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Augmented - the industry 4.0 podcast
Episode 97: Industrial AI

Augmented - the industry 4.0 podcast

Play Episode Listen Later Sep 21, 2022 47:41


Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. The topic is Industrial AI. Our guest is Professor Jay Lee, the Ohio Eminent Scholar, the L.W. Scott Alter Chair Professor in Advanced Manufacturing, and the Founding Director of the Industrial AI Center at the University of Cincinnati (https://www.iaicenter.com/). In this conversation, we talk about how AI does many things but to be applicable; the industry needs it to work every time, which puts additional constraints on what can be done by when. If you liked this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 81: From Predictive to Diagnostic Manufacturing Augmentation (https://www.augmentedpodcast.co/81). Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim (https://trondundheim.com/) and presented by Tulip (https://tulip.co/). Follow the podcast on Twitter (https://twitter.com/AugmentedPod) or LinkedIn (https://www.linkedin.com/company/75424477/). Trond's Takeaway: Industrial AI is a breakthrough that will take a while to mature. It implies discipline, not just algorithms. In fact, it entails a systems architecture consisting of data, algorithm, platform, and operation. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Industrial AI. Our guest is Professor Jay Lee, the Ohio Eminent Scholar, and the L.W. Scott Alter Chair Professor in Advanced Manufacturing, and the Founding Director of the Industrial AI Center at the University of Cincinnati. In this conversation, we talk about how AI does many things but to be applicable, industry needs it to work every time, which puts on additional constraints on what can be done by when. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Jay, it's a pleasure to have you here. How are you today? JAY: Good. Thank you for inviting me to have a good discussion about industrial AI. TROND: Yeah, I think it will be a good discussion. Look, Jay, you are such an accomplished person, both in terms of your academics and your industrial credentials. I wanted to quickly just go through where you got to where you are because I think, especially in your case, it's really relevant to the kinds of findings and the kinds of exploration that you're now doing. You started out as an engineer. You have a dual degree. You have a master's in industrial management also. And then you had a career in industry, worked at real factories, GM factories, Otis elevators, and even on Sikorsky helicopters. You had that background, and then you went on to do a bunch of different NSF grants. You got yourself; I don't know, probably before that time, a Ph.D. in mechanical engineering from Columbia. The rest of your career, and you correct me, but you've been doing this mix of really serious industrial work combined with academics. And you've gone a little bit back and forth. Tell me a little bit about what went into your mind as you were entering the manufacturing topics and you started working in factories. Why have you oscillated so much between industry and practice? And tell me really this journey; give me a little bit of specifics on what brought you on this journey and where you are today. JAY: Well, thank you for talking about this career because I cut my teeth from the factory early years. And so, I learned a lot of fundamental things in early years of automation. In the early 1980s, in the U.S, it was a tough time trying to compete with the Japanese automotive industry. So, of course, the Big Three in Detroit certainly took a big giant step, tried to implement a very good manufacturing automation system. So I was working for Robotics Vision System at that time in New York, in Hauppage, New York, Long Island. And shortly, later on, it was invested by General Motors. And in the meantime, I was studying part-time in Columbia for my mechanical engineering, Doctor of Engineering. And, of course, later on, I transferred to George Washington because I had to make a career move. So I finished my Ph.D. Doctor of Science in George Washington later. But the reason we stopped working on that is because of the shortage of knowledge in making automation work in the factory. So I was working full-time trying to implement the robots automation in a factory. In the meantime, I also found a lack of knowledge on how to make a robot work and not just how to make a robot move. Making it move means you can program; you can do very fancy motion. But that's not what factories want. What factories really want is a non-stop working system so they can help people to accomplish the job. So the safety, and the certainty, the accuracy, precision, maintenance, all those things combined together become a headache actually. You have to calibrate the robot all the time. You have to reprogram them. So eventually, I was teaching part-time in Stony Brook also later on how to do the robotic stuff. And I think that was the early part of my career. And most of the time I spent in factory and still in between the part-time study and part-time working. But later on, I got a chance to move to Washington, D.C. I was working for U.S. Postal Service headquarters as Program Director for automation. In 1988, post service started a big initiative trying to automate a 500 mil facility in the U.S. There are about 115 number one facilities which is like New York handled 8 million mail pieces per day at that time; you're talking about '88. But most are manual process, so packages. So we started developing the AI pattern recognition, hand-written zip code recognition, robotic postal handling, and things like that. So that was the opportunity that attracted me actually to move away from automotive to service industry. So it was interesting because you are working with top scientists from different universities, different companies to make that work. So that was the early stage of the work. Later on, of course, I had a chance to work with the National Science Foundation doing content administration in 1991. That gave me the opportunity to work with professors in universities, of course. So then, by working with them, I was working on a lot of centers like engineering research centers and also the Industry-University Cooperative Research Centers Program, and later on, the materials processing manufacturing programs. So 1990 was a big time for manufacturing in the United States. A lot of government money funded the manufacturer research, of course. And so we see great opportunity, like, for example, over the years, all the rapid prototyping started in 1990s. It took about 15-20 years before additive manufacturing came about. So NSF always looks 20 years ahead, which is a great culture, great intellectual driver. And also, they're open to the public in terms of the knowledge sharing and the talent and the education. So I think NSF has a good position to provide STEM education also to allow academics, professors to work with industry as well, not just purely academic work. So we support both sides. So that work actually allowed me to understand what is real status in research, in academics, also how far from real implementation. So in '95, I had the opportunity to work in Japan actually. I had an opportunity...NSF had a collaboration program with the MITI government in Japan. So I took the STA fellowship called science and technology fellow, STA, and to work in Japan for six months and to work with 55 organizations like Toyota, Komatsu, Nissan, FANUC, et cetera. So by working with them, then you also understand what the real technology level Japan was, Japanese companies were. So then you got calibration in terms of how much U.S. manufacturing? How much Japanese manufacturing? So that was in my head, actually. I had good weighting factors to see; hmm, what's going on here between these two countries? That was the time. So when I came back, I said, oh, there's something we have to do differently. So I started to get involved in a lot of other things. In 1998, I had the opportunity to work for United Technologies because UTC came to see me and said, "Jay, you should really apply what you know to real companies." So they brought me to work as a Director for Product Environment Manufacturing Department for UTRC, United Technology Research Center, in East Hartford. Obviously, UTC business included Pratt & Whitney jet engines, Sikorsky helicopters, Otis elevators, Carrier Air Conditioning systems, Hamilton Sundstrand, et cetera. So all the products they're worldwide, but the problem is you want to support global operations. You really need not just the knowledge, what you know, but also the physical usage, what you don't know. So you know, and you don't know. So how much you don't know about a product usage, that's how the data is supposed to be coming back. Unfortunately, back in 1999, I have to tell you; unfortunately, most of the product data never came back. By the time it got back, it is more like a repair overhaul recur every year to a year later. So that's not good. So in Japan, I was experimenting the first remote machine monitoring system using the internet actually in 1995. So I published a paper in '98 about how to remotely use physical machine and cyber machine together. In fact, I want to say that's the first digital twin but as a cyber-physical model together. That was in my paper in 1998 in Journal of Machine Tools and Manufacture. TROND: So, in fact, you were a precursor in so many of these fields. And it just strikes me that as you're going through your career here, there are certain pieces that you seem to have learned all along the way because when you are a career changer oscillating between public, private, semi-private, research, business, you obviously run the risk of being a dilettante in every field, but you seem to have picked up just enough to get on top of the next job with some insight that others didn't have. And then, when you feel like you're frustrated in that current role, you jump back or somewhere else to learn something new. It's fascinating to me because, obviously, your story is longer than this. You have startup companies with your students and others in this business and then, of course, now with the World Economic Forum Lighthouse factories and the work you've been doing for Foxconn as well. So I'm just curious. And then obviously, we'll get to industrial AI, which is so interesting in your perspective here because it's not just the technology of it; it is the industrial practice of this new domain that you have this very unique, practical experience of how a new technology needs to work. Well, you tell me, how did you get to industrial AI? Because you got there to, you know, over the last 15-20 years, you integrated all of this in a new academic perspective. JAY: Well, that's where we start. So like I said earlier, I realized industry we did not have data back in the late 1990s. And in 1999, dotcom collapsed, remember? TROND: Yes, yes. JAY: Yeah. So all the companies tried to say, "Well, we're e-business, e-business, e-commerce, e-commerce," then in 2000, it collapsed. But the reality is that people were talking about e-business, but in the real world, in industrial setting, there's no data almost. So I was thinking, I mean, it's time I need to think about how to look at data-centric perspectives, how to develop such a platform, and also analytics to support if one-day data comes with a worry-free kind of environment. So that's why I decided to transition to an academic career in the year 2000. So what I started thinking, in the beginning, was where has the most data? As we all know, the product lifecycle usage is out there. You have lots of data, but we're not collecting it. So eventually, I called a central Intelligent Maintenance System called IMS, not intelligent manufacturing system because maintenance has lots of usage data which most developers of a product don't know. But if we have a way to collect this data to analyze and predict, then we can guarantee the product uptime or the value creation, and then the customer will gain most of the value back. Now we can use the data feedback to close-loop design. That was the original thinking back in the year 2000, which at that time, no cell phone could connect to the internet. Of course, nobody believed you. So we used a term called near-zero downtime, near-zero downtime, ZDT. Nobody believed us. Intel was my first founding member. So I made a pitch to FANUC in 2001. Of course, they did not believe it either. Of course, FANUC in 2014 adopted ZDT, [laughs] ZDT as a product name. But as a joke, when I talked to the chairman, the CEO of the company in 2018 in Japan, Inaba-san that "Do you know first we present this ZDT to your company in Michigan? They didn't believe it. Now you guys adopted." "Oh, I didn't know you use it." So when he came to visit in 2019, they brought the gift. [laughs] So anyway, so what happened is during the year, so we worked with the study of 6 companies, 20 companies and eventually they became over 100 companies. And in 2005, I worked with Procter & Gamble and GE Aircraft Engine. They now became GE Aviation; then, they got a different environment. So machine learning became a typical thing you use every day, every program, but we don't really emphasize AI at that time. The reason is machine learning is just a tool. It's an algorithm like a support-vector machine, self-organizing map, and logistic regression. All those are just supervised learning or now supervised learning techniques. And people use it. We use it like standard work every day, but we don't talk about AI. But over the years, when you work with so many companies, then you realize the biggest turning point was Toyota 2005 and P&G in 2006. The reason I'm telling you 2005 is Toyota had big problems in the factory in Georgetown, Kentucky, where the Camry factory is located. So they had big compressor problems. So we implemented using machine learning, the support-vector machine, and also principal component analysis. And we enable that the surge of a compressor predicted and avoided and never happened. So until today -- TROND: So they have achieved zero downtime after that project, essentially. JAY: Yeah. So that really is the turning point. Of course, at P&G, the diaper line continues moving the high volume. They can predict things, reduce downtime to 1%. There's a lot of money. Diaper business that is like $10 billion per year. TROND: It's so interesting you focus on downtime, Jay, because obviously, in this hype, which we'll get to as well, people seem to focus so much on fully automated versus what you're