now I always make sure I’m starting the CPU back up and then hit finish. And then I’m gonna go online, go over here and show network view, and go online. And I got green balls and green check marks all over the board, so I’m excited. This works out. Everything’s done. But now what about the IO? So now your programmer is already talking to it, but now I need to know what the inputs and outputs are. So go back offline, double click here, and then I’m gonna just quickly look at a couple things. The interface modules IO tags are in a different spot than the terminal modules. So just a little note. It’s right here. If you double click on integrated I LED, you click here and then go to properties and say IO tags. There it lists all of the inputs and outputs. So it comes here. But if I do a terminal module, click here, then once you just click on it in general oops. Sorry. In general, it’s right here in the IO addressing. There’s where it starts start the bytes, but then I come here to tags, and then here’s the listing. So the the the programs automatically already allocated the byte and the bit for each of these guys. So if I click there, there, click there, there’s it there, onward and upward. Now notice that the byte so if I click on position four, it is three. So it’s one one less because the base zero versus here, it’s five. Just give me a little bit of a so if you look in here, all that starts at I four dot zero. I four dot zero. So k. So that’s there. So I’m gonna come here. I’m gonna go to the selector switch for this, and I’ve called it s s one, and that’s input two dot zero. Then I’m gonna click here, and I’m gonna call this green push button. Notice there’s two inputs because I have one contactor here, one contactor there, and 30 and 31. So then what I’m gonna do is that I’m going to go over here to the PLC, and I’m gonna go to and it’s updated my PLC tag table. There you go. It’s in there. So then I’m gonna grab that guy. I’m gonna because portal pushes you to use two monitors. I’m gonna come here, go to the main OB, and then I’m gonna just grab a normally open contact, drag it on, drop it, put it in there we go. And then I’m gonna grab selector switch and drop that right there, and grab green LED and drop that right there, and then close that out and compile. And everybody’s happy. I’m gonna download and say yes. Okay. And then I’m gonna go online. Alright. So it’s waiting in for me to switch that, and there you go. And if you wanna see my screen there, Shawn, that’s the green light is turned on. Shawn Tierney (Host): Yeah. Let me switch over to Okay. Bring up your, alright. And could you switch it back off now? Mark Berger (Siemens): Yeah. No problem. Yep. So there we go. We switch it off. We switch it on. Now I wanna show you something kinda cool. If I turn that off and I come back here and I go offline Mhmm. I have a indicator light that needs to flash to let the operator know that there’s something here I need you to attend to. So we used to put in some type of timer. Right? Mhmm. Shawn Tierney (Host): Mhmm. Mark Berger (Siemens): And so what we would do here instead of that, I’m gonna come back down here to my tab and go to the hardware config. I’m gonna double click here. I’m gonna go to module parameters, and I’m gonna drop this down, and I’m gonna put it at two hertz. Also, just to point out, I can also do a normally open contact and a normally closed contact and switch them. You see right here. Cool. And I can control the brightness of the LED if it has an LED, and it’s all hard coded into it. So once I’ve done that, do a quick compile. I’m I mean, you know, I’ve always compile and then do download. Mhmm. Mhmm. So we’re gonna download that and hit load and finish. K. Here we go. Turn that on, and now it’s flashing. Shawn Tierney (Host): That’s great. So you have a timer built in. If you need to flash, you don’t have to go get a clock bit or create your own timer. Plus, if it’s a button, you can change the contacts from normally open to normally closed. That is very cool. Mark Berger (Siemens): Yep. And that is PROFINET push buttons. As I stated let me quickly pull that up. Remember, you pointed out just a few minutes ago, here is the wiring diagram for that. So here’s the back of that with the terminal blocks. And you come down here, and it shows you that you just wire in that, variable resistor or a potentiometer. And you see m and you there’s the 10 volts, and then the signal comes into a. And then that guy is right here. Excellent. So if you come here, you go to properties and IO tags, and it comes in on I 60 fours and input and IO tags, and then I could call that a pot. Yeah. And now you have a potentiometer that you can use as a a speed reference for your VFD. That is very cool. Engineering efficiency, we reduced wiring. We don’t have all the IO cards that is required, and we have the diagnostics. Emphasize that each of these here, their names, you can change those if you would like because this is your diagnostic string. So if something goes wrong here, then it would come up and say commanding. So you double click here, and we go here to general, and it’ll say commanding and underscore LED module two, or you can you can call that start conveyor p b. And then that would change this. Now see this changed it. This would be your diagnostic string to let you know if if that button got damaged or is not working properly. Shawn Tierney (Host): You know, I wanted to ask you too. If I had, let’s say I needed two potentiometers on the front of the enclosure, could I put another interface module in the system? Even if it didn’t have any push buttons on it or pilots on it, could I just put it in there to grab, some more IO? Mark Berger (Siemens): Yep. Yes, sir. I have a customer that he uses these as small little IO blocks. Shawn Tierney (Host): Yeah. I mean, if you just needed a second pot, it might make sense to buy another interface module and bring it into that than buying an analog card. Right? Assuming the resolution and everything was app you know, correct for your application, but that’s very cool. I you know, it it really goes in line with all the videos we’ve done recently looking at e t 200 I o, all the different flavors and types. And when you walk through here, you know, I’m just so especially, thankful that it reads in all the push buttons and their positions and pilot lights. Because if you have this on your desk, you’re doing your first project, you can save a lot of dragging and dropping and searching through the hardware catalog just by reading it in just like we can read in a rack of, like, e t 200 SPIO. Mark Berger (Siemens): Yep. Engineering efficiency, reducing wiring, reducing time in front of the PC to get things up and running. You saw how quickly just a simple push button and a and, you know, again, a simple start and turn that on and off the races we went. Shawn Tierney (Host): Well, Mark, I really wanna thank you. Was there anything else that we wanted to cover before we close out the show? Mark Berger (Siemens): Nope. That’s just about it. I think, we got a little bit to have your your viewers, think about for it. So I appreciate the time, and I really appreciate you allowing me to show this. I think this is a a really engineering efficiency way of going about using our push buttons and and, making everybody’s projects in a timely manner and getting everything done and having cost savings with it. Shawn Tierney (Host): Well, and I wanna thank you for taking the time out of your busy day, not only to put together a little demo like you have for me to use here in the school, but also to come on and show our audience how to use this. And I wanna thank our audience. This was actually prompted from one of you guys out there at calling in or writing in. I think it was on YouTube somewhere and saying, hey. Could you cover the PROFINET push buttons from Siemens? I didn’t even know they had them. So thanks to the viewers out there for your feedback that helps guide me on what you wanna see. And, Mark, this would not be possible if it wasn’t for your expertise. Thank you for coming back on the show. I really appreciate it. Mark Berger (Siemens): Thank you, Shawn. All the best. Thank you. Shawn Tierney (Host): I hope you enjoyed that episode. And I wanna thank Mark for taking time out of his busy schedule to put together that demo and presentation for us and really bring us up to speed on Sirius X. And I wanna thank the user out there who put a comment on one of my previous videos that said, hey. Did you know Siemens has this? Because I wouldn’t have known that unless you said that. So thank you to all you. I try to read the comments every day or at least every two days, and so I appreciate you all wherever you are, whether you’re on YouTube, the automation blog, Spotify, iTunes, Google Podcasts, and wherever you’re listening to this, I just wanna thank you for tuning in. And now with next week being Thanksgiving, we’ll have a pause in the automation show, then we have some more shows in December, and we’re already filming episodes for next year. So I’m looking forward to, releasing all those for you. And if you didn’t know, I also do another podcast called the History of Automation. Right now, it’s only available on video platforms, so YouTube, LinkedIn, and the automation blog. Hopefully, someday we’ll also do it on, audio as well. But, we’re meeting with some of the really legends in automation who worked on some of the really, you know, just really original PLCs, original HMIs, up and through, like, more modern day systems. So it’s just been a blast having these folks on to talk about the history of automation. And so if you need something to listen to during Thanksgiving week or maybe during the holidays, check out the history of automation. Again, right now, it’s only available on YouTube, the automation blog, and LinkedIn, but I think you guys will enjoy that. And I wanna wish you guys, since I won’t be back next week, a very happy Thanksgiving. I wanna thank you always for tuning in and listening, and I also wanna wish you all good health and happiness. And until next time, my friends, peace. Until next time, Peace ✌️  If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Shawn Tierney meets up with Henrik Pedersen and Jacob Abel to learn about OTee Virtual PLCs in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 252 Show Notes: Special thanks to Henrik Pedersen and Jacob Abel for coming on the show, and to OTee for sponsoring this episode so we could release it “ad free!” To learn about the topics discussed in this episode, checkout the below links: OTee Virtual PLCs website Schedule an OTee demo Connect with Henrik Pedersen Connect with Jacob Abel Read the transcript on The Automation Blog: (automatically generated) Shawn Tierney (Host): Thank you for tuning back into the automation podcast. Shawn Tierney here from Insights. And this week on the show, I meet up with Henrik Pedersen and Jacob Abel to learn all about virtual PLCs from OTee. That’s o t e e. And, I just thought it was very interesting. So if you guys have ever thought about maybe running virtual PLCs to test some processes out, I think you’ll really enjoy this. With that said, I wanna welcome to the show for the very first time, Hendrik and Jacob. Guys, before we jump into your presentation and learn more about what you do, could you first introduce yourself to our audience? Henrik Pedersen (OTee): Yeah. Sweetly. So my name is Hendrik. I am the cofounder, COO, OT, a new industrial automation company, that, we’re really glad to present here today. I have a background from ABB. I worked eleven years at ABB. In terms of education, I have an engineering degree and a master degree in industrial economics. And, yeah, I’m I’m excited to be here. Thanks, Rom. And I’ll pass it over to Jake. Jacob Abel (Edgenaut): I’m, Jacob Abel. I’m the principal automation engineer at Edgnot. EdgeNaught is a systems integrator focusing on edge computing and virtual PLCs. My background is in mechanical engineering, and I’m a professional control systems engineer, and I have thirteen years experience in the machine building side of industrial automation, specifically in oil and gas making flow separators. And I’ll hand it back to Henrik here. Henrik Pedersen (OTee): K. Great. So OT, we are a a new industrial automation company, the new kid on the block, if you will. We’re a start up. So, we only started, about three years ago now. And, we focus solely on virtual PLCs and and the data architectures allow you to integrate virtual PLCs in in operations. And, you know, some of the listeners will be very familiar with this first, thing I’m gonna say, but I think it’s valuable to just take a take a little bit step back and and remember what has happened in in history when when it comes to to IT and OT and, and and what really what really happened with that split. Right? So it was probably around the ‘9 you know, around nineteen nineties where the the the domain computer science were really split into these two domains here, the IT and