saying, which is it doesn't really, you know, we will get to the automation part, but it is the downtime that's where a lot of the savings is obviously. Because whether it's a lights out or lights on, humans are not the real saving here. And the real accomplishment is in zero downtime because that is the industrialization factor. And that is what allows the system to keep operating. Of course, it has to do with automation, but it's not just that. Can you then walk us through what then became industrial AI for you? Because as I've now understood it, it is a highly specific term to you. It's not just some sort of fluffy idea of very, very advanced algorithms and robots running crazy around autonomously. You have very, very specific system elements. And they kind of have to work together in some architectural way before you're willing to call it an industrial AI because it may be a machine tool here, and a machine tool there, and some data here. But for you, unless it's put in place in a working architecture, you're not willing to call it, I mean, it may be an AI, but it is not an industrial AI. So how did this thinking then evolve for you? And what are the elements that you think are crucial for something that you even can start to call an industrial AI? Which you now have a book on, so you're the authority on the subject. JAY: Well, I think the real motivation was after you apply all the machine learning toolkits so long...and a company like National Instruments, NI, in Austin, Texas, they licensed our machine learning toolkits in 2015. And eventually, in 2017, they started using the embedding into LabVIEW version. So we started realizing, actually, the toolkit is very important, not just from the laboratory point of view but also from the production and practitioners' point of view from industry. Of course, researchers use it all the time for homework; I mean, that's fine. So eventually, I said...the question came to me about 2016 in one of our industry advisory board meeting. You have so many successes, but the successes that happen can you repeat? Can you repeat? Can you repeatably have the same success in many, many other sites? Repeatable, scalable, sustainable, that's the key three keywords. You cannot just have a one-time success and then just congratulate yourself and forget it, no. So eventually, we said, oh, to make that repeat sustainable, repeatable, you have a systematic discipline. TROND: I'm so glad you say this because I have taken part in a bunch of best practice schemes and sometimes very optimistically by either an industry association or even a government entity. And they say, "Oh yeah, let's just all go on a bunch of factory visits." Or if it's just an IT system, "Let's just all write down what we did, and then share it with other people." But in fact, it doesn't seem to me like it is that easy. It's not like if I just explain what I think I have learned; that's not something others can learn from. Can you explain to me what it really takes to make something replicable? Because you have done that or helped Foxconn do that, for example. And now you're obviously writing up case studies that are now shared in the World Economic Forum across companies. But there's something really granular but also something very systemic and structured about the way things have to be explained in order to actually make it repeatable. What is the sustainability factor that actually is possible to not just blue copy but turn it into something in your own factory? JAY: Well, I think that there are basically several things. The data is one thing. We call it the data technology, DT, and which means data quality evaluation. How do you understand what to use, what not to use? How do you know which data is useful? And how do you know where the data is usable? It doesn't mean useful data is usable, just like you have a blood donation donor, but the blood may not be usable if the donor has HIV. I like to use an analogy like food. You got a fish in your hand; wow, great. But you have to ask where the fish comes from. [chuckles] If it comes from polluted water, it's not edible, right? So great fish but not edible. TROND: So there's a data layer which has to be usable, and it has to be put somewhere and put to use. It actually then has to be used. It can't just be theoretically usable. JAY: So we have a lot of useful data people collect. The problem is people never realized lots of them are not usable because of a lack of a label. They have no background, and they're not normalized. So eventually, that is a problem. And even if you have a lot of data, it doesn't mean it is usable. TROND: So then I guess that's how you get to your second layer, which I guess most people just call machine learning, but for you, it's an algorithmic layer, which is where some of the structuring gets done and some of the machines that put an analysis on this, put in place automatic procedures. JAY: And machine learning to me it's like cooking ware like a kitchen. You got a pan fry; you got a steamer; you got the grill. Those are tools to cook the food, the data. Food is like data. Cooking ware is like AI. But it depends on purpose. For example, you want fish. What do you want to eat first? I want soup. There's a difference. Do you want to grill? Do you want to just deep fry? So depending on how you want to eat it, the cooking ware will be selected differently. TROND: Well, and that's super interesting because it's so easy to say, well, all these algorithms and stuff they're out there, and all you have to do is pick up some algorithms. But you're saying, especially in a factory, you can't just pick any tool. You have to really know what the effect would be if you start to...for example, on downtime, right? Because I'm imagining there are very many advanced techniques that could be super advanced, but they are perhaps not the right tool for the job, for the workers that are there. So how does that come into play? Are these sequential steps, by the way? So once you figure out what the data is then, you start to fiddle with your tools. JAY: Well, there are two perspectives; one perspective is predict and prevent. So you predict something is going to happen. You prevent it from happening, number one. Number two, understand the root causes and potential root causes. So that comes down to the visible and invisible perspective. So from the visible world, we know what to measure. For example, if you have high blood pressure, you measure blood pressure every day, but that may not be the reason for high blood pressure. It may be because of your DNA, maybe because of the food you eat, because of lack of exercise, because of many other things, right? TROND: Right. JAY: So if you keep measuring your blood pressure doesn't mean you have no heart attack. Okay, so if you don't understand the reason, measuring blood pressure is not a problem. So I'm saying that you know what you don't know. So we need to find out what you don't know. So the correlation of invisible, I call, visible-invisible. So I will predict, but you also want to know the invisible reason relationship so you can prevent that relationship from happening. So that is really called deep mining those invisibles. So we position ourselves very clearly between visible-invisible. A lot of people just say, "Oh, we know what the problem is." The problem is not a purpose. For example, the factory manufacturing there are several very strong purposes, number one quality, right? Worry-free quality. Number two, your efficiency, how much you produce per dollar. If you say that you have great quality, but I spent $10,000 to make it, it is very expensive. But if you spend $2 to make it, wow, that's great. How did you do it? So quality per dollar is a very different way of judging how good you are. You got A; I spent five days studying. I got A; I spent two hours studying. Now you show the capability difference. TROND: I agree. And then the third factor in your framework seems to be platform. And that's when I think a lot of companies go wrong as well because platform is...at least historically in manufacturing, you pick someone else's platform. You say I'm going to implement something. What's available on the market, and what can I afford, obviously? Or ideally, what's the state of the art? And I'll just do that because everyone seems to be doing that. What does platform mean to you, and what goes into this choice? If you're going to create this platform for industrial AI, what kind of a decision is that? JAY: So DT is data, AT is algorithm, and PT is platform, PT platform. Platform means some common things are used in a shared community. For example, kitchen is a platform. You can cook. I can cook. I can cook Chinese food. I can cook Italian food. I can cook Indian food. Same kitchen but different recipe, different seasoning, but same cooking ware. TROND: Correct. Well, because you have a good kitchen, right? JAY: Yes. TROND: So that's -- JAY: [laughs] TROND: Right? JAY: On the platform, you have the most frequently used tool, not everything. You don't need 100 cooking ware in your kitchen. You probably have ten or even five most daily used. TROND: Regardless of how many different cuisines you try to cook. JAY: Exactly. That's called the AI machine toolkit. So we often work with companies and say, "You don't need a lot of tools, come on. You don't need deep learning. You need a good logistic regression and support-vector machine, and you're done." TROND: Got it. JAY: Yeah, you don't need a big chainsaw to cut small bushes. You don't need it. TROND: Right. And that's a very different perspective from the IT world, where many times you want the biggest tool possible because you want to churn a lot of data fast, and you don't really know what you're looking for sometimes. So I guess the industrial context here really constrains you. It's a constraint-based environment. JAY: Yes. So industry, like I said, the industry we talked about three Ps like I said: problems, purposes, and processes. So normally, problem comes from...the main thing is logistic problems, machine, and factory problems, workforce problems, the quality problems, energy problem, ignition problem, safety problems. So the problem happens every day. That's why in factory world, we call it firefighting. Typically, you firefight every day. TROND: And is that your metaphor for the last part of your framework, which is actually operation? So operation sounds really nice and structured, right? JAY: [chuckles] Yes. TROND: As if that was like, yeah, that's the real thing, process. We got this. But in reality, it feels sometimes, to many who are operating a factory; it's a firefight. JAY: Sometimes the reason lean theme work, Six Sigma, you turn a problem into a process, five Ss process, okay? And fishbone diagram, Pareto chart, and Kaizen before and after. So all the process, SOP, so doesn't matter which year workforce comes in, they just repeat, repeat, repeat, repeat, repeat. So in Toyota, the term used to be called manufacturing is just about the discipline. It's what they said. The Japanese industry manufacturing is about discipline, how you follow a discipline to everyday standard way, sustainable way, consistent way, and then you make good products. This is how the old Toyota was talking about, old one. But today, they don't talk that anymore. Training discipline is only one thing; you need to understand the value of customers. TROND: Right. So there are some new things that have to be added to the lean practices, right? JAY: Yes. TROND: As time goes by. So talk to me then more about the digital element because industrial AI to you, clearly, there's a very clear digital element, but there's so many, many other things there. So I'm trying to summarize your framework. You have these four factors: data, algorithms, platforms, and operations. These four aspects of a system that is the challenge you are dealing with in any factory environment. And some of them have to do with digital these days, and others, I guess, really have to do more with people. So when that all comes together, do you have some examples? I don't know, we talked about Toyota, but I know you've worked with Foxconn and Komatsu or Siemens. Can you give me an example of how this framework of yours now becomes applied in a context? Where do people pick up these different elements, and how do they use them? JAY: There's a matrix thinking. So horizontal thinking is a common thing; you need to have good digital thread including DT, data technology, AT, algorithms or analytics, PT, platform, edge cloud, and the things, and OT operation like scheduling, optimizations, stuff like that. Now, you got verticals, quality vertical, cost vertical, efficiency verticals, safety verticals, emission verticals. So you cannot just talk about general. You got to have focus on verticals. For example, let me give you one example: quality verticals. Quality is I'm the factory manager. I care about quality. Yes, the customer will even care more, so they care. But you have a customer come to your shop once a month to check. You ask them, "Why you come?" "Oh, I need to see how good your production." "How about you don't have to come? You can see my entire quality." "Wow, how do I do that?" So eventually, we develop a stream of quality code, SOQ, Stream Of Quality. So it's not just about the product is good. I can go back to connect all the processes of the quality segment of each station. Connect them together. Just like you got a fish, oh, okay, the fish is great. But I wonder, when the fish came out of water, when the fish was in the truck, how long was it on the road? And how long was it before reaching my physical distribution center and to my home? So if I have a sensor, I can tell you all the temperature history inside the box. So when you get your fish, you take a look; oh, from the moment the fish came out of the boat until it reached my home, the temperature remained almost constant. Wow. Now you are worry-free. It's just one thing. So you connect together. So that's why we call SOQ, Stream Of Quality, like a river connected. So by the time a customer gets a quality product, they can trace back and say, "Wow, good. How about if I let you see it before you come? How about you don't come?" I say, "Oh, you know what? I like it." That's what this type of manufacturing is about. It just doesn't make you happy. You have to make the customer happy, worry-free. MID-ROLL AD: In the new book from Wiley, Augmented Lean: A Human-Centric Framework for Managing Frontline Operations, serial startup founder Dr. Natan Linder and futurist podcaster Dr. Trond Arne Undheim deliver an urgent and incisive exploration