OT. And, and that, that was, that was kind of natural that that happened because we got on the, on the IT side of things, we got Internet, we got open protocols and, you know, we had the personal computers and innovation could truly flourish on the IT side. But whereas on the OT side, we were we were kind of stuck still in the proprietary, hardware software lock in situation. And and that has that has really not been solved. Right? That that that is still kind of the the situation today. And it this is what this is obviously what also, brought me personally to to really got really super motivated to solve this problem and and really dive deep into it. And I experienced this firsthand with with my role in NAD and, how how extremely locked we are at creating new solutions and new innovation on the OT side. So so we’re basically a company that wants to to truly open up the the the innovation in this space and and make it possible to adopt anything new and new solutions, that that sits above the PLC and and, you know, that integrate effectively to to the controller. So I I have this this, you know, this slide that kind of illustrates this point with with some some, you know, historical events or or at least some some some big shifts that has happened. And, Aurene mentioned a shift in nineteen nineties. And it wasn’t actually until ’20, 2006 that Gartner coined this term OT, to explain the difference really what what has happened. And and, you know, as we know, IT has just boomed with innovation since since the nineties and OT is, is, is slowly, slowly incrementally getting better, but it’s still, it’s still the innovation pace is really not, not fast. So, this is also, of course, illustrated with all the new developments in in GenAI and AgenTic AI, MCP, and things like that that is kinda booming on on the IT side of things. And and and yeah. So, but we do believe that there is actually something happening right now. And and we have data that they’re gonna show for for that. Like, the the large incumbents are now working on this as well, like virtual PLCs, software defined automation and all kinds of exciting things going on on the OT side. So we do believe that that we will see, we will see a shift, a true big shift on the OT side in terms of innovation, really the speed in which we can, we can improve and adopt new solutions on the OT side. And this is kind of exemplified by, like, what what is the endgame here? Like, you could say that the endgame could be that IT and OT once once again becomes the same high paced innovation domain. Right. But then we need to solve those underlying problems, the infrastructural problems that are still so persistent on the OT side of things. The fine point of this slide is to just illustrate what’s happening right now. It’s like cloud solutions for control is actually happening. Virtual PLC, software based automation, AI is happening all at once. And we see it with the big suppliers and and also the exciting startups that’s coming into this space. So I think there’s there’s lots of great excitement now that we can we can expect from the OT side, in in next few years. Shawn Tierney (Host): Yeah. You know, I wanna just, just for those listening, add a little, context here. If we look at 1980, why was that so important? Why is this on the chart? And if you think about it, right, we got networks like Modbus and, Data Highway in nineteen seventy eight, seventy nine, eighty. We also got Ethernet at that time as well. And so we had on the plant floor field buses for our controls, but in the offices, people were going to Ethernet. And then when we started seeing the birth of the public Internet, right, we’re talking about in the nineties, people who are working on the plant floor, they were like, no. Don’t let the whole world access by plant floor network. And so I think that’s where we saw the initial the the divide, you know, was 1980. It was a physical divide, just physically different topologies. Right? Different needs. Right? And then and and as the Internet came out in the early nineties, it was it was now like, hey. We need to keep us safe. We know there’s something called hackers on the Internet. And and I think that’s why, as you’re saying in 2006, when Gartner, you know, coined OT, we were seeing that there was this hesitant to bring the two together because of the different viewpoints and the the different needs of both systems. So I think it’s very interesting. I know you listeners, you can’t see this, but I kinda want to go back through that and kinda give some context to those early years. And and, you know, like Henrik says, you know, now that we’re past all that, now that we’re using Ethernet on the plant floor everywhere, right, almost everywhere, on all new systems, definitely, that that becomes the right now on this on the today on the, on the chart. And I’ll turn it back to you, Henrik. Henrik Pedersen (OTee): Yeah. I’ll search that. I just wanna echo that as I think that there are really good reasons for why this has happened. Like, the there has you could argue that innovation could flourish on the IT side because there was less critical systems, right, less, more, you know, you can do to fail fast and you can do, you can test out things on a different level. And so so there’s really lots of good reasons for why this has happened. We do believe that right now there is some really excitement around innovation, the OT side of things and and this pent up kind of, I wouldn’t call it frustration, but this pent up potential, I think is the right word, is is can be kind of unleashed in our industry for for the next, next decade. So so we are like this is really one of the key motivators for me personally. It’s, like, I truly believe there’s something truly big going on right now. And and I I do I do encourage everyone, everyone listening, like, get in get in on this. Like, this is happening. And, you know, be an entrepreneur as well. Like, build your company, build and, you know, create something new and exciting in this space. I think I think this is this is a time that there hasn’t been a better time to create a new new technology company or a new service company in this space. So this this, this is something at least that motivates me personally a lot. So let me move over to kind of what we do. I mentioned I mentioned that we focus solely on the virtual PLC. This this is now presented in the slide for those that are listening as a as a box inside a open hardware. We can deploy a virtual PLC on any, ARM thirty two thirty two and and sixty four bit processor and x eighty six sixty four bit with the Linux kernel. So so there are lots of great, options to choose from on the hardware side. And and, and yeah. So you can obviously when you have a Virtual PLC you can think of it new in terms of your system architecture. You could for instance, you know deploy multiple Virtual PLCs on this on the same hardware and you can also, think about it like you can use a virtual PLC in combination with your existing PLCs and could work as a master PLC or some kind of optimization deterministic controller. So it’s it’s really just opening up that, you know, that architectural aspect of things. Like you can think new in terms of your system architecture, and you have a wide range of hardware to choose from. And, and yeah, So the the flexibility is really the key here, flexibility in how you architect your system. That CPU that you deploy on will will obviously be need to be connected to to the field somehow, and that’s that’s true, classical remote IO, connections. So we currently support, Modbus TCP and Ethernet IP, which is kind of deployed to to, our production environment, as it’s called. So moving on to the next slide. Like, this is kind of the summary of our solution. We have built a cloud native IDE. So meaning anyone can can basically go to our website and log in to into the solution and and give it a spin. And, we’ll show you that afterwards with with Jake. And the system interacts through a PubSub data framework. We use a specific technology called NUTS, for the PubSub communication bus. And you can add MQTT or OPC UA to the PubSub framework, according to your needs. So, and from that, you can integrate with, whatever whatever other, software you might have, in your system. So we have these value points that we always like to bring up. Like, this obviously breaks some kind of vendor lock in in terms of the hardware and the software. But it’s also, our virtual PLC is based on on the six eleven thirty one. So it’s not a lock in to any kind of proprietary programming language or anything like that. There is, there’s obviously the cost, element to this that you can potentially save a lot of cost. We have, we have verified with with with some of our customers that they estimate to save up to 60% in total cost of ownership. This is there is obviously one part is the capex side and the other part is is the opex. And and is this data framework, as I mentioned, is in in in which itself is is future proof to some extent. You can you can integrate whatever comes comes in in a year or or in a few years down the line. And, there’s environmental footprint argument for this as you can save a lot on the on the infrastructure side. We have one specific customer that estimates to save a lot on and this this particular point is really important for them. And then final two points is essentially that we have built in a zero trust based security, principle into this solution. So we have role based access control. Everything is encrypted end to end, automatic certification, and things like that. The final point is, is that this is the infrastructure that allows you to bring AI and the classical, DevOps, the the thing that we’re very used to in the IT side of things. Like, you you commit and merge and release, instead of, instead of the traditional, way of working with your automation systems. So I know this is like, this is pro pretty much, like, the boring, sales pitch slide, but, but, yeah, I just wanted to throw this this out there for for the guys that there is some there is some, intrinsic values underneath here. The way the system works, you will you will see this very soon, through the demo, but it’s basically you just go to a website, you log in, you create a project. In there, you would create your your PLC program, test, you code, you simulate. You would onboard a device. So onboard that Linux device that you you want to deploy on. This can be as simple as a Raspberry Pi, or it can be something much more industrial grade. This depends on on on the use case. And then you would deploy services like, as I mentioned, MQTT and OPC UA, and then you would manage your your your system from from the interface. And, I have this nice quote that we got to use from one of the customers we had. This is a global, automotive manufacturer that, basically tells us that it’s, they they highlighted the speed in which you can set this up, as as one of the biggest values for them, saving them a lot of hours and setting setting up the system. So I also wanted to show you a real you know, this is a actual real deployment. It was it was deployed about a year ago, and this is a pump station, or a water and wastewater operator with around 200 pump stations. They had a mix of of Rockwell and Schneider PLCs, and they had a very high upkeep, and they were losing a lot of data from these stations because they were connected over four g. When the Internet was a bit poor, they lost a bit of data in their SCADA systems, so they had these data gaps and things like that. So pretty pretty, you know, standard legacy setup to be to be honest. Quite outdated PLCs as well. So what they what they did for the first, pump station was they they, you know, removed the PLC. They put in a Raspberry Pi for for, like, €60 or, like, $70, connected it to to a to a remote IO Ethernet IP module they had, in in the storage, and deploy this data framework as I’m showing on the screen now. So so they that was that was the first station they put online, and they they chose a Raspberry Pi because they thought, okay, this is interesting, but will it work? And then they chose a pump station, which was was really just poor from before. So they had very little to to to lose to to deploy on this station. So so, yeah, this has been running for a year now without any any problems on a Raspberry Pi. We have obviously advised against using a Raspberry Pi in a critical environment, but they just insisted that that what that’s what they wanted to do for this first case. Shawn Tierney (Host): And I’ll back that up too. Your generic off the shelf Raspberry Pi is just like a generic off the shelf computer. It’s not rated for these type of environments. Not that all pump houses are really bad, but they’re not air conditioned. And I think we’ve all had that situation when it’s a 120, 130 out that, you know, off the shelf computer components can act wonky as well as when they get below freezing. So just wanted to chime in there and agree with you on that. For testing, it’s