of when, how, and why to augment your workforce with technology, and how to do it in a way that scales, maintains innovation, and allows the organization to thrive. The key thing is to prioritize humans over machines. Here's what Klaus Schwab, Executive Chairman of the World Economic Forum, says about the book: "Augmented Lean is an important puzzle piece in the fourth industrial revolution." Find out more on www.augmentedlean.com and pick up the book in a bookstore near you. TROND: So, Jay, you took the words out of my mouth because I wanted to talk about the future. I'm imagining when you say worry-free, I mean, you're talking about a soon-to-be state of manufacturing. Or are you literally saying there are some factories, some of the excellence factories where you've won awards in the World Economic Forum or other places that are working towards this worry-free manufacturing, and to some extent, they have achieved it? Well, elaborate for me a little bit about the future outlook of manufacturing and especially this people issue because you know that I'm engaged...The podcast is called Augmented Podcast. I'm engaged in this debate about automation. Well, is there a discrepancy between automation and augmentation? And to what extent is this about people running the system? Or is it the machines that we should optimize to run all the system? For you, it's all about worry-free. First of all, just answer this question, is worry-free a future ideal, or is it actually here today if you just do the right things? JAY: Well, first of all, worry-free is our mindset where the level of satisfaction should be, right? TROND: Yep. JAY: So to make manufacturing happen is not about how to make good quality, how to make people physically have less worry, how to make customers less worry is what is. But the reason we have a problem with workforce today, I mean, we have a hard time to hire not just highly skilled workers but even regular workforce. Because for some reason, not just U.S., it seems everywhere right now has similar problems. People have more options these days to select other living means. They could be an Uber driver. [laughs] They could be...I don't know. So there are many options. You don't have to just go to the factory to make earnings. They can have a car and drive around Uber and Lyft or whatever. They can deliver the food and whatever. So they can do many other things. And so today, you want to make workforce work environment more attractive. You have to make sure that they understand, oh, this is something they can learn; they can grow. They are fulfilled because the environment gives them a lot of empowerment. The vibe, the environment gives them a wow, especially young people; when you attract them from college, they'd like a wow kind of environment, not just ooh, okay. [laughs] TROND: Yeah. Well, it's interesting you're saying this. I mean, we actually have a lack of workers. So it's not just we want to make factories full of machines; it's actually the machines are actually needed just because there are no workers to fill these jobs. But you're looking into a future where you do think that manufacturing is and will be an attractive place going forward. That seems to be that you have a positive vision of the future we're going into. You think this is attractive. It's interesting for workers. JAY: Yeah. See, I often say that there are some common horizontal we have to use all the day. Vertical is the purpose, quality. I talked about vertical quality first, quality. But what are the horizontal common? I go A, B, C, D, E, F. What's A? AI. B is big data. C is cyber and cloud. D is digital or digital twin, whatever. E is environment ecosystem and emission reduction. What's F? Very important, fun. [laughs] If you miss that piece, who wants to work for a place there's no fun? You tell me would you work for...you and I, we're talking now because it's fun. You talk to people and different perspectives. I talk to you, and I say, wow, you've built some humongous network here in the physical...the future of digital, not just professional space but also social space but also the physical space. So, again, the fun things inspire people, right? TROND: They do. So talking about inspiring people then, Jay, if you were to paint a picture of this future, I guess, we have talked just now about workers and how if you do it right, it's going to be really attractive workplaces in manufacturing. How about for, I guess, one type of worker, these knowledge workers more generally? Or, in fact, is there a possibility that you see that not just is it going to be a fun place to be for great, many workers, but it's actually going to be an exciting knowledge workplace again? Which arguably, industrialization has gone through many stages. And being in a factory wasn't always all that rosy, but it was certainly financially rewarding for many. And it has had an enormous career progression for others who are able to find ways to exploit this system to their benefit. How do you see that going forward? Is there a scope, is there a world in which factory work can or perhaps in an even new way become truly knowledge work where all of these industrial AI factors, the A to the Fs, produce fun, but they produce lasting progression, and career satisfaction, empowerment, all these buzzwords that everybody in the workplace wants and perhaps deserves? JAY: That's how we look at the future workforce is not just about the work but also the knowledge force. So basically, the difference is that people come in, and they become seasoned engineers, experienced engineers. And they retire, and the wisdom carries with them. Sometimes you have documentation, Excel sheet, PPT in the server, but nobody even looks at it. That's what today's worry is. So now what you want is living knowledge, living intelligence. The ownership is very important. For example, I'm a worker. I develop AI, not just the computer software to help the machine but also help me. I can augment the intelligence. I will augment it. When I make the product happen, the inspection station they check and just tell me pass or no pass. They also tell me the quality, 98, 97, but you pass. And then you get your score. You got a 70, 80, 90, but you got an A. 99, you got an A, 91, you got an A, 92. So what exactly does A mean? So, therefore, I give you a reason, oh, this is something. Then I learn. Okay, I can contribute. I can use voice. I can use my opinion to augment that no, labeled. So next time people work, oh, I got 97. And so the reason is the features need to be maintained, to be changed, and the system needs to be whatever. So eventually, you have a human contribute. The whole process could be consisting of 5 experts, 7, 10, 20, eventually owned by 20 people. That legacy continues. And you, as a worker, you feel like you're part of the team, leave a legacy for the next generation. So eventually, it's augmented intelligence. The third level will be actual implementation. So AI is not about artificial intelligence; it is about actual implementation. So people physically can implement things in a way they can make data to decisions. So their decision mean I want to make an adjustment. I want to find out how much I should adjust. Physically, I can see the gap. I can input the adjustment level. The system will tell me physically how could I improve 5%. Wow, that's good. I made a 5% improvement. Your boss also knows. And your paycheck got the $150 increase this month. Why? Because my contribution to the process quality improved, so I got the bonus. That's real-world feedback. TROND: Let me ask you one last question about how this is going to play out; I mean, in terms of how the skilling of workers is going to allow this kind of process. A lot of people are telling me about the ambitions that I'm describing...and some of the guests on the podcasts and also the Tulip software platform, the owner of this podcast, that it is sometimes optimistic to think that a lot of the training can just be embedded in the work process. That is obviously an ideal. But in America, for example, there is this idea that, well, you are either a trained worker or an educated worker, or you are an uneducated worker. And then yes, you can learn some things on the job. But there are limits to how much you can learn directly on the job. You have to be pulled out, and you have to do training and get competencies. As you're looking into the future, are there these two tracks? So you either get yourself a short or long college degree, and then you move in, and then you move faster. Or you are in the factory, and then if you then start to want to learn things, you have to pull yourself out and take courses, courses, courses and then go in? Or is it possible through these AI-enabled training systems to get so much real-time feedback that a reasonably intelligent person actually never has to be pulled out of work and actually they can learn on the job truly advanced things? So because there are two really, really different futures here, one, you have to scale up an educational system. And, two, you have to scale up more of a real-time learning system. And it seems to me that they're actually discrepant paths. JAY: Sure. To me, I have a framework in my book. I call it the four P structure, four P. First P is principle-based. For example, in Six Sigma, in lean manufacturing, there's some basic stuff you have to study, basic stuff like very simple fishbone diagram. You have to understand those things. You can learn by yourself what that is. You can take a very basic introduction course. So we can learn and give you a module. You can learn yourself or by a group, principle-based. The second thing is practice-based. Basically, we will prepare data for you. We will teach you how to use a tool, and you will do it together as a team or as individual, and you present results by using data I give to you, the tool I give to you. And it's all, yeah, my team A presented. Oh, they look interesting. And group B presented, so we are learning from each other. Then after the group learning is finished, you go back to your team in the real world. You create a project called project-based learning. You take a tool you learn. You take the knowledge you learn and to find a project like a Six Sigma project you do by yourself. You formulate. And then you come back to the class maybe a few weeks later, present with a real-world project based on the boss' approval. So after that, you've got maybe a black belt but with the last piece professional. Then you start teaching other people to repeat the first 3ps. You become master black belt. So we're not reinventing a new term. It really is about a similar concept like lean but more digital space. Lean is about personal experience, and digital is about the data experience is what's the big difference. TROND: But either way, it is a big difference whether you have to rely on technological experts, or you can do a lot of these things through training and can get to a level of aptitude that you can read the signals at least from the system and implement small changes, perhaps not the big changes but you can at least read the system. And whether they're low-code or no-code, you can at least then through learning frameworks, you can advance, and you can improve in not just your own work day, but you can probably in groups, and feedbacks, and stuff you can bring the whole team and the factory forward perhaps without relying only on these external types of expertise that are actually so costly because they take you away. So per definition, you run into this; I mean, certainly isn't worry-free because there is an interruption in the process. Well, look, this is fascinating. Any last thoughts? It seems to me that there are so many more ways we can dig deeper on your experience in any of these industrial contexts or even going deeper in each of the frameworks. Is there a short way to encapsulate industrial AI that you can leave us with just so people can really understand? JAY: Sure. TROND: It's such a fundamental thing, AI, and people have different ideas about that, and industry people have something in their head. And now you have combined them in a unique way. Just give us one sentence: what is industrial AI? What should people leave this podcast with? JAY: AI is a cognitive science, but industrial AI is a systematic discipline is one sentence. So that means people have domain knowledge. Now we have to create data to represent our domain then have the discipline to solve the domain problems. Usually, with domain knowledge, we try with our experience, and you and I know; that's it. But we have no data coming out. But if I have domain become data and data become discipline, then other people can repeat our success even our mistake; they understand why. So eventually, domain, data, discipline, 3 Ds together, you can make a good decision, sustainable and long-lasting. TROND: Jay, this has been so instructive. I thank you for spending this time with me. And it's a little bit of a never-ending process. JAY: [laughs] TROND: Industry is not something that you can learn it and then...because also the domain changes and what you're doing and what you're producing changes as well. So it's a lifelong -- JAY: It's rewarding. TROND: Rewarding but lifelong quest. JAY: Yeah. Well, thank you for the opportunity to share, to discuss. Thank you. TROND: It's a great pleasure. You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was Industrial AI. And our guest was Professor Jay Lee from University of Cincinnati. In this conversation, we talked about how AI in industry needs to work every time and what that means. My takeaway is that industrial AI is a breakthrough that will take a while to mature. It implies discipline, not just algorithms. In fact, it entails a systems architecture consisting of data, algorithm, platform, and operation. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 81: From Predictive to Diagnostic Manufacturing Augmentation. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us. We would love to share your thoughts with other listeners. The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects the people, machines, devices, and systems used in a production or logistics process in a physical location. Tulip is democratizing technology and is empowering those closest to operations to solve problems. Tulip is also hiring. You can find Tulip at tulip.co. Please share this show with colleagues who care about where industry and especially where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube. Augmented — industrial conversations that matter. See you next time. Special Guest: Jay Lee.