great. But if you’re gonna leave it in there, if you were in my town and you say you’re gonna leave that in there permanently, I would ask to have you, assigned somewhere else for the town. Henrik Pedersen (OTee): Yeah. Yeah. Exactly. No. So and and that point is also illustrated with the second station they brought online. So there they chose a much more industrial grade CPU, that, that, was much, you know, cost cost a bit more, but it’s more suited for the environment. And, and yeah. So this was, I can disclose it was a Bayer Electronics, CPU. So so yeah. And, and they reported, some good, good metrics in terms of, like, the results. They they said around 50 on the hardware, 75% on the management of the PLC system. So this relates more to that they have very a lot of, you know, driving out with the car to these stations and doing changes to their systems and, and updates. They no longer have any, any data loss. It’s local buffer on the data framework. They’ve increased tag capacity with 15 x, resulting in in four fifty five x better data resolution and a faster scan frequency. And this is actually on the Raspberry Pi. So so just just think of it as as the the even the even the, kind of the lowest quality IT off the shelf, computers, are are able to to, to execute really fast in in in, or fast enough for for, for these cases. So, Shawn, that was actually what I wanted to say. And, and also, you know, yeah, we are we are a start up, but we do have, fifth users now in 57 different countries across the world. And it’s it’s really cool to see our our our, our technology being deployed around the world. And, and yeah. I’m really, really excited to to, to get more, users in and and hear what they what they, think of the solution. So so yeah. I’ll I’ll with that, I don’t know if, Shawn, you wanna you shoot any questions or if we should hand it over to Jake for for for a demo. Shawn Tierney (Host): Yeah. Just before we go to Jake, if somebody who’s listening is interested, this might be a good time. It said that, you already talked about being cloud based. It’s, o t e e. So Oscar Tom, Edward Edward for the the name of the company. Where would they go if if they like what Jake’s gonna show us next? Where will they go to find out more? Henrik Pedersen (OTee): Yeah. So I would honestly propose that they just, reach out to to me or Jake, on on one of the QR codes that we have on the presentation. But they can also obviously go to our website, 0t.io,0tee.io, and just, either just, log in and test the product, or they could reach out to us, through our website, through the contact form. So yeah. Shawn Tierney (Host): Perfect. Perfect. Alright, Jake. I’ll turn it over to you. Jacob Abel (Edgenaut): Thanks, Shawn. Fantastic stuff, Henrik. I wanna take a second too to kinda emphasize some of the technical points that you, presented on. Now first, the the fact that you have the built in zero trust cybersecurity is so huge. So, I mean, the OT cybersecurity is blowing up right now. So many certifications, you know, lots of, consulting and buzz on LinkedIn. I mean, it’s a very real concern. It’s for a good reason. Right? But with this, zero trust built in to the system, I I mean, you can completely close-up the firewall except for one outgoing port. And you have all the virtual PLCs connected together and it’s all done. You know, there’s no incoming ports to open up on the firewall to worry about, you know, that security concern. You know, it’s basically like, you know, you’ve already set up a VPN server, if you will. It’s it’s not the same, but similar and, you know, taking care of that connection already. So there’s an immense value in that, I think. Shawn Tierney (Host): And I wanted to add to the zero trust. We’ve covered it on the show. And just for people, maybe you’ve missed it. You know, with zero trust is you’re not trusting anyone. You authorize connections. Okay? So by default, nobody’s laptop or cell phone or tablet can talk to anything. You authorize, hey. I want this SCADA system to talk to this PLC. I want this PLC to talk to this IO. I want this historian to talk to this PLC. Every connection has to be implicitly I’m sorry. Explicitly, enabled and trusted. And so by default, you know, an an integrator comes into the plant, he can’t do anything because in a zero trust system, somebody has to give him and his laptop access and access to specific things. Maybe he only gets access to the PLC, and that makes sense. Think about it. Who knows whether his laptop has been? I mean, we’ve heard about people plug in to the USB ports of the airport and getting viruses. So it’s important that person’s device or a SCADA system or a historian only has access to exactly what it needs access to. Just like you don’t let the secretary walk on the plant floor and start running the machine. Right? So it’s a it’s an important concept. We’ve covered it a lot. And and, Jake, I really appreciate you bringing that up because zero trust is so huge, and I think it’s huge for OT to have it built into their system. Henrik Pedersen (OTee): Yeah. Absolutely. Absolutely. Jacob Abel (Edgenaut): I wanted to highlight too the Henrik mentioned that the the backbone of the system is running on a technology called NATS. That’s spelled n a t s. And why that’s important is this is a a lightweight messaging, service, and it’s designed to send millions of messages per second. You know, that’s opposed to, you know, probably the best Modbus TCP device that you can find. You might get a couple 100 messages through per second. It’s millions of messages per second. It’s, you know, especially with, you know, we’re dealing with AI machine learning, you know, training models. I mean, we’re data hungry. Right? So this gives you the backbone too. You know, it’s like it can push an immense amount of tag data, you know, with ease. I think that’s another really important point. With that, though, I’ll I’ll get on to the demo. Henrik Pedersen (OTee): Oh, that’s great. We do we do see that, Jay, that most of our customers report on that, you know, 400 or 700 x better data resolution. And so it’s it’s a step change for for for the data resolution there. Yeah. Jacob Abel (Edgenaut): Excellent. So one of the things that I personally love about OT is how quickly you can get into the PLC once everything’s set up. So this is OT’s website, obviously, ot.io. So once you’re here, you just go to log in. And that brings in the login screen. Now I’m are I’m using my Google account for single sign on, so I can just click continue with Google. And this brings me into the main interface. And another thing that I love is that, you know, it is very simple and straightforward, you know, and simple is not a bad thing. Simple is a good thing. I mean, the way that things should be is that it should be, it should be easy and the finer details are taken care of for you. So right here, we have our main project list. I just have this one benchmarking program that I’ve imported in here. And you also have device lists, just a a test device that I’ve installed the runtime on. Just real quick. You know, you have a Martha, the AI assistant in the corner here. And, the documentation guides is up here. So you can get help or look into reference material very easily. It’s all right there for you. So I’m gonna open up this program here. So just a quick tour here. Right up here in the top left is basically where where most everything’s done. So if you click on this little down arrow, you can choose what virtual PLC runtime to attach it to. I’ve already attached it to the device. I installed the runtime on. You can add, you know, a new program, driver, function blocks, custom data types real quick here. Compile your program, download it to the device. Check the release history, which is really, really great. As you can, you can go into release history and you can revert to a prior version very easily. We got built in, version control, which is another, great feature. Henrik Pedersen (OTee): I can also just comment on that, Jake, that we do have we do have, in the quite short term roadmap to also expand on that with Git integration, that, a lot of our customers are are asking for. So yeah. Jacob Abel (Edgenaut): Awesome. Yeah. I mean, that’s that’s another, very hot topic right now. It’s, you know, getting getting the revision control systems, as part of, you know, at least the textual, programming languages. See, so, you know, we have a few, like, housekeeping things here. I mean, you can delete the program, export it. It’s a good good point here is that, OT complies with the PLC open, XML specification. So you can import or export programs, in this XML format, and it should work with solid majority of other automation software out there. You know, if you need to, you want to transition over to OT, you know, you can export it from your other software and import it rather easily. Got your program list here and, you know, just the basic configuration of, you know, you can add global variables that you wanna share between the different programs and POUs or, you know, change the, cycle rate of the periodic tasks, add more tasks. Let’s just get jump into this program here. Both the system uses the IEC sixty one one thirty one dash three standard structured text. So here’s just a little, quick benchmark program that I’ve been using to do some performance testing. Like you, you have the, the code right here, obviously. And on our, our right, the variable list, very easy to add a new variable and pick out the type. You can set a set of default value, add some notes to it. Super easy. So let’s go online. So if you have these little glasses up here in the top, right, you display live tag values. And so it’s grabbing from the runtime that’s running and plopping it right in here in the editor, which I I love the way it’s displayed. It makes it. And, you know, it’s one of the question marks is if you’re doing structured text instead of letter logic, like how it’s gonna show up and how readable is it gonna be. I think the, the text, like the color contrast here helps a lot. It’s very, very readable and intuitive. And we also have the tag browser on the right hand side. Everything is, organized into, you know, different groups. There’s the the resources and instances that you’ve set up in the configuration tab. So the by default, the tag the tags are all listed under there. And here too, you know, you can set tag values doing some performance testing, as I said. So this is, recording some some jitter and task time metrics. And that’s that’s really it. That’s the that’s the cloud IV in a nutshell. Super easy, very intuitive. I mean, it’s there there’s zero learning curve here. Shawn Tierney (Host): For the, audio audience, just a little comment here. First of all, structured text to me seems to be, like, the most compatible between all PLCs. So, you know, everybody does ladder a little bit differently. Everybody does function blocks a little bit differently. But structured text and, again, I could be wrong if you guys think out there in the in listening, think I’m wrong about that. But when I’ve seen structured text and compared it between multiple different vendors, it always seems to be the closest from vendor to vendor to vendor. So I can see this makes a great a great place to start for OT to have a virtual PLC that supports that because you’re gonna be able to import or export to your maybe your physical PLCs. The other thing is I wanted to comment on what we’re seeing here. So, many of you who are familiar with structured text, you know, you may have an if then else, or an if then. And and you may have, like, tag x, equals, you know, either some kind of calculation, you know, maybe, you know, z times y or just maybe a a constant. But what we’re seeing here is as we’re running, they have inserted at a in a different color the actual value of, let’s say, tag x. So in between you know, right next to tag x, we see the actual value changing and updating a few times a second. And so it makes it very easy to kinda monitor this thing while it’s running and see how everything’s working, and I know that’s that’s huge. And I know a lot of vendors also do this as well, but I love the integration here, how it’s so easy to see what the current values are for each of these variables. And, I’ll turn it over to you, Hendrick. I think I interrupted you. Go ahead. Henrik Pedersen (OTee): Yeah. No. I was just gonna comment on that. Jake said, like, this is the this is the POC editor, and the next the next big feature that we’re releasing very soon is essentially the service, manager, which is the, which is the feature that will allow our users to deploy any kind of service very efficiently, like another runtime or OPC UA server or an entity server or or or whatever other, software components that that, you want to deploy, like a Knox server or things like that. So and that’s that’s, we were really excited about that because, that will kind of allow for a step change in how you kind of orchestrate and manage your system and your, your