Calvary Baptist Church
9/18/22 - Troubled by Tulip - The Glorious Truth of God's Salvation - ”Guilty by Choice” - Week 1

Calvary Baptist Church

Play Episode Listen Later Sep 20, 2022 41:14


Gardening with Ben
Visit to Sheffiel Pollen Market and what we have purchased today

Gardening with Ben

Play Episode Listen Later Sep 18, 2022 13:34


Welcome to Gardening With Ben in today's gardening podcast episode we talk about our visit to Sheffield Pollen Market and what happens at the plant market. Find out what Gardening with Ben has purchased as well from Pollen Market in Sheffield______________________________________Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

Gardening with Ben
Visit to Sheffiel Pollen Market and what we have purchased today

Gardening with Ben

Play Episode Listen Later Sep 18, 2022 13:34


Welcome to Gardening With Ben in today's gardening podcast episode we talk about our visit to Sheffield Pollen Market and what happens at the plant market. Find out what Gardening with Ben has purchased as well from Pollen Market in Sheffield______________________________________Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

The Growing Season
The Growing Season, Sept. 17, 2022 - Fall Bulbs

The Growing Season

Play Episode Listen Later Sep 17, 2022 53:40


They're the last gasp of planting.  They're one of the first gasps of colour in the spring.Fall bulbs - a sure fire way to irritate Matt McFarland.Jack, Lynne and their aforementioned son steer The Growing Season into the waters of all that is bulbous.  Tulips, hyacinths, muscari, daffodils, snow drops and many more are chatted about.  How deep do you plant them?  WHEN should you be plating them and is weather a factor in the timeframe to plant?Matt updates you on the goings on of Cole the cat.   Tune in! Looking to book a consult for your property?  We'd love to help.  CLICK HERE.What is a TGS Tiny Garden? CLICK HERE. Subscribe to The Growing Season podcast.  CLICK HERE. 

Gardening with Ben
What have we been buying for the allotment garden today

Gardening with Ben

Play Episode Listen Later Sep 16, 2022 14:14


Join Gardening with Ben as he talks about all the things he has been purchasing for the allotment garden today in preparation for Spring in the garden and looking after the bees on his allotment garden.______________________________________Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

Gardening with Ben
What have we been buying for the allotment garden today

Gardening with Ben

Play Episode Listen Later Sep 16, 2022 14:14


Join Gardening with Ben as he talks about all the things he has been purchasing for the allotment garden today in preparation for Spring in the garden and looking after the bees on his allotment garden.______________________________________Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

Dig It - Discussions on Gardening Topics
Container Gardening with Kathy Brown

Dig It - Discussions on Gardening Topics

Play Episode Listen Later Sep 15, 2022 59:43


For the past 33 years Kathy and her husband Simon have created a simply amazing Manor House Garden in Stevington, just north of Bedford. It's a garden full of inspiration, buoyed by Kathy's keen use of colour and structure as well as plenty of great plants. In this episode of Dig it, Peter Brown and Chris Day discover more about how the garden evolved, advice on growing plants in containers using recipe-style plantings, the crocking debate, tales of a donkey, opening a garden to the public and using edible flowers in baking.Plants mentioned: Beech hedging, Eucalyptus, Pine trees, avenues of Betula jacquemontii, Metasequoia glyptostroboides and Ginkgo biloba. Wisteria, Weeping Cedrus, xeriscape plants such as succulents. Perennials Agapanthus, Alliums, Japanese anemones, Gladiolus callianthus 'Murielae' (Abyssinian gladiolus, RHS AGM), Sedum, Hellebore Gold Collection (outward facing blooms perfect in pots) Helleborus ‘Frosty' is a good one, Verbena bonariensis, ornamental grasses including Calamagrostis ‘Overdam', Echinaceas. Hyacinths, Dwarf and species Tulips, Tulip clusiana 'Lady Jane' and Dwarf Narcissi like ‘January Gold' (early) and ‘Pipit' (later flowering). Good flavours to use with cake bakes include scented rose petals as these provide the most flavour as well as lavender.Kathy's desert island plant: English lavender – wonderfully versatile, you can cook with it and use it in a wide variety of ways as well as producing a wonderful tea to enjoy.Products mentioned: White Himalayan birch plantings at Anglesey Abbey. National Garden Scheme (NGS). Solardome ® greenhouse. Beth Chatto's dry garden – a converted car park to a gravel garden. Piet Oudolf, a Dutch garden designer, plant nursery man and author who practices a more naturalistic approach to gardening. Composts: Dalefoot Wool Compost and Jack's Magic All Purpose Improved Compost (reduced peat) and New Horizon Peat-Free Compost. Broadleaf p4, using John Innes Compost as an additive. Kathy likes to use Evergreen Compost , who offer peat-free, peat-reduced and a traditional compost containing sphagnum moss peat. Water retaining granules such as Broadleaf P4 and Swelgel, which can be added to compost and soil to help retain moisture around the plant's roots. Garden photographer Clive Nichols and the early morning photo shoot.Kathy Brown's Books The Edible Flower Garden, Container Gardening, Kathy Brown's Recipes For Easy Container Gardening and A Bulb for all SeasonsTo find out more about Kathy's Garden, opening details, Kathy's lectures and how to book a visit click hereOur thanks to Chiltern Music Therapy for providing the music. Hosted on Acast. See acast.com/privacy for more information.

Gardening with Ben
We need to start thinking about Spring in the Allotment Garden

Gardening with Ben

Play Episode Listen Later Sep 14, 2022 13:09


Welcome to Gardening with Ben's Podcast In today's episode Gardening with Ben talks about why we need to be starting to think about Spring in the allotment garden and why we should be planting spring bulbs including daffodils, tulips, crocuses, and hyacinths.Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

Childz Play
Kidz Bop Leftovers - Dawn of the Tulip Meister

Childz Play

Play Episode Listen Later Sep 14, 2022 63:45


Let's...let's just sit down and knock a few of the stragglers out, shall we? The end is night. So, we're gonna chill for a hot sec.  Alex cries out for a lover.  Adam does math.  Hey!!! We have a Ko-fi link if you wanna just toss us a few bucks! https://ko-fi.com/childzplay or Support Our Show on Patreon Please!! If you have a second, fill out this very short survey to help us define our demographic for potential advertisers. We haven't mentioned it in a while, but it would be truly awesome of you. Also, bonus points for reading this far in the show notes.  Check out our partner shows on the Missing Sock Network! And follow the Network on Instagram too. Follow Childz Play on Instagram and Twitter, and follow R. Alex Murray right now! Check Out our Merch and Keep On Boppin!