system and your, your, you have a very good overview of what’s going on with versions of, of the different software components running in your, your infrastructure and your devices and things like that. So we’re really excited about that, that it’s coming out. And it might be that actually when when this, episode airs, who knows if it’s if it’s done or or not, but we’re very close to release the first version of that. So excited about that. Shawn Tierney (Host): Now I have a question for you guys, and maybe this is off topic a little bit. So let’s say I’m up here in the cloud. I’m working on a program, and I have some IO on my desk I wanna connect it to. Is that something I can do? Is there a connector I can download and install my PC to allow the cloud to talk to my IO? Or is that something where I have to get a a, you know, a local, you know, like we talked about those industrial Linux boxes and and test it here with that? Henrik Pedersen (OTee): Yeah. So I think you what you what you’re you’re after is, like, the IO configuration of, if you wanna deploy a driver, right, or, like, a modbus driver and how you figure out the system. Right? Shawn Tierney (Host): Yeah. Because this is in the cloud. It’s not on my desk. The IO is on my desk. So how would I connect the two of them? How would I is is that something that can be done? Henrik Pedersen (OTee): Yep. Yeah. Exactly. That’s that’s actually the you know, I I think, Jake, you might just wanna show why you deploy a driver. Right? Jacob Abel (Edgenaut): Sure. Sure. And I just wanna take a second to, clarify. You know, it’s something that kinda comes up often, and I I don’t I don’t think it gets it’s it’s cleared up enough is that so, you know, we have this cloud ID here. So, you know, you can open this from anywhere in the world. But the virtual PLC run times get installed on computers preferably very locally, you know, on the machine, on the factory floor, something like that. I I’ve got, an edge computer right here. Just as an example. I mean, this is something you would just pop in the control panel and you can install OT on this. So to answer your question better, Shawn, you know, to get to, you know, the remote IO that you need essentially, or actually in the, in the case of this, this has onboard IO. You know, you’re looking at connecting with MOBAs, PCP, Ethernet IP. I I know that a lot more protocols are coming. Profinet. So how you would do that is that you have that plus sign up here and add a driver config. We’re just gonna do, Modbus real quick. Henrik Pedersen (OTee): Mhmm. Jacob Abel (Edgenaut): And we wanna add a TCP client. So you can name the client, tell it how fast to pull, you know, any delays, put in the IP address. Just an example. Do the port number if you need and then add your requests. You know, you have support for, all the main function codes and mod bus right here, you know, read holding, read input, you know, write multiple coils, all that good stuff, you know, tell address how many registers you wanna do, timeouts, slave ID. And then, you know, once you’ve done that, so let’s say, you know, I’m gonna read, and holding registers here, the table on the right auto updates. You can do aliases for each one of these. You can just do register one Mhmm. As an example Shawn Tierney (Host): It’s showing just for the audio audience, it’s showing the absolute address for all these modbus, variables and then, has the symbols, and he’s putting in his own symbol name. It has a default symbol name of symbol dash something, and he’s putting his own in, like, register one, which makes it easier. Yeah. Jacob Abel (Edgenaut): Good point. Yeah. Good point. Thanks, Shawn. So, yeah, once once you put in your request and you can throw in some aliases, for the different registers, you know, you can go back to your program and here’s this, sample variable that I just added from earlier. You know, you can the registers are 16 bits. I’m gonna select, an int. And what you can do here now is select those modbus requests that you just set up. So it automatically maps these to those variables for you. So that that way you don’t have to do anything anything manual, like have a separate program to say, you know, this tag equals, you know, register 40,001. You know, it’s already mapped for you. So that’s that’s essentially how you would connect to remote IO is, just add a client in the driver configs and, fill in all your info and be off and running. Shawn Tierney (Host): That’s excellent. I really liked how you were able to easily map the register to the modbus value you’re reading in or writing to to your, variable so you can use that in your program. That was very easy to do. Jacob Abel (Edgenaut): Oh, yeah. Yeah. It’s that it’s like I said, that’s one of the things that I love about this interface is that everything is just very straightforward. You know, it’s it’s super easy to just stumble upon whatever it is you need and figure it out. Henrik Pedersen (OTee): And just just, to add to to kinda your your processors, like, once you have created that connection between the IO and and and the program, you basically just, compile it and download it to the to the runtime again, and and it executes locally the based on the yeah. Nice. Jacob Abel (Edgenaut): Oh, right. Good point. Yeah. Of of course, after we add something, we do have to redownload. So Shawn Tierney (Host): Very interesting. Well, that answers my question. Jacob Abel (Edgenaut): I think that’s that’s about it for the the demo. I mean, unless, Shawn, you have any more questions about the interface here. Shawn Tierney (Host): No. It looked pretty straightforward to me, Hendrik. I don’t know. Did you have anything else you wanted to discuss while we have the demo up? Henrik Pedersen (OTee): Nope. Not nothing related to this except for that, you know, this is probably something that’s quite new in the OT space is that this is a software service, meaning that there are continuous development going on and releases, and improvements to the software all the time. Like literally every week we deploy new improvements. And, and what, I typically say is that like, the, you know, if you if you if you sign up with OT, what you what you will experience is that the actual software keeps on becoming better over time and not is not going to become outdated. It’s going to be just better over time. And I think that’s part of what I really loved about the innovation space, innovation happening around IT is that that, that has become the new de facto standard in how you develop software and great software. And I think we in, in, in the OT space, we need to adopt that same methodology of developing software, something that continuously becomes better over time. Shawn Tierney (Host): Yeah. And I would just say, you know, if you’re if you’re on the OT side of things, you wanna be in six eleven thirty one dash three languages, because these are things that your staff, you know, what you know, your electricians and technicians and even engineers, you know, should know, should be getting up to speed. I don’t know. We’re at the automation school. We’re teaching, structured text. And so, easier. I look at this, and I’m like, this is a lot easier than trying to learn c plus or or JavaScript. So in any case, I think, you know, if it’s an OT side real IO control, real control system or data collection, you know, you know, very important, you know, mission critical data collection, then, you know, I’d rather have this than somebody trying to write some custom code for me and, you know, use some kind of computer language who doesn’t understand, you know, the OT side of things. So, I could definitely see the advantage of your system, Henrik. Henrik Pedersen (OTee): Yep. I I I also wanted to say to that, Stike, the I I do not believe the EIC standards in general will disappear. They exist for a very good reason. Right. Exists to standardise to to ensure safety and determinists, determinism in this. So I don’t think they will disappear. But there are obviously advances now with AI and things like that that can can help us create these things much faster and much more efficient and things like that. So, so but, but the EIC standards, I think, will be there for a very long time. Obviously, the 06/4099 standard is is really exciting, and and we believe that that can be, yeah, that that can clearly be there, but it’s still a new EIC standard. So, Shawn Tierney (Host): it’s not think what we’re gonna see is we’re gonna see a lot more libraries fleshed out. There’ll be a lot less writing from scratch. We’ve interviewed on the History of Automation podcast. We’ve interviewed some big integrators, and they’re at a point now, you know, twenty, thirty years on that they have libraries for everything. And I think that’s where we’ll see, you know, much like the DCS, I think, vendors went two years ago. But I still think that the there’s a reason for these languages. There’s a reason to be able to edit things while they run. There’s a reason for different languages for different applications and different, people maintaining them. So I agree with you on that. I don’t I don’t think we’re we’re gonna see the end of these, these standard languages that have done us very well since the, you know, nineteen seventies. Jacob Abel (Edgenaut): I just wanna add a bit on there about, Shawn, you mentioned, you know, doing less code. I I did show earlier in the bottom right hand corner here, we have our our little AI assistant, Martha. I don’t believe the feature, it has been released yet. You know, Henrik, correct me if I’m wrong, but I know one of the things that’s coming is, AI code generation, you know, similar to that of cloud or chat GPT. So it’s going to, you know, you can open this guy up here. You know, right right now, I think it’s just for, help topics, but you’ll be able to talk to Martha and she’s gonna generate code for you in your program there all built in. Henrik Pedersen (OTee): Yeah. Yeah. That’s that’s coming really fast now. So, it’s it’s not been implemented yet, but it’s, it’s right around the corner. Shawn Tierney (Host): Yeah. And it’s it’s not gonna be able to it’s you’re not gonna be able to hook a camera up to it and, like, take pictures of your machine and say, okay. Write the control code for this. But, you know, if you had a, you know, process that had 12 steps in it, the AI could definitely help you generate that code and and other code. And we’ll have to have Henrik and Jake back on to talk about that when it comes out, but, you know, it’s gonna be able to save you, reduce the tedious part of the the coding. You know, if you need an array of so many tags and so many dimensions or, you know, the stuff that, you know, it would just be the typing intensive, it’s gonna be able to help you with that, and then you can actually put the context in there. Just like, you can pull up a template in Word for a letter, and then you can fill in the blanks. You know? And and, of course, AI is helping make that easier too. But, in any case, Henrik, maybe you can come back on when that feature launches. Henrik Pedersen (OTee): Yeah. Absolutely. And I’m also excited about just a simple a use case of of translating something. Right? Translating your existing let’s say if it’s a proprietary code or something like that, like, getting it getting it standardized and translating it to the ESE six eleven thirty one standard, for instance, or, so so the obviously AI is, like, perfect for this space. It’s there is no doubt, And and it’s, like, that’s also why I’m so excited about, like, what’s going on at the moment. It’s like there’s so much innovation potential, in the on the OT side now that, they are with all these new technologies. Shawn Tierney (Host): Yeah. Absolutely. Absolutely. Well, gentlemen, was there anything else you wanted to cover? Henrik Pedersen (OTee): I think just just one final thing from from me is, like, we thought a lot about it, like, before this this episode, and we thought, like, let’s offer let’s offer the listeners something something of of true value. So so we thought, the, you know, after this after this episode launched, we want to want to offer anyone out there that’s listening a free, completely hands on trial of our technology, in their in their in their environment or on their Raspberry Pi or whatever. So just just reach out to us if you wanna do that. And, and I yeah. We’ll get you set up for for for testing this, and it’s not gonna cost you anything. Shawn Tierney (Host): Well, that’s great. And, guys, if you’re listening, if you do take advantage of that free trial, please let me know what you thought about it. But, Henrik, thank you so much for, that offer to our listening audience. Guys, don’t be bashful. Reach out to him. Reach out to Jake. Jake, thank you for doing the demo as well. Really appreciate it. My pleasure. Any final words, Henrik, before we close out? Henrik Pedersen (OTee): No. It’s been great. Great, being here, Shawn, and thanks for for helping us. Shawn Tierney (Host): Well, I hope you enjoyed that episode. I wanna thank Hendrik and Jacob for coming on the show, telling us all about OT virtual PLCs, and then giving us a demo. I thought it was really cool. Now if any of you guys take them up on their free trial, please let me know what you think. I’d love to hear from you. And, with that, I do wanna thank OT for sponsoring this episode so we could release it completely ad free. And I also wanna thank you for tuning back in this week. We have another podcast coming out next week. It’ll be early because I will be traveling and doing an event with a vendor. And so expect that instead of coming out on Wednesday to come out on Monday if all goes as planned. And then we will be skipping the Thanksgiving, week, and then we’ll be back in the in the, in December, and then we have shows lined up for the new year already as well. So thank you for being a listener, a viewer, and, please, wherever you’re consuming the show, whether it’s on YouTube or on the automation blog or at iTunes or Spotify or Google Podcasts or anywhere, please give us a thumbs up and a like or a five star review because that really helps us expand our audience and find new vendors to come on the show. And with that, I’m gonna end by wishing you good health and happiness. And until next time, my friends, peace. Until next time, Peace ✌️  If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Shawn Tierney meets up with Ivan Spronk of Siemens to learn about the SINAMICS G220 Clean Power Drive in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 251 Show Notes: Special thanks to Ivan Spronk of Siemens for coming on the show, and to Siemens for sponsoring this episode so we could release it “ad free!” To learn about the topics discussed in this episode, checkout the below links: White Paper – Drives Harmonics – Siemens US SINAMICS G220 Website SINAMICS G220 Catalog Siemens Product Configurator (SPC) for quick part number selection and access to data sheets and CAD files Siemens energy savings calculator, SinaSave  Read the transcript on The Automation Blog: (automatically generated) Shawn Tierney (Host): Thank you for tuning back into the automation podcast. My name is Shawn Tierney from Insights and Automation. And this week, I meet up with Iren Sprock from Siemens to learn all about their g two twenty clean power drive. I also wanna thank Siemens for sponsoring this episode so I can bring it to you completely ad free. So with that said, I wanna welcome back to the show Ivan from Siemens to talk about VFDs. And, this is something we’ve been wanting to talk about for a while. But before you jump into your presentation, Ivan, could you introduce yourself to our audience for those who maybe didn’t catch your last appearance? Ivan Spronk (Siemens): Thanks a lot for just having me, back to the show here. I got a slide up here that introduces myself. I’m the product manager for the Synamix variable frequency drives for Siemens here in The US. So, yeah, happy to be back on your show. And what I would, like to talk to you about and discuss with you is our latest variable frequency drive. It’s the g two twenty and specifically the clean power drive. This is a best in class solution for a grid friendly power quality when using variable frequency drives. So Shawn, you audience may be wondering why we should discuss power grids and variable frequency drives, but I’ll just say if you’ve been around variable frequency drives or VFDs as I’ll refer to them, you’ve likely had conversations or heard something about VFDs creating or generating harmonics on the power grid. Shawn Tierney (Host): Oh, yeah. Yeah. Ivan Spronk (Siemens): Yeah. Or maybe you’ve, you know, someone in the audience has been involved in a situation where harmonic current and associated voltage distortion on your plants electrical grid were causing overheating on transformers and cabling or potentially causing circuit breakers to trip their fuses to open. Or maybe you’re just an engineer looking to select and specify a variable frequency drive and you may need to answer some questions about harmonics that typical VFDs generate. You can relate to any of those or if you’re just interested to know more about this topic, we’ll invite you to stay tuned here for the next thirty five to forty minutes for discussion on power quality and VFDs. So, Shawn, I’d like to just ask you, have you heard anything about the power grid lately? Shawn Tierney (Host): Well, yes. I’ve heard lots about the power grid. I know that this is more and more becoming a big issue because when you have a lot of VFDs producing all kinds of harmonics, that can cause lots of problems like the ones you just mentioned. But, also, the utilities are starting to to see this and saying, why are we putting up with this? So aside from the power grid needing to be hardened against all kinds of things, everything from EMTs to, you know, just, you know, Yahoo’s shooting transformers in the middle of nowhere. This has been a, I think, a big and growing issue. That’s why I’m glad that you’re on the talk about this because in the preshow, we just really I really got a sense of how important this was, you know, in 2025 and going into 2026. Ivan Spronk (Siemens): Lots of conversations about the grid and really how the grid electrical grid is being stretched. And with all of the, you know, data centers being built, you know, lots of conversations about how power is gonna be supplied with those. In other words, I think for maybe the first time in twenty five to thirty years, they’re anticipating our usage and power requirements going up. So that’s why I think all these utilities and plant operators are interested in the grid. So some reasons to discuss then the power grid and variable frequency drives is variable frequency drives very useful for motor control, but left unchecked, they can introduce several power quality issues. Harmonics, as you can see on the screen here, typical VFDs use rectifiers that generate nonlinear currents that also distort the voltage waveform and these harmonics can propagate through the electrical grid. And, you know, with that voltage waveform potentially affecting other equipment or you know at worst case other utility customers. These voltage fluctuations can lead to flicker in lighting and perhaps even take other sensitive devices offline. Typical VFDs some of them can negatively impact power factor. Again, something that’s of interest to utilities and plant operators. And just you know there could be some resonant frequencies set up that may interfere with other things. So those are all things that yeah, harmonics, and you know, the voltage fluctuation, things that are unfavorable I’ll say. And what I’d like to do here Shawn is just gonna introduce, you know, what I want to tell you is we have a very unique product here in the SINAMICS g two twenty clean power drive. Three advantages of this product we’ll wanna talk about here through through the course of this podcast. One is the clean power technology. So you can see total harmonic current distortion is well under the strictest harmonic standards there at less than 2%. It delivers near unity power factor under almost any load conditions. And I’ll just say, you know, there has been technologies out there that have been able to produce, you know, those two attributes of of, you know, low current harmonic distortion and near unity power factor. But what’s most unique about, this product we’re that we’re launching here is the compact space saving design, and it is the smallest low harmonics drive in the market. And also available, it’s all self contained, so there’s nothing extra to install. It’s all in one footprint. And I’ll give you an example here. This product is released up to a through 150 horsepower now. By the end of the year we’ll have it released up through 200 horsepower. So this is a relatively new product on the market. But that 200 horsepower drive imagine this Shawn less than three feet tall, less than 12 inches wide, and about 14 inches deep. That’s a 200 horsepower drive, that will guarantee these, things I’ve got got here with low distortion and near unity power factor. Shawn Tierney (Host): You know, that’s not something I would have thought of is that these clean drives are more clean power drives are typically larger than their standard cousins. And so the fact that you’ve been able to get these smaller and closer to the sizes of the standard drive is pretty impressive. Ivan Spronk (Siemens): You’re quite we we’d like to think so. Let’s dig into, you know, first of all, if, you know, I I said variable frequency drives or typical very free frequency drives can generate harmonics. So why why would people wanna use VFDs? Turns out variable frequency drives are really good at two things. One, saving energy, and two, improving processes. So just, you know, kind of as a reminder, why do people wanna use variable frequency drives? Just a reminder. Yeah. Half the world’s electricity is used by motors operating pumps and fans and compressors. And just as a reminder, Shawn, if you’ve got a 20 horsepower motor operating and I just use twelve hours a day, two sixty five days a year, I used average commercial power rate of 12¢ a kilowatt hour, that electric motor is gonna cost you running across the line around $5,500. If I operate that motor with a VFD and I’ve got opportunity to adjust the speed, you know, based on demand, electricity cost is half of it. So $2,500 And that even gets more grows your savings grow if I consider a 100 horsepower motor operating twelve hours a day, two fifty days a year, again, with that same kilowatt hour. You know, that running that electric motor across the line is gonna cost you, you know, I’ve got on the screen here $28,000. I’ve got the opportunity to adjust speed and control speed as I do with the VFD, and the application can, of course, doesn’t have to be run at full speed. You know, just typical savings again is gonna it’s gonna cost you less than half to run that electric motor. So I like to put those numbers in front of people, Shawn, because I think people lose sight of how much it costs to run an electric motor. So any thoughts on that? Shawn Tierney (Host): Yeah. You know, when I first got in this industry back in ’90, this was big. This was talked about all the time. They were like, if you get a fan or pump and you don’t have a VFD on it, you’re just wasting money. And and and to some extent too soft status. But the point being that, you know, if the way you drove your car was you just put the pedal to the metal everywhere you went, you could just realize that’s not gonna be very efficient, you know, fuel wise. And so, you know, putting aside the process thing, because many processes, you can’t just do a cross line starter. Right? It would be great for the process, but, typically, fans and and pumps, I mean, the the amount of savings is tremendous. And I know for a very long time, this was, you know, it was up there with, lighting, up upgrading your lighting in your plant. You’re just installing VFDs or upgrading VFDs from very old VFDs. A lot of times, the cost savings and the rebates would make the the project pay for itself within a year or two, if not sooner. So it’s, for anybody listening, I know all the old timers out there are like, yeah, know all about this, but maybe he’s listening and you haven’t taken a look at that, definitely call your, local representative and ask him about energy savings with VFDs because it’s huge. I mean, it’s just massive. As you show in this slide, you know, but it’s it’s it’s just it’s it’s super. Now at your second point, processes, yeah, some processes I mean, they wouldn’t be possible if all you had was across the line. You know, we we think about, you know, needing a very precise control, very precise movement, maybe not servo control, but in some cases, you know, just, you know, starting the VFD across the line would, you know, would break things. Right? You need to coast up and coast down, and, you know, be able to vary the speed based on the but what part of the what product you’re making sometimes. But let me turn it back to you. Ivan Spronk (Siemens): Sure. So one of the links that I’ve got in my resources is a a a link to it’s called CNA Save. It’s just our Siemens name for our, energy savings calculator. So somebody, you know, with that link, somebody could go in there and very quickly, you know, put in their own horsepower and speed profiles and energy costs and see for themselves, you know, more dialed in. So yeah. And I liked your your conversation about the process. I mean, so I think what I’m trying to establish on this slide really is VFDs are very useful and very effective at helping manage costs and improve process. So, you know, VFDs are not going away. So now let’s then dive into figuring out, okay, how do we handle harmonics that typical drives generate. So first, Shawn, let’s start with a conversation about what are line harmonics, and I’ve just got a few slides here to talk about that. But we’ll relate it to, you know, what we call linear loads, which is