Gardening with Ben
We need to start thinking about Spring in the Allotment Garden

Gardening with Ben

Play Episode Listen Later Sep 14, 2022 13:09


Welcome to Gardening with Ben's Podcast In today's episode Gardening with Ben talks about why we need to be starting to think about Spring in the allotment garden and why we should be planting spring bulbs including daffodils, tulips, crocuses, and hyacinths.Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

Inside Crypto
Expanded Coding Support,  Concentrated Liquidity and Security Audits

Inside Crypto

Play Episode Listen Later Sep 12, 2022 22:37


Hey Solanians….. How are you? The merge has had an effect on pretty much everything including Solana... This is the tenth episode  of our SOLI focused segment of the Inside Crypto podcast. In this series we plan to cover the latest news regarding the constituents of our Solana Ecosystem Index. They are Serum, mSOL and MNDE, Raydium, Orca, Solend, UXP, Mango, Tulip and Aldrin. This episode was recorded on September 12th 2022.  The first thing we will always dive into, is the price action of the week and then go through any major news items with regards to the constituents.... Today we discuss how instant liquid unstaking is changing the game and recap Solend in August…this and many more stories on today's episode. I have to mention that nothing in this episode constitutes financial advice. Please do your own research. Anything said here is my own opinion and not to be connected with my employer. But I am forever grateful to them for helping make this podcast a reality so please do check out our website and tokens we offer at tokens.amun.com. Thanks everyone for listening and don't forget to tune in next week where we help you to get to grips with what is going on in the Solana Ecosystem.  News Covered Today: https://tokens.amun.com/token/SOLI (SOLI Price Action) https://defillama.com/chain/Solana (Solana TVL - DefiLlama) https://www.bitcoinmarketjournal.com/top-projects-building-on-solana/ (Top Projects Building on Solana in 2022 - Bitcoin Market Journal) https://twitter.com/MarinadeFinance/status/1567903148685070336?s=20&t=LDgNw7By-OOtd6BC8JFxPw (Marinade Instant Unstaking) https://twitter.com/MarinadeFinance/status/1568305789194113024?s=20&t=LDgNw7By-OOtd6BC8JFxPw (Marinade Gauge Summary) https://twitter.com/solana_daily/status/1567479166865494025?s=20&t=LDgNw7By-OOtd6BC8JFxPw (Raydium Holders) https://blog.solend.fi/august-in-review-6b310225e6ad (Solend August 2022 Review) https://medium.com/orca-so/announcing-wave-1-of-the-whirlpools-builders-program-3a2df8a6147b (Announcing Wave 1 of the Whirlpools Builders Program! | by Orca | Orca | Sep, 2022 | Medium) https://twitter.com/CredoraPlatform/status/1568223585378107392?s=20&t=LDgNw7By-OOtd6BC8JFxPw (UXD and Credora Partnership) https://twitter.com/TulipProtocol/status/1567589010737971201?s=20&t=LDgNw7By-OOtd6BC8JFxPw (Meet Tulip in Canada) https://twitter.com/mangomarkets/status/1565589073766584320?s=20&t=eNCATn8KbksS2AQFrQbJcQ (Mango Security Audit) https://twitter.com/Aldrin_Exchange/status/1565670883225640961?s=20&t=eNCATn8KbksS2AQFrQbJcQ (Aldrin Recap) Follow Us On: http://www.amun.com (Website) https://twitter.com/Amun (Twitter) https://discord.gg/EDufcYpseD (Discord) https://t.me/AmunTokens (Telegram) (English) https://www.reddit.com/r/AmunTokens/ (Reddit) Email

Audio Sermons – Ebenezer Primitive Baptist Church

After some lingering technical difficulties, our podcast is back! Enjoy this message from Paul’s second epistle to the Thessalonians.

Gardening with Ben
Catch up with Award Winning Gardening With Ben

Gardening with Ben

Play Episode Listen Later Sep 11, 2022 19:40


Catch up with Gardening With Ben's Podcast to see what he has been doing and hear about him winning the Gardening Awards this year. Also, find out what Spring bulbs he has been purchasing recently. _____________________________________________-Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out our main Gardening With Ben Podcast channel here:- https://open.spotify.com/show/1ZK8sbHqPAPXjDxwIFs94a?si=f5389ea4f5184841

Gardening with Ben
Catch up with Award Winning Gardening With Ben

Gardening with Ben

Play Episode Listen Later Sep 11, 2022 19:40


Catch up with Gardening With Ben's Podcast to see what he has been doing and hear about him winning the Gardening Awards this year. Also, find out what Spring bulbs he has been purchasing recently. _____________________________________________-Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out our main Gardening With Ben Podcast channel here:- https://open.spotify.com/show/1ZK8sbHqPAPXjDxwIFs94a?si=f5389ea4f5184841

StoryNerds
Episode 88: Recent CCR Reads

StoryNerds

Play Episode Listen Later Sep 9, 2022 40:09


Join Narelle, Valerie, and Elizabeth as they talk about CCR they've been reading lately. Books discussed include: To Win a Prince by Toni Shiloh To Begin Again by Emily Conrad The Billionaire's Nanny by Elizabeth Maddrey The Trouble with Tulips by Emily Dana Boutrous A Wide and Pleasant Place by Valerie Comer Potential Threat by Tara Grace Ericson