like an induction motor or resistors or incandescent lamps. They draw sinusoidal or linear current proportional to voltage. So in other words, for the audience on the looking at this slide here you can see very nice looking sine waves. Yeah. In this country of course that’s coming from our power plants at 60 Hertz. Looks very nice, right? Well, when you put a nonlinear load on your electrical distribution center system, yeah, and nonlinear loads are any power electronic device that’s converting AC power to DC power. So that’s what we’re doing in a VFD, we’re converting AC power to DC power. But also computers, you know, that’s obviously not the same talking in the same magnitude of power, but this is what computers are doing. Same thing with LED lamps now, Discharge lighting. And very interestingly enough, this is also what’s going on in EV charging stations. You know, you’re converting AC power to DC power, so that’s considered a nonlinear load. And what happens there in a nonlinear load is it doesn’t draw, it just draws power in pulses when the capacitors need to charge. So think about these capacitors charging more at the top of the waveform, And that’s then what causes these variations in both voltage and current, from the fundamental sine wave. And you know, in very simple terms, that’s what these harmonics are. Yeah. They’re non sinusoidal, they’re nonlinear, and even since it’s changing with the applied voltage. So there’s some things that they, you know, negative impacts we’ll say. And again, for the audience that’s looking at the slide there, you can kind of see some of these nonlinear currents stacked up there. Point is it creates a much more complex waveform, and there’s current flowing at those multiple frequencies. So Shawn, I’ve got for for people that are maybe having a hard time visualing this up, I’ve got a little example. So can you think, Shawn, of a musical group that sings in parts? Shawn Tierney (Host): Mhmm. Ivan Spronk (Siemens): Even if we can’t mention them on the air, you can we can all think of, you know, a group that’s in Yep. Yep. Yeah. Exactly. So here we go. We’ve got a musical group singing in different parts, and these different musical parts are sung at different pitches or frequencies. And that all blends together to make a richer sound. Right? Well, we can think of that fuller sound that’s flowing at those frequencies. That’s kinda like more current flowing in there. So, you know, to back to our harmonics example. So, yeah, there’s world flowing at these other frequencies other than 60 Hertz, and that kind of fundamentally becomes a problem we need to deal with. And then in that in that group, Shawn, can you think of someone what does it sound like when they sing off key? Shawn Tierney (Host): Absolutely. Who doesn’t sound good. Ivan Spronk (Siemens): Does it so maybe we’ll think of that as voltage distortion. So we gotta gotta do something about that too. So Shawn Tierney (Host): Yeah. I’d like to you know what? For me, you know, to and I think the charts for those listening, I think the charts really spell it out. They’re color coded, and they show the different harmonics. And for me, I think charting it is kinda one of the ways to understand it visually because if you think about let’s say you have a large rock, a medium rock, and a small rock, and you throw all three at the same time into a pond. You can visually see the big ripple, the medium ripple, and the small ripple, but it’s really hard for you to understand as they’re spreading out what the effect would be on, you know, any any, you know, maybe toy boats that your kids have in the water or grandkids have in the water. Right? And so it it’s it’s a very tough for for human beings to try to keep in their head more than three things happening at a time. Right? And so and so I I love seeing the chart here, and it shows the relationship to when the capacity of charging and how that affects the primary and the sympathetic and the different waveforms. And I just know that these are, you know, inducing currents, And each one of these are inducing currents, but it’s like that throwing multiple rocks into into a body of water. I just can’t I, you know, I need to see it. I need to draw it out. I just can’t, you know, understand. Hey. Well, that me means this little boat’s gonna go to the Northwest because, you know, you know, and this is where I think it’s it’s easy to overlook the effects that these harmonics have because it is it does get kinda complicated to visualize. Ivan Spronk (Siemens): Yeah. No. I I like that analogy of, the rocks and the water too. You can see those wave forms and yeah. It becomes, you know, more current flow that has to be dealt with. And and the voltage notching is something again, talking about typical VFDs. I’ve got a little picture here of yeah, showing in the center of the screen there. Just main section of a typical VFD with the rectifier front end that’s a six pulse, standard six pulse rectifier in there that’s what you know is very very common. You can see the DC link capacitors in the middle there, and of course the inverter section on the output which is recreating that sine wave. But let’s turn our attention to you know the input waveform that we’re showing. You can see you know drawing power creating those that notched waveform. And really what I want to point out on this slide is okay that’s kind of at the top of the slide I’ve got a picture of OneDrive doing that that you know on any given distribution system there’s a variety of loads right? Each with its own signature that interacts with each other, So you end up in trying to show down in this down in the orange section here of this drawing. Okay all of these different loads combined with their own signature to create kind of a system signature if you will. And then what happens is, okay, you’ve got standards that we’ll talk about here a little bit, but standards and specifications, you know, you’ll see if you’re an engineer dealing with harmonics, you know, they often refer to this point of common coupling. So that’s kind of what I’m trying to come across on this slide here as well is when you have a system, you know, it’s very useful to identify this point of common coupling where you’re gonna measure, these harmonics. So you’ll see that in a lot of specifications. Not sure if you ever seen that, Shawn. Shawn Tierney (Host): No. And and and just the point of common coupling, when you’re saying that you’re referring to go ahead. Give me that again. What what does that actually mean? Ivan Spronk (Siemens): If you notice over on the right side here, we’ve got a different loads. I’m showing I’m showing a couple of different drives. I’m showing few motors operating across the line, each with their own signature, but that ends up creating, you know, on the distribution system, you know, a system signature. So we need some place, you know, to decide, you know, if you’re trying to meet a spec, well, tell me then where I have to measure it. So that becomes that’s what this point of common coupling is. And I just wanted to get that term out there because people have often heard of this. Sometimes it’s right at the we’ll say the you know connection to the Utility Transformer. If you’re a plant operator maybe you’ve got a handful of buildings over here and you want to define a point of common coupling between some of these other buildings. Mhmm. But it’s just a, yeah, place to define for a measurement. Shawn Tierney (Host): So in this case they have let’s say they have a transformer here. This transformer feeds two, let’s say, VFDs and then two motor starters. So they’re exactly at that point, you know, on the outfeed of the transformer, which we know we have four loads on, to be that point of common coupling. Because what’s gonna happen is we have all these different loads, so we have all these different waveforms. We have the different harmonics from the VFDs. So that’s gonna average together to give us a a waveform that’s the combination of those four devices, And that’s point of common coupling. Alright, I’m with you. Thank you. Ivan Spronk (Siemens): Exactly. Again, just one other factor, just to talk about a factor that impacts the magnitude of harmonics, is something else you’ll see in a lot of specifications is what’s called the relative short circuit ratio. And really this is just a metric that’s used when evaluating the grid’s ability to support variable frequency drives and and really any other nonlinear load, which, you know, we mentioned LED lighting and there’s other nonlinear loads out there too. But what it does is compares the strength of the grid or distribution system maybe that you have in your plant to the size of the connected load. And of course, this ratio and therefore the magnitude of the harmonics is impacted by transformer size, by what you all got connected if I’ve got other reactors, how much cable I’ve got connected. And then probably most importantly by load size and type. In other words, by load size I mean, okay is this 50 horsepower or 200 horsepower? And by type meaning, is this 300 horsepower running across the line or is it on a with a VFD? I like to give an example there, Shawn. Water treatment facilities often you hear a lot about harmonics in those facilities because often there’s such big motor loads being controlled by VFDs and that is by far the largest represents the largest percentage of load on that transformer. Right? So I’ve got to imagine kind of this remote water treatment facility, you know, what’s out there? Probably four to five to six depending on how big it is, you know, huge motors running pumps, right? And not much else. So there’s an example of people that would be you know very concerned about how much you know what percentage of nonlinear load do I have on my transformer? So that’s kind of all relates back to this short circuit ratio. Again, something you see in a lot of specs. So just trying to give some definition around what that is. Sure if you got anything, any questions or anything you wanted to add or? Shawn Tierney (Host): No. I I appreciate that. Appreciate you going over. Ivan Spronk (Siemens): No. Kind of a point I’m trying to make is, you know, there’s multiple factors that impact the magnitude and lots of things to think about and figure out. It’s like, wow. If you’re a plant engineer with responsibilities for a power grid, wouldn’t it be great not to have to think about this? And I guess ask you to remember, you know, why I showed you at the beginning of this is, well, our our product, you know, take that whatever’s I drive is giving you no distortion at the terminals, no, you know, near unity power factor. So it becomes something that can really simplify. Yeah. Make make make a life of a plant engineer much simpler by specifying products that are you know low harmonic content. So let’s talk just okay so we kind of defined variable frequency drives. We we like them. They do a lot of good things. But okay there’s some things going on with harmonics. Okay so what’s what’s necessarily bad about these harmonics? So I’ve got a couple slides here showing that’ll walk us through the effects of, you know, kind of the pain points of harmonics. So, you know, with regards to transformers, generally, remember we talked about there’s there’s more current flowing at these other frequencies. So that’s gonna induce some additional heating and additional losses, likely to see some insulation stress, possibly even some resonant frequencies that are gonna set up core vibrations. So those are some of the, you know, undesirable things with generators. You know, there’s most good sized facilities have a standby generator. Right? Well, now if I’m operating a lot of nonlinear loads, I’d really start to need need to start to pay attention to, okay, is my generator gonna work to power these nonlinear loads? So something to consider there. And what what ends up happening is you people may have to oversize that generator Shawn Tierney (Host): Mhmm. Ivan Spronk (Siemens): To be able to run these nonlinear loads. And dropping down to cables and conductors again, if I’ve got more current flowing through them, that’s gonna increase your cable losses due to increased cable resistance caused by the skin effect, which is something that in tendency of alternating currents to flow primarily along the surface of the conductor. Yeah. Increasing or decreasing its ability to, you know, do its job and really deteriorating the the insulation, due to excessive heating. So those are all, you know, negative things that happen when you have a lot of harmonics. Right? Alright. Looking at one more slide of just some, you know, negative impact on circuit breakers or that may trip prematurely or fuses that may open prematurely. Again, thermomagnetic circuit breakers have these bimetallic strips that may be impacted by those additional currents flowing. Electronic type circuit breakers use current sensors which need to account for, you know, these harmonic currents. Yeah. Most circuit breakers are designed to trip at a