Augmented - the industry 4.0 podcast
Episode 96: The People Side of Lean

Augmented - the industry 4.0 podcast

Play Episode Listen Later Sep 7, 2022 49:37


Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. The topic is "The People Side of Lean." Our guest is Jeffrey Liker, academic, consultant, and best-selling author of The Toyota Way (https://www.amazon.com/Toyota-Way-Management-Principles-Manufacturer/dp/B09BDC3525/ref=sr_1_1?crid=2JABTVWQBAZC8&keywords=the+toyota+way&qid=1661872838&sprefix=the+toyot%2Caps%2C107&sr=8-1). In this conversation, we talk about how to develop internal organizational capability and problem-solving skills on the frontline. If you liked this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 84 on The Evolution of Lean (https://www.augmentedpodcast.co/84). Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim (https://trondundheim.com/) and presented by Tulip (https://tulip.co/). Follow the podcast on Twitter (https://twitter.com/AugmentedPod) or LinkedIn (https://www.linkedin.com/company/75424477/). Trond's Takeaway: Lean is about motivating people to succeed in an industrial organization more than it is about a bundle of techniques to avoid waste on a factory production line. The goal is to have workers always asking themselves if there is a better way. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is the People Side of Lean. Our guest is Jeffrey Liker, academic, consultant, and best-selling author of The Toyota Way. In this conversation, we talk about how to develop internal organizational capability, problem-solving skills on the frontline. Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip. Jeffrey, how are you? Welcome to the podcast. JEFFREY: Thank you. TROND: So I think some people in this audience will have read your book or have heard of your book and your books but especially the one that I mentioned, Toyota. So I think we'll talk about that a little bit. But you started out as an engineering undergrad at Northeastern, and you got yourself a Ph.D. in sociology. And then I've been reading up on you and listening to some of the stuff on the musical side of things. I think we both are guitarists. JEFFREY: Oh, is that right? TROND: Yeah, yeah, classical guitar in my case. So I was wondering about that. JEFFREY: So I play also a classical guitar now. I played folk and rock earlier when I was young. But for the last more than ten years, I've been only studying classical guitar. TROND: Well, so then we share a bunch of hours practicing the etude, so Fernando Sor, and eventually getting to the Villa-Lobos stuff. So the reason I bring that up, of course, beyond it's wonderful to talk about this kind of stuff with, you know, there aren't that many classical guitarists out there. But you said something that I thought maybe you could comment on later. But this idea of what happened to you during your studies of classical guitar actually plays into what you later brought into your professional life in terms of teaching you something about practicing in particular ways. So I hope you can get into that. But obviously, you've then become a professor. You are a speaker and an advisor, and an author of this bestseller, The Toyota Way. Now you run some consulting. And I guess I'm curious; this was a very, very brief attempt at summarizing where you got into this. What was it that brought you into manufacturing in the first place? I mean, surely, it wasn't just classical guitar because that's not a linear path. [laughs] JEFFREY: No. So for undergraduate, I had basically studied industrial engineering because I didn't really know what I wanted to do with my life. And my father was an engineer. And then I literally took a course catalog and just started reading the descriptions of different kinds of engineering. And industrial engineering was the only one that mentioned people. And in theory, industrial engineering is a systems perspective which integrates people, materials, methods, machines, the four Ms. And in the description from Northeastern University, they said it's as much about human organization as it is about tools and techniques. So that appealed to me. When I got to Northeastern...I was not a particularly good high school student. So I didn't have a lot of choices of what colleges I went to, so Northeastern was pretty easy to get into. But they had a cooperative education program where you go to school, and you work. You go back and forth between school and work and had a pretty elaborate system for setting you up with jobs. I got one of the better jobs, which was at a company called General Foods Corporation at the time, and they make things like Jell-O, and Gravy Train dog food, and Birds Eye vegetables, and a lot of other household names, Kool-Aid, all automated processes, even at that time in the 1970s. And they had been experimenting with something called socio-technical systems, which is supposed to be what I was interested in, which is bringing together the social and technical, which no one at Northeastern University had any interest in except me. But I was very interested in this dog food plant where they were written up as a case study pioneer. And the basic essence of it was to give groups of people who are responsible, for example, for some automated processes to make a certain line of Gravy Train dog food, give them responsibility for all their processes, and they called them autonomous workgroups. And what we try to do is as much as possible, give them all the responsibility so they can work autonomously without having to go and find the engineer or deal with other support functions, which takes time and is kind of a waste. So that fascinated me. I studied it. I wrote papers about it even in courses where it didn't fit. But the closest I could get to the social side was through sociology courses which I took as soon as I was able to take electives, which was about my third year. And I got to know a sociology professor closely and ultimately decided to get a Ph.D. in sociology and did that successfully, published papers in sociology journals at a pretty high level. And then discovered it was really hard to get a job. TROND: Right. [laughs] JEFFREY: And there happened to be an advertisement from an industrial engineering department at University of Michigan for someone with a Ph.D. in a social science and an undergraduate degree in industrial engineering. And I was probably the only person in the world that fit the job. And they were so excited to hear from me because they had almost given up. And I ended up getting that job quickly then getting to Michigan excited because it's a great university. I had a low teaching load. They paid more than sociology departments. So it was like a dream job. Except once I got there, I realized that I had no idea what I was supposed to be doing [chuckles] because it wasn't a sociology department. And I had gotten away from industry. In fact, I was studying family development and life's course development, and more personal psychology and sociology stuff. So I was as far away as I could be. So I had to kind of figure out what to do next. And fortunately, being at Michigan and also being unique, a lot of people contacted me and wanted me to be part of their projects. And one of them was a U.S.-Japan auto study comparing the U.S.-Japan auto industry going at the same time as a study at MIT and Harvard that ultimately led to the book The Machine That Changed the World, which defined lean manufacturing. So this was sort of a competitive program. And they asked me to be part of it, and that's what led to my learning about Toyota. I mean, I studied Toyota, Nissan, Mazda mainly and compared them to GM, Ford, and Chrysler. But it was clear that Toyota was different and special. And ultimately, then I learned about the Toyota Production System. And from my perspective, not from people in Toyota, but from my perspective, what they had done is really solve the problem of socio-technical systems. Because what I was seeing at General Foods was workers who were responsible for technical process and then were given autonomy to run the process, but there was nothing really socio-technical about it. There was a technical system, and then there was social system autonomous work groups and not particularly connected in a certain way. But the Toyota Production System truly was a system that was designed to integrate people with the technical system, which included things like stamping, and welding, and painting, which were fairly automated as well as assembly, which is purely manual. And Toyota had developed this back in the 1940s when it was a lone company and then continued to evolve it. And the main pillars are just-in-time and built-in quality. They have a house, and then the foundation is stable and standardized processes. And in the center are people who are continuously improving. Now, the socio-technical part the connection is that just-in-time for Toyota means that we're trying to flow value to the customer without interruption. So if what they do is turn raw materials into cars that you drive, then anything that's turning material into a component or car physically is value-added, and everything else is waste. And so things like defects where you have to do rework are waste. And machines are shut down, so we have to wait for the machines to get fixed; that's waste. And inventory sitting in piles doing nothing is waste. So the opposite of waste is a perfect process. And Toyota also was smart enough, and all that they figured out was more like folk learning or craft learning. It was learning from doing and experience and common sense. And they didn't particularly care about linking it to academic theories or learning from academic theories, for that matter. So their common sense view is that the world is complicated. Humans are really bad at predicting the future. So the best we can do is to get in the ballpark with what we think is a good process and then run it and see how it fails. And then the failures are what lead to then the connection of people who have to solve the problems through creative thinking. So that was the integration that I did not see before that. TROND: Just one thing that strikes me...because nowadays, comparing the U.S. or Europe and Asia in terms of business practices, it's sort of like, oh, of course, you have to compare them because they are culturally different. But it strikes me that in the automotive industry, was it immediately really clear to you at the outset that there would be such striking differences between the Japanese and the U.S. auto industry? Or is that actually something that had to be studied? Or was it something that was known, but no one really knew exactly what the differences were? JEFFREY: So it wasn't like the American auto companies figured out that if they get good at using chopsticks, they'll be good at making cars. They weren't looking for something peculiar in Japanese culture. But they were addressing the more general problem, which was that Japanese companies were making small fuel-efficient cars at low cost with high quality. And none of the American companies could do that. The costs were higher. The quality was terrible compared to Japan. They took a long time to do everything, including developing cars. So somehow, the Japanese were purported, they weren't convinced this was true, but according to the evidence, the Japanese were purported to be better at just about everything. And the Americans wanted to know why particularly. And at that time, there had been an oil crisis, and there was a demand for small cars. The real question they were interested in is how could they make small cars that were competitive with the Japanese? So they had to understand what the Japanese were doing. Now, they realized that some of what the Japanese were doing were purely technical things that had nothing to do with culture. And then there was also a level of attention to detail and motivation that maybe was, for some reason, peculiar to Japan. But they needed to figure out how to replicate it in the United States. And then, in addition to that, they had Americans like Dr. Deming, who had gone to Japan and taught the Japanese supposedly quality control methods. And Japanese companies had taken quality control methods that were created in the United States more seriously than the American companies. So part of it was relearning what came from America to Japan and got done better. So it wasn't necessarily this kind of strange place, and how can we emulate this strange culture? TROND: Right. But that becomes then your challenge then, right? Because what you then discover is that your field is immensely important to this because what you then went on to do is...and I guess part of your consulting work has been developing internal organizational capability. These are skills that particular organizations, namely Toyota, had in Japan. So you're thinking that this then became...it's like a learning process, the Japanese learned some lessons, and then the whole rest of the automotive industry then they were trying to relearn those lessons. Is that sort of what has been happening then in the 30 years after that? JEFFREY: Yeah, the basic question was, why are they so good? Why are we so bad? And how can we get better in America? Then there were lots of answers to that question coming from different people in different places. My particular answer was that Toyota especially had developed a socio-technical system that was extremely effective, that was centered on people who were developed to have the skills of problem-solving and continuous improvement. And while the study was going on, they were doing a study out of MIT that led to The Machine That Changed the World. And around that same time, a joint venture between Toyota and General Motors had been formed called NUMMI. It was in California. And in their first year, it was launched in 1983, and in the first year, they had taken what was the worst General Motors plant in the world, with the worst attendance, the worst morale, workers who were fighting against supervisors every day, including physically fighting with them, terrible quality, and General Motors had closed the plant because it was so bad. And then, in the joint venture, they reopened the plant and took back 80% of the same workers who were like the worst of the worst of American workers. And within a year, Toyota had turned the plant around so that it was the best in North America with the best workers. TROND: That's crazy, right? Because wouldn't some of the research thesis in either your study or in the MIT study, The Machine That Changed the World, would have to have been around technology or at least some sort of ingenious plan that these people had, you know, some secret sauce that someone had? Would you say that these two research teams were surprised at finding that the people was the key to the difference here or motivating people in a different way? JEFFREY: Well, frankly, I think I probably had a better grasp that people were really the key than most other researchers because of my background and my interest in human-centered manufacturing. So I was kind of looking for that. And it was what the Toyota people would say...whenever they made a presentation or whenever you interviewed them, they would say, "People are kind of distracted by the tools and methods, but really at the center are people." And generally, most people listening to them didn't believe it, or it didn't register. Because Toyota did have cool stuff, like, for example, something called a kanban system, which is how do you move material around in the factory? They have thousands of parts that have to all be moved and orchestrated in complicated