zero crossover point. So with these distorted currents, you know, there may be some spurious zero crossovers. And then kind of some similar problems with fuses again due to heating effect. This RMS current and non uniform current distribution through the fuse element. You know, what tends to happen is people may have to oversize fuses. But of course, I’m also, you know, to match that actual RMS curve that’s flowing with these harmonics. But okay, that’s not necessarily unless somebody’s out there measuring it, they don’t know what that is. Right, Shawn? And I’ve got codes to meet. I can’t just put a way bigger fuse in. So, you know, it kind of becomes this balancing act. Right? Yep. So Yeah. So those are all things, you know, that happen when you have a lot of harmonics. Again, I can kind of summarize them on one slide here. Line, you know, line harmonics produced by these nonlinear loads cause overheating, inefficient operation, you know, and more losses, perhaps some premature line tripping, perhaps some system oscillations and instability, perhaps noise, and and yeah. And reduced power factor. So none of those are good. Right? In general, reduced efficiency, increased power loss and energy costs, and of course then higher carbon emissions as well. And yet to kind of summarize this all up, current distortion is is bad, infects your all your systems. You gotta account for it. Voltage distortion is often the one that will get people that it’s much worse because that goes all other systems as well if if left unchecked. So that’s my kind of my summary slide there of effects of harmonics and why we wanna do things to control them. So any any thoughts or questions there, Shawn? Shawn Tierney (Host): No. I think I think the slide does a good job of showing that, you know, this isn’t not just for your VFD, VSD. It’s the other things on the line too that you’re affecting. Right? So so now I’m sure some of the, some of those, listening or watching have have stories of where, you know, one drive, two drive wasn’t a problem, four, five, six drives, and they started seeing these issues because it was cumulative. Right? You know, the more drives you have. So, I’d love to hear any stories you guys that are listening and watching have about this and what you did to resolve it. But, this is this is I mean, in some cases, you may just need to get a VFD, like this clean power drive that eliminates this problem versus, you know, other ways of dealing with it. Ivan Spronk (Siemens): Sure. Oh, so, yeah, that that leads well into my next kind of couple of slides here. I mean, harmonics are not new. Line harmonics voltage distortion isn’t something that’s new. I mean, this this has been around for as long as VFBs has been around. So people have come up with, you know, ways to mitigate this. And I’ve got, you know, five of those methods listed on the screen. And we’re just gonna kinda very quickly step through these. But the last one there is really we’re gonna get to okay. What is in the g two twenty that makes it unique, and why do I wanna talk about it? So again, what and we’ll come back to this summary slide at the end here, but just okay. Like I said, people have come up with a handful of different ways to try and mitigate harmonics. First one is just, you know, a simple line reactor. And what you also see is some manufacturers, and Siemens has done this too, to some of our lines. We have DC chokes in the, you know, in that DC link section. You know, it’s an inductor and really all that’s doing is imposing, you know, opposing rather the rate of change of current flowing through it. So it kinda takes the top off of those notches if you you will. Yeah. It’s simple, probably economical. It’s usually applied to each VFD. If you know something about what impedance you need, there’s there’s a selection you know available in these AC line reactors. You can select the impedance you want. But some of the negative things is they take up more panel space. They gotta wire it. And in reality, it only offers kind of a small improvement. So people invented other things. So the next thing I got here is people came up with, they call them massive harmonic filters. They’re also called line harmonic filters, you know, LHF, you see that or harmonic trap filters. And what these do is they eliminate or control kind of those dominant lower order harmonics. I didn’t talk about this much, but these harmonic currents that are flowing they’re they’re much more dominant kind of at the lower end of the frequency range so they these harmonic trap filters work on, you know, those low order harmonics. And they they can be effective for, you know, putting in front of a drive. Kind of what they consist of is a LC circuit there, maybe with a damping resistor, and they get tuned to these specific frequencies. So but again, it’s a device that takes up panel space. I have to install that separate from the drive, so I gotta wire it. And then they don’t do a very good job because they still have, you know, voltage notching and instability on gen generator operation is a a is a known problem with these things. And okay you’re introducing more losses to the system. So that’s passive harmonic filters. The next thing I’ve got here is, you may have this has been pretty common in the industry. It’s called the 18 pulse front end. And really what this does is uses takes your incoming three phase power and really converts it to nine phases with a, you know, special transformer, that creates a phase shift between these different, now nine phases, so I can now I gotta have this 18 pulse, diode bridge and you can kinda see that on the on the slide here too. So I need, you know, this involves a lot of equipment. I need this auto transformer, I need a different rectifier bridge, you know, a much bigger one really, but it does do a really good job of yeah. So I’m not drawing current in big chunks anymore, I’m drawing current more often. Right? Because I’ve got this, you know, 18 pulse rectifier. So it really does a good job of meeting, you know, there’s a standard out there called IEEE five nineteen that’s referenced, that we’ll talk about just a little bit more here in a bit. And these also, work relatively well with the standby generator. Some of the negative things is, okay, you know, soon as I introduce that transformer and more switching, that reduces my system efficiency. And really the big one is this takes a ton of space to not only mount that transformer, but that, 18 pulse rectifier. I got a wire between all of that. So it ends up being a pretty substantial product cost in terms of component cost and and floor space cost. So, but you know has been widely used in the industry but a lot of metal, you know copper and iron, being used in that solution. Next IBT bridge and a DC bus much like the front end, front two parts of that AC drive that I showed you. So we’ve got kind of a the front end and a DC bus set in there. And what this really does is monitors the current and then really generates compensation current in opposite phase to offset harmonics. So this can be, you know, effective. The waveform looks pretty good. It’s unaffected by impedance changes because it’s managing the switches. But yeah, it tends to be you know more complex, it’s more expensive than passive filters, and again it becomes another device to install. Permissioning can be a bit of a challenge because you gotta get this tuned to obtain optimal performance. Although there are some self tuning ones out there that, you know, help take that burden away. But, yeah, you gotta install another piece of equipment that takes up think of it as, you know, two thirds of another VFD setting out there. Right? Shawn Tierney (Host): I would think it is also less energy efficient too because so we all know we have noise canceling headphones. They take power to generate a cancel waveform. Right? So we were already losing power because of harmonics, and now we’re generating another waveform to cancel out the harmonics. So it just seems like we’re losing more energy to produce this canceling wave. So it I mean, I could if this is the option that works, then you have the space granted, but it seems like it’s less energy efficient than maybe a passive filter. Right? But I don’t know. What do you I mean, two thirds more of the panel space as a as just the VFD alone. That sounds like a lot of equipment. Ivan Spronk (Siemens): Give you a a fucking waveform. So I think that’s why people like it. But, yeah, it is definitely something that’s more complex. And and again, I think also there’s that commissioning aspect. And another thing is okay. So you get it set up on a given distribution system and it’s doing great. Okay what happens when I add a couple of more drives on this distribution system? It’s gonna change the dynamics and may need to do some recommissioning. So again it’s something that a plant operator would would need to you know pay attention to. So all those methods and and what I’m gonna get to next is something that’s actually in the G220. So all these previous method methods you know kind of works to a degree and each kind of has its maybe strong points and and not so strong points. But what I want to talk about now is something that’s called active front end. And this is you know, the g two twenty clean power drive is a version of this active front end. So active front ends. So what do we mean by that? Basically, it’s, you know, a sinusoidal input rectifier. And we are controlling the commutation or when we’re conducting energy. So with that we can get, you know, if done right we can have a high dynamic response. So we can respond to, changes for instance, you know, voltage dips in the distribution center excuse me, distribution system. And and because of that, then we we can also kinda get because we’re controlling when we’re conducting current, you know, it’s it’s near you unity power factor. So, yeah. These active front ends have been versions of these drives out there as well. What’s unique about the g two twenty is that it’s a two quadrant active front end. So power is flowing only in one direction. So in other words from the supplier line source, you know, through the drive to the motor. These are called clean power. So you hear the name clean power infeed that’s because okay the, you know, the infeed or line supply is is clean. This is known as something, out in the industry. They’re called Vienna bridge rectifiers. Vienna bridge rectifiers, something that was invented in the mid nineties. And basically, I I just put up a, you know, bigger diagram of kinda what’s going on here. There you can kinda see, okay, it is only two quadrant, but there’s this three level switching process that really reduces all these lower ordered harmonics. So this provides them a stable controllable. The advantage is five voltage DC output, so there’s no voltage reduction going on. Makes it ideal for high power applications like VFDs. And again, remember I mentioned earlier in the conversation here, electric vehicle chargers. So this is a technology that’s been popularized by some of the people. Yeah. Making electric vehicle chargers as well. So and really, yeah. What we’re doing here is using on smaller sizes MOSFETs or on larger sizes, you know, IGBTs here in the power section. Mhmm. And then using a very, you know, part of the sauce here is the control or of the pulse width modulation to manage power inflow is is really, as short a sentence as I can come up to describe what’s going on here. With this, because we’re only controlling power in one direction, there’s some ability, you know, we we don’t have as many switching losses. Again, because we’re only dealing with two quadrants, it’s a compact size, but it is non regenerative. And I I just what I’ll do here is I’ll put up, you know, a four quadrant comparison. So there are active front ends out there that are four quadrant, which has more of a full IGBT, you know, front end to it. The advantage of that is you do get power flow. It is regenerative. You do get power flow in both directions. But of course now I have higher losses because I’m switching in both directions and and you know, just a little bit less efficient. So really kind of coming back to what’s in the the g two twenty clean power drive is this two quadrant Vienna Bridge rectifier. Again because we’re only controlling power in one direction there’s some space savings that that come from that. So yeah and I’ll just add a two quadrant so that’s why this is targeted at you know, non regenerative load applications like pumps and fans. Right? And compressors. Those are not regen load applications. If you need something, you know, four quadrant that would be, you know, like think of a hoisting application or something like that. Maybe large centrifuges or something like that that has a lot of mass that’s been accelerated up and yet can capture some region on the D cell. But that’s kind of, what’s in the g two twenty clean power drive. So, Shawn, I’ll just kinda stop there and the and by the way, the waveform is fantastic. Just