ways. And Toyota did it with physical cards. And the concept was a pulse system that the worker; when they see that they're getting low on parts, they take a card and they post it. They put it in a box, and then the material handler picks it up. And they said, okay, they need another bin of these. On my next route, I'll bring a bin of whatever cards I get. So they were replenishing the line based on a signal from the operator saying, "I need more." So it was a signal from the person who knows best what they need. And it also, from Toyota's point of view, put the employee in the driver's seat because now they're controlling their supply in addition to controlling their work process. And it didn't require that you predict the future all the time because who knows what is happening on the line and where they're backed up, and where they maybe have too many parts, and they don't need more? But the worker knows. He knows when he needs it and when he doesn't. It was kind of an ingenious system, but the fact that you had these cards moving all over the factory and thousands of parts are moving just to the right place at the right time based on these cards, that was fascinating. So a lot of the consumers were more interested in that than they were in the people aspect, even though Toyota kept talking about the people aspect. TROND: But so this is my question, then there was more than one element that they were doing right. JEFFREY: There were multiple elements, yeah. TROND: There were multiple elements. Some of them were structural or visual, famously. JEFFREY: Right. TROND: But you then started focusing, I guess, on not just the people aspect, but you started structuring that thinking because the obvious question must have been, how can we do some of this ourselves? And I guess that's my question is once you and the team started figuring out okay, there are some systematic differences here in the way they motivate people, handle the teams, but also structure, honestly, the organizational incentives minute by minute, how then did you think about transferring this? Or were you, at this point, just really concerned about describing it? JEFFREY: Like I said, I was kind of unusual in my background, being somewhere between industrial engineering and sociology and being in industrial engineering departments. So maybe I wasn't as constrained by some of the constraints of my academic colleagues. But I never believed this whole model that the university gathers information structures that formulates it, then tells the world what to do. I never thought that made any sense. And certainly, in the case of lean, it didn't, and it wasn't true. So the way that companies were learning about this stuff was from consultants, largely, and from people who had worked for Toyota. So anybody who had worked for Toyota, even if they were driving a forklift truck, in some cases, suddenly became a hot commodity. I consulted to Ford, and they were developing the Ford Production System. They were using a consulting firm, and all their consulting firm's business was to poach people from Toyota and then sell them as consultants to other companies. And that company literally had people every day of the week who were in their cars outside the gates of Toyota. And as people came out, they would start talking to them to try to find people that they could hire away from Toyota. TROND: It's funny to hear you talking about that, Jeff, right? Because in some way, you, of all people, you're a little bit to blame for the fame of Toyota in that sense. I mean, you've sold a million books with The New Toyota -- JEFFREY: Well, that was -- TROND: I'm just saying it's a phenomenon here that people obsess over a company, but you were part of creating this movement and this enormous interest in this. [laughs] JEFFREY: I didn't feel that that was...I personally had a policy because I had a consulting company too. So I personally had a policy that I would not hire somebody away from Toyota unless they were leaving anyway. That was my personal policy. But the important point was that there were a lot of really well-trained people coming out of Toyota who really understood the whole system and had lived it. And they could go to any other company and do magic, and suddenly things got better. [laughs] And what they were doing was setting up the structures and the tools, and they also were engaging the people and coaching the people. They were doing both simultaneously, and that's how they were trained. Toyota had sent an army of Japanese people to America. So every person who was in a leadership position had a one-on-one coach for years, a person whose only reason for being in the United States was to train them. So they got excellent training, and then they were able to use that training. And then other people once they had worked with a company and then that company got good at lean, then, within that company, you'd spawn more consultants change agents. Like, there was a company that I was studying called Donnelly Mirrors that made exterior mirrors for cars. And one of the persons that was trained by a Toyota person became a plant manager. And he ended up then getting offered a job as the vice president of manufacturing for Merillat Kitchen Cabinets. And now he's the CEO of the parent company that owns Merillat. And he's transformed the entire company. So little by little, this capability developed where most big companies in the world have hired people with lean experience. Sometimes it's second generation, sometimes third generation. And there are some very well-trained people. So the capability still resides within the people. And if you have someone who doesn't understand the system but they just set up a kanban system or they set up quality systems, and they try to imitate what they read in a book or what they learned in a course; usually, it doesn't work very well. TROND: Well, that was going to be my next question. Because how scalable is this beyond the initial learnings of Toyota and the fact that it has relied so heavily on consulting? Because there is sort of an alternate discourse in a lot of organizational thinking these days that says, well, not just that the people are the key to it but actually, that as a leader, however much you know or how aware you are of people processes, it is the organization itself that kind of has to find the answers. So there's perhaps some skepticism that you can come in and change a culture. Aren't there organizations that have such strong organizational practices, whether they are cultural in some meaningful way or they're simply this is the way they've done things that even one person who comes in has a hard time applying a Toyota method? What do you think about that kind of challenge? JEFFREY: Okay, so, anyway, I think what you said is...how I would interpret it is it's a gross oversimplification of reality. So first of all, in the second edition of The Toyota Way, because I realized from the first edition, which was fairly early back in the early 2000s, I realized that some people were taking my message as copy Toyota, even though I didn't say that in the book. And I specifically said not to do that, but I said it in the last chapter. So I put out the second edition a year ago, and I say it in the first page or first few pages. I say, "Don't copy Toyota," and explain why. And then, throughout the book, I say that, and then, in the end, I say, "Develop your own system." So it's probably repeated a dozen times or more with the hope that maybe somebody would then not ask me after reading it, "So, are we supposed to copy Toyota?" So the reason for that is because, as you said, you have your own culture. And you're in a different situation. You're in a different industry. You're starting in a different place. You're drawing on different labor. You have maybe plants around the world that are in different situations. So the other thing I said in the book, which is kind of interesting and counterintuitive, is I said, "Don't copy Toyota; even Toyota doesn't copy Toyota." TROND: So what does that mean? Did they really not? JEFFREY: What it means is that...because Toyota had this dilemma that they had developed this wonderful system in Japan that worked great, but they realized that in auto, you need to be global to survive. So when they set up NUMMI, that was the first experiment they did to try to bring their system to a different culture. And in reality, if you look at some of the cultural dimensions that make lean work in Japan, the U.S. is almost opposite on every one of them, like, we're the worst case. So if you were a scientist and you said, let's find the hardest place in the world to make this work and see if we can make it work, it would be the United States, particularly with General Motors workers already disaffected and turned off. So Toyota's perspective was, let's go in with a blank sheet of paper and pretend we know nothing. We know what the total production system is and what we're trying to achieve with it. But beyond that, we don't know anything about the human resource system and how to set it up. And so they hired Americans, and they coached them. But they relied a lot on Americans, including bringing back the union leader of the most militant union in America. They brought him back. TROND: Wow. JEFFREY: And said, "You're a leader for a reason. They chose you. We need your help. We're going to teach you about our system, but you need to help make it work." So that created this sort of new thing, a new organizational entity in California. And then what Toyota learned from that was not a new solution that they then brought to every other plant, whether it was Czechoslovakia, or England, or China. But rather, they realized we need to evolve a cultural system every time we set up a plant, starting with the local culture. And we need to get good at doing that, and they got good at doing it. So they have, I don't know, how many plants but over 100 plants around the world and in every culture you can imagine. And every one of them becomes the benchmark for that country as one of their best plants. And people come and visit it and are amazed by what they see. The basic principles are what I try to explain in The Toyota Way. The principles don't change. At some level, the principle is we need continuous improvement because we never know how things are going to fail until they fail. So we need to be responding to these problems as a curse. We need people at every level well trained at problem-solving. And to get people to take on that additional responsibility, we need to treat people with a high level of respect. So their model, The Toyota Way, was simply respect for people and continuous improvement. And that won't change no matter where they go. And their concept of how to teach problem-solving doesn't change. And then their vision of just-in-time one-piece flow that doesn't change, and their vision of building in quality so that you don't allow outflows of poor quality beyond your workstation that doesn't change. So there are some fundamental principles that don't change, but how exactly they are brought into the plant and what the human resource system looks like, there'll be sort of an amalgam between the Japanese model and the local model. But they, as quickly as possible, try to give local autonomy to people from that culture to become the plant managers, to become the leaders. And they develop those people; often, those people will go to Japan for periods of time. TROND: So, Jeff, I want to move to...well, you say a lot of things with Toyota don't change because they adapt locally. So my next question is going to be about future outlook. But before we get there, can we pick up on this classical guitar lesson? So you were playing classical guitar. And there was something there that, at least you said that in one interview that I picked up on, something to do with the way that guitar study is meticulous practice, which both you and I know it is. You literally will sit plucking a string sometimes to hear the sound of that string. I believe that was the example. So can you explain that again? Because, I don't know, maybe it was just me, but it resonated with me. And then you brought it back to how you actually best teach this stuff. Because you were so elaborate, but also you rolled off your tongue all these best practices of Toyota. And unless you either took your course or you are already literate in Toyota, no one can remember all these things, even though it's like six different lessons from Toyota or 14 in your book. It is a lot. But on the other hand, when you are a worker, and you're super busy with your manager or just in the line here and you're trying to pick up on all these things, you discovered with a colleague, I guess, who was building on some of your work some ways that had something in common with how you best practice classical guitar. What is that all about? JEFFREY: Well, so, first of all, like I said, the core skill that Toyota believes every person working for Toyota should have is what they call problem-solving. And that's the ability to, when they see a problem, to study what's really happening. Why is this problem occurring? And then try out ideas to close the gap between what should be happening and what is happening. And you can view that as running experiments. So the scientific mindset is one of I don't know. I need to collect the data and get the evidence. And also, I don't know if my idea works until I test it and look at what happens and study what happens. So that was very much central in Toyota. And they also would talk about on-the-job development, and they were very skeptical of any classroom teaching or any conceptual, theoretical explanations. So the way you would learn something is you'd go to the shop floor and do it with a supervisor. So the first lesson was to stand in a circle and just observe without preconceptions, kind of like playing one-string guitar. And the instructor would not tell you anything about what you should be looking for. But they would just ask you questions to try to dig deeper into what's really going on with the problems or why the problems are occurring. And the lesson length with guitar, you might be sweating after 20 minutes of intense practice. This lesson length was eight hours. So for eight hours, you're just on the shop floor taking breaks for lunch and to go to the bathroom and in the same place just watching. So that was just an introductory lesson to open your mind to be able to see what's really happening. And then they would give you a task to, say, double the productivity of an area. And you would keep on trying. They would keep on asking questions, and eventually, you would achieve it. So this on-the-job development was learning by doing. Now, later, I came to understand that the culture of Japan never really went beyond the craftsman era of the master-apprentice relationship. That's very central throughout Japan, whether you're making dolls, or you're wrapping gifts, or you're in a factory making a car. So the master-apprentice relationship system is similar to you having a guitar teacher. And then, if you start to look at modern psychology leadership books, popular leadership books, there's a fascination these days with the idea of habits, how people form habits and the role of habits in our lives. So one of my former students, Mike Rother, who had become a lean practitioner, we had worked together at Ford, for example, and was very good at introducing the tools of lean and transforming a plant. He started to observe time after time that they do great work. He would check in a few months later, and everything they had done had fallen apart and wasn't being followed anymore. And his