dialed that in there. So any thoughts or questions or what’s on your what’s on your mind there? Shawn Tierney (Host): Yeah. No. That’s important to know. So, you know, you got the two quadrant version in the Clean Power g two twenty. And the important thing here is you’re gonna get beautiful. You’re gonna get beautiful elimination of harmonics. You’re gonna have a beautiful waveform. But when you make this choice, you’re also opting out of, regen, like you said, like a hoist or a large inertia load. There’ll be no regenning, which in some cases, you’d be choosing a different VFD. That’s just a different application. Right? Ivan Spronk (Siemens): Exactly. Shawn Tierney (Host): But I think most VFD applications, at least the ones I’ve seen over the years, do not have any regen. Right? They’re your standard purpose, even your high performance VFDs are not doing regen or anything any any type of regeneration capabilities. So I think for most applications, that’s not gonna be an issue, but it’s important to point out. Ivan Spronk (Siemens): What do you think? In the you know, some people we’ve asked questions about, why didn’t you just make it four quadrant? Well, let me ask you, Shawn. What do you think’s less expensive to make? A a two quadrant or four quadrant version? Shawn Tierney (Host): I got a feeling the four quadrant may be twice as much. Yeah. Well, at least that part of it. Right? The front end. Ivan Spronk (Siemens): And when do you think would, you know, take up more handle space Shawn Tierney (Host): at two quadrant or four quadrant? Yeah. Exactly. Exactly. Yeah. Ivan Spronk (Siemens): So, I mean, it’s it’s a very targeted, again, targeted at those, applications that are non region load applications, which Yeah. I’ll I’ll submit that’s at least 80% of them, you know, what’s out there. So if so, again, this really just to emphasize, it’s it’s a Vienna bridge rectifier. So, you know, some uniqueness there. But then really, also the software side of it, you know, building the, algorithm to manage that power flow and assure efficient operation is what’s been done in the g two twenty drive. And yeah. With regards to nice looking waveforms, it’s a lights out, you know, the best looking waveform out there. And matter of fact, I’ve got one more slide here that shows just, you know, development team took one of our g two twenty products, you know. So this is what’s shown over on the left side here is just your standard our, you know, waveform. You can see kind of the double humped waveform there. If you put a passive harmonic filter in front of the g two twenty, you know, waveform starts to look pretty good. But now if you just use a clean power drive, you get a very nice looking waveform. All that worrying about what the effect of harmonics how they’re generated you don’t have to think about that anymore because right at the input terminals of the drive you know, we’re giving you very very low turn harmonic distortion. So and and also that near unity power factor. So that’s really the advantages of the clean power drive. Shawn Tierney (Host): Well, and I you know, just for the audio audience, I mean, we’re looking at the standard g two twenty, right, your standard drive. You’re looking at a total harmonic distortion of, let’s say, 33. Well, you put that passive harmonic filter on, that’s standard drive. Now we’re down to around 4%. Right? But if you have a lot of those drives, that may not be enough. Right? So with the clean power g two twenty, we’re down to under 2%, 1.9 total harmonic distortion. And you see that I know you guys listening can’t see it, but you can see that in the waveforms. All the viewers who are watching can see the waveforms definitely the improvement as you go through each of these options. And, again, you’ll know if you need clean power. Right? I’m fairly sure that, you you know, if you don’t need clean power, you don’t need it. Right? But if you need it Right. And and this is something that I think we’ll see more and more because quite honestly, I mean, power fact, we all know how that affects your utility bill and how our company thinks about that. And so we can accept more stringent controls over time as, yes, the systems become more advanced. You know, you’re gonna get dinged if you have really bad power, you know, the quality of the power. If you’re causing problems down, you know, for the rest of the block or for the rest of the, business park, they’re gonna start tracking that. So let me turn it back to you, Evan. Ivan Spronk (Siemens): Yep. We’re kind of to the end. I’ve got a couple of slides just to summarize what we’ve talked about here. You know, the the g two twenty is, a new drive for us. It’s our next generation SINAMICS product. And really this drive was designed and built on four pillars of digitalization. So in the form of you know, having a digital twin capability to help engineers shorten design and engineering efforts when sizing a drive system, and then tools to optimize operation once it’s up and running. You can see another pillar of secure, meaning security, with regards to cybersecurity and and safety that protects people from machines and protects machines from people as well and other sinister actors. And ease of use, you know, next generation product starting with a clean sheet of paper. Okay. Some things were done with regards to selection, configuring, commissioning, training, things like that with making the product as easy to use as possible. And then this fourth pillar of being sustainable, you know optimizing manufacturing resources and materials used, even operational efficiency during the life of the product and then even considering you know the end of the product life cycle. So all of those things designed into the Sinamics G220 and then if we look again specifically at the advantages of the clean power drive, you know that nice clean low low total distortion that complies with the harmonic standards, near unity power factor, and again, in that space saving design. And just to kinda give you an idea, I’ve I’ve been telling you it’s small, and I think I maybe let the cat out of the bag at the beginning of the, presentation as well. Yeah. Here’s here’s kind of a table that shows dimensions, and there’s that 200 horsepower drive that I referenced. So, yeah, this this technology, you know, it’s not like buy the drive and buy buy something else to add on to it. It’s all in one package. And, yeah, that that 200 horsepower drive, you know, 31 inches tall, less than 12 inches wide, and about 14 inches deep. That’s a 200 horsepower clean power drive that would yeah. You wouldn’t have to think about all this harmonic stuff. And I’m not gonna put up a chart that shows competitor a, b, and c and and our product next to it. But you can take that table and go find go look at other people’s solutions and you’ll see yeah. It’s it’s a very compact device. So that’s kind of the point of that slide there, Shawn. And, yeah, really my last slide then just kind of I have drawn heavily from a white paper that my counterpart, Nikun Shah, wrote. So we’ll give you a link to go download that, white paper. That discusses a little bit more. I’ve kinda mentioned on and off, I triple e five nineteen. That is by far the prevalent standard in this country for, yeah, describing what harmonics are, different medication techniques. And then, you know, there’s tables in there. It’s like, okay, if you’re being called to meet specification at triple eight five nineteen, you know, here are the harmonic current distortion levels and voltage distortion levels that that you need to meet. So that’s all laid out in that white paper. Yeah. And then we’ll give you a a link to our website, to the g two twenty catalog. I have another very useful feature shown that I’ll give you a link to is the seamless product selector where you can go and, you know put in a part you know very quickly pick a part number and then get to some you know CAD models of it. And then I’ve mentioned that energy savings calculator at all. So Shawn that’s kind of what I had for today. I hope that was interesting to you and, more importantly, interesting to your audience. Shawn Tierney (Host): Yeah. And I just wanna remind the audience that we had you on to talk about the g two twenty a while back. We also had Jackie on that go through commissioning the one twenty and the two twenty. So if you’re kinda curious, how do you do that in TIA portal? Because I’ve never done that before. So Jackie came on, and she walked us through that for both of these two models. We also have received some samples from Siemens. So we will be, trying those out them ourselves here in the in the studio. Don’t know. Don’t have a date on that. We’re a little backed up here. But, definitely, they’re right in front of me every day, so I don’t forget about them. So we’ll be doing that as well. And, then we’ll make those available to our in person students who come to the school as well as we’ll add those as lessons to the online course over at the automation school. But so lots of stuff. We’ve had a lot of coverage. If you have any questions, check out this white paper. I’m sure we just touched the surface of what’s in there. And, of course, Ivan and all his colleagues at Siemens would love to hear from you. And, Ivan, let me, pass it back to you for the final word. Ivan Spronk (Siemens): Yeah. Just thank you so much for having me on, Shawn. Shawn Tierney (Host): Well, I hope you enjoyed that episode. I wanna thank Ivan for coming on the show and giving us that very technical presentation, which I totally enjoyed. I hope you guys did too. Also wanna thank Siemens for sponsoring this episode because you guys know I love to really stem completely ad free and available to the entire public. So with that said, I also wanna thank you for tuning back in this week. If you think about it, please give me a thumbs up or a like or a five star review. That is the best way for me to find new vendors to come on the show. And with the exception of Thanksgiving week, we should have a show every week up until the last two weeks of the year, and we are already recording shows for next year. So I’m excited about that. If you know any vendors you think we should be on the show, please reach out to them. I’m working on a new media guide as well, and so, we’d love to have them on the show this coming year of 2026. So with that said, I just wanna wish you all good health and happiness. And until next time, my friends, peace. Until next time, Peace ✌️  If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

Factories don't run on magic. They run on control panels that turn raw sensor data into precise, safe action—and we're kicking off a three‑part series to show exactly how. We break down the essentials in plain language so you can open a panel door and actually know what you're seeing, from the disconnect and power supplies to the PLC logic and the HMI screens operators trust.We start with the PLC, the rugged brain that reads inputs, executes logic, and drives outputs with millisecond timing. You'll learn why modern controllers are networked, how modular I/O scales with your process, and what clean wiring and accurate channel maps do for uptime. Then we shift to the HMI, the operator window into the process. A well‑built screen mirrors the machine, makes status obvious, and keeps routine actions outside the enclosure for safer work. Clear colors, readable values, trends, and alarms turn data into smart, fast decisions.Power is the quiet foundation. We walk through the pathway: visible disconnects, fuses and breakers sized for protection, control transformers that step down voltage, and 24 VDC power supplies that feed sensors, relays, and PLC cards. Grounding, spacing, and heat management guard both people and electronics. Along the way, we share practical tips to read a panel like a map: trace power first, find the PLC and I/O, compare HMI values to the machine, and rely on current drawings stored on the door. These habits, backed by UL 508A and NFPA 79 principles, create safer, more reliable systems that technicians can troubleshoot under pressure.With nearly a century of experience supporting automation across industries, we believe craftsmanship and documentation are force multipliers. If you're new to automation, mentoring someone who is, or just want a refresher, this guide will raise your confidence on the plant floor. Subscribe for the next parts of the series, share this with a colleague who needs it, and leave a quick review to help more pros find the show.Keep Asking Why...Read our latest article on Industrial Manufacturing herehttps://eecoonline.com/inspire/panels_101 Online Account Registration:Video Explanation of Registering for an AccountRegister for an AccountOther Resources to help with your journey:Installed Asset Analysis SupportSystem Planning SupportSchedule your Visit to a Lab in North or South CarolinaSchedule your Visit to a Lab in VirginiaSubmit your questions and feedback to: podcast@eecoaskwhy.comFollow EECO on LinkedInHost: Chris Grainger