ultimate conclusion was that what they were missing was the habit of scientific thinking that Toyota put so much effort into. But he realized that it would be a bad solution to, say, find a Toyota culture -- TROND: Right. And go study scientific thinking. Yeah, exactly. JEFFREY: Right. So he developed his own way in companies he was working with who let him experiment. He developed his own way of coaching people and developing coaches inside the company. And his ultimate vision was that every manager becomes a coach. They're a learner first, and they learn scientific thinking, then they coach others, which is what Toyota does. But he needed more structure than Toyota had because the Toyota leaders just kind of learned this over the last 25 years working in the company. And he started to create this structure of practice routines, like drills we would have in guitar. And he also had studied mastery. There's a lot of research about how do you master any complex skill, and it was 10,000 hours of practice and that idea. But what he discovered was that the key was deliberate practice, where you always know what you should be doing and comparing it to what you are doing, and then trying to close the gap. And that's what a good instructor will do is ask you to play this piece, realize that you're weak in certain areas, and then give you an exercise. And then you practice for a week and come back, and he listens again to decide whether you've mastered or not or whether he needs to go back, or we can move to the next step. So whatever complex skill you're learning, whether it's guitar, playing a sport, or learning how to cook, a good teacher will break down the skill into small pieces. And then, you will practice those pieces until you get them right. And the teacher will judge whether you got them right or not. And then when you're ready, then you move on. And then, as you collect these skills, you start to learn to make nice music that sounds good. So it turns out that Mike was developing this stuff when he came across a book on the martial arts. And they use the term kata, which is used in Japanese martial arts for these small practice routines, what you do repeatedly exactly as the master shows you. And the master won't let you move on until you've mastered that one kata. Then they'll move to the second kata and then third. And if you ask somebody in karate, "How many katas do you have?" They might say, "46," and you say, "Wow, you're really good. You've mastered 46 kata, like playing up through the 35th Sor exercise. So he developed what he called the improvement kata, which is here is how you practice scientific thinking, breaking it down into pieces, practicing each piece, and then a coaching kata for what the coach does to coach the student. And the purpose of the scientific thinking is not to publish a paper in a journal but to achieve a life goal, which could be something at work, or it could be that I want to lose weight. It could be a personal goal, or I want to get a new job that pays more and is a better job. And it becomes an exploration process of setting the goal. And then breaking down the goal into little pieces and then taking a step every day continuously toward, say, a weekly target and then setting the next week's target, and next week's target and you work your way up the mountain toward the goal. So that became known as Toyota Kata. He wrote a book called Toyota Kata. And then, I put into my model in the new Toyota Way; in the center of the model, I put scientific thinking. And I said this is really the heart and soul of The Toyota Way. And you can get this but only by going back to school, but not school where you listen to lectures but school where you have to do something, and then you're getting coached by someone who knows what they're doing, who knows how to be a coach. TROND: So my question following this, I think, will be interesting to you, or hopefully, because we've sort of gone through our conversation a little bit this way without jumping to the next step too quickly. Because the last question that I really have for you is, what are the implications of all of this? You have studied, you know, Toyota over years and then teaching academically, and in industry, you've taught these lessons. But what are the implications for the future development of, I guess, management practice in organizations, in manufacturing? Given all that you just said and what you've previously iterated about Toyota's ideas that not a lot of things change or necessarily have to change, how then should leaders go about thinking about the future? And I'm going to put in a couple of more things there into the future. I mean, even just the role of digital, the role of technology, the role of automation, all of these things, that it's not like they are the future, but they are, I guess, they are things that have started to change. And there are expectations that might have been brought into the company that these are new, very, very efficient improvement tools. But given everything that you just said about katas and the importance of practicing, how do you think and how do you teach preparing for the future of manufacturing? JEFFREY: And I have been working with a variety of companies that have developed what you might call industry 4.0 technologies, digital technologies, and I teach classes where a lot of the students are executives from companies where in some cases, they have a dual role of lean plus digitalization. So they're right at the center of these two things. And what I learned going back to my undergraduate industrial engineering days and then to my journey with Toyota, I was always interested in the centrality of people, whatever the tools are. And what I was seeing as an undergraduate was that most of the professors who were industrial engineers really didn't have much of a concept of people. They were just looking at techniques for improving efficiency as if the techniques had the power themselves. And what I discovered with people in IT, and software development, and the digital movement is often they don't seem to have a conception of people. And people from their point of view are basically bad robots [laughs] that don't do what they're supposed to do repeatedly. So the ultimate view of some of the technologists who are interested in industry 4.0 is to eliminate the people as much as possible and eliminate human judgment by, for example, putting it into artificial intelligence and having the decisions made by computers. I'm totally convinced from lots of different experiences with lots of different companies that the AI is extremely powerful and it's a breakthrough, but it's very weak compared to the human brain. And what the AI can do is to make some routine decisions, which frees up the person to deal with the bigger problems that aren't routine and can also provide useful data and even some insight that can help the person in improving the process. So I still see people as the ultimate customer for the insights that come out of this digital stuff, Internet of Things, and all that. But in some cases, they can control a machine tool and make an automatic adjustment without any human intervention, but then the machine breaks down. And then the human has to come in and solve the problem. So if you're thinking about digitalization as tools to...and sometimes have a closed loop control system without the person involved. But in addition, maybe, more importantly, to provide useful data to the human, suddenly, you have to think about the human and what makes us tick and what we respond to. And for example, it's very clear that we're much better at taking in visual information than text information. And that's one of the things that is part of the Toyota Production System is visual management. So how can you make the results of what the AI system come up with very clear and simple, and visual so people can respond quickly to the problem? And most of these systems are really not very good. The human user interface is not well designed because they're not starting with the person. And the other thing is that there are physical processes. Sometimes I kind of make a sarcastic remark, like, by the way, the Internet of Things actually includes things. TROND: [laughs] JEFFREY: And there's a different skill set for designing machines and making machines work and repairing machines than there is for designing software. There are a lot of physical things that have to go on in a factory, changing over equipment, be it for making different parts. And the vision of the technologists might be we'll automate all that, which may be true. Maybe 30 years from now, most of what I say about people will be irrelevant in a factory. I doubt it. But maybe it's 100 years from now, but it's going to be a long time. And there was an interesting study, for example, that looked at the use of robots. And they looked at across the world jobs that could be done by a human or could be done by a robot. And they found that of all the jobs that could be done by a human or a robot, 3% were done by robots, 97%...so this kind of vision of the robots driven by artificial intelligence doing the work of people is really science fiction. It's mostly fiction at this point. At some point, it might become real, but it's got a long way to go. So we still need to understand how to motivate, develop people. But particularly, the more complex the information becomes and the more information available, the more important it is to train people first of all in problem-solving and scientific thinking to use the data effectively and also to simplify the data because we're actually not very good at using a lot of data. We actually can't handle a lot of bits of data at a time like a computer can. So we need simple inputs that then allow us to use our creativity to solve the problem. And most of the companies are not doing that very well. They're offering what they call digital solutions, and I hate that term, on the assumption that somehow the digital technology is the solution. And really, what the digital technology is is just information that can be an input to humans coming up with solutions that fit their situation at that time, not generic solutions. TROND: It's fascinating that you started out with people. You went through all these experiences, and you are directly involved with digital developments. But you're still sticking to the people. We'll see how long that lasts. I think people, from the people I have interviewed, maybe self-selected here on the podcast, people and processes seem enormously important still in manufacturing. Thank you for your perspective. It's been a very rich discussion. And I hope I can bring you back. And like you said if in X number of years people are somehow less important...well, I'm sure their role will change, will adjust. But you're suspecting that no matter what kind of technology we get, there will be some role, or there should be some role for people because you think the judgment even that comes into play is going to be crucial. Is that what I'm -- JEFFREY: There's one more thing I want to add. If you look at industry 4.0, it'll list these are the elements of industry 4.0, and they're all digital technologies. But there's something that's becoming increasingly popular called industry 5.0, where they're asking what's beyond industry 4.0? Which has barely been implemented. But why not look beyond it? Because we've talked about it enough that it must be real. Once we kind of talk about something enough, we kind of lose interest in it. We want to go on to the next thing. So none of these things necessarily have been implemented very well and very broadly. But anyway, so industry 5.0 is about putting people back in the center. So I call it a rework loop. Uh-oh, we missed that the first time. Let's add it back in. TROND: So then what's going to happen if that concludes? Are we going to then go back to some new version of industry 4.0, or will it -- JEFFREY: Well, industry 4.0 is largely a bunch of companies selling stuff and then a bunch of conferences. If you go and actually visit factories, they're still making things in the same way they've always made them. And then there's a monitor that has information on a screen. And the IT person will show you that monitor, and the person on the floor may not even know what it is. But there's a disconnect between a lot of these technologies and what's actually happening on the shop floor to make stuff. And when they do have a success, they'll show you that success. You know, there's like hundreds of processes in the factory. And they'll show you the three that have industry 4.0 solutions in there. And so it's a long way before we start to see these technologies broadly, not only adopted but used effectively in a powerful way. And I think as that happens, we will notice that the companies that do the best with them have highly developed people. TROND: Fantastic. That's a good ending there. I thank you so much. I believe you've made a difference here, arguing for the continued and continuing role of people. And thank you so much for these reflections. JEFFREY: Welcome. Thank you. My pleasure. TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was the People Side of Lean. Our guest was Jeffrey Liker, academic, consultant, and best-selling author of The Toyota Way. In this conversation, we talked about how to develop internal organizational capability. My takeaway is that Lean is about motivating people to succeed in an industrial organization more than it is about a bundle of techniques to avoid waste on a factory production line. The goal is to have workers always asking themselves if there is a better way. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 84 on The Evolution of Lean. Hopefully, you will find something awesome in these or in other episodes. And if you do, let us know by messaging us, and we would love to share your thoughts with other listeners. The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, devices, and systems used in a production or logistics process in a physical location. Tulip is democratizing technology and empowering those closest to operations to solve problems. Tulip is also hiring, and you can find Tulip at tulip.co. Please share this show with colleagues who care about where industry and especially where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube. Augmented — industrial conversations that matter. See you next time. Special Guest: Jeffrey Liker.

Advanced Manufacturing Now
Composing Manufacturing Solutions in a Disruptive World

Advanced Manufacturing Now

Play Episode Listen Later Sep 7, 2022 33:15


Analysts at Gartner predict that organizations that employ “composable” software tools will outpace competition by 80% in the speed of new initiative implementation by 2023. In this podcast, SME Media Senior Editor Steve Plumb and Russ Waddell, Community Lead for Tulip, discuss how manufacturers are using composability systems to empower workers and achieve quantifiable results.

F1 Mode Push
Episode 6: From Tulips to Tiramisu

F1 Mode Push

Play Episode Listen Later Sep 6, 2022 63:36


Buzz and Jeanne break down the unexpected from the Dutch Grand Prix, and they look ahead to Monza. They also cover the latest silly season updates, including the details of just how the Alpine/McLaren Piasco unfolded. And you know Buzz has a field day with his Cultural Attache briefing on all things Italian. Have questions or comments about anything related to F1? Let Buzz and Jeanne know so they can respond on a future episode. Email them at ModePushPodcast@gmail.com or message them on Twitter @F1ModePush. Links: - Italian Recipes: https://leitesculinaria.com/84057/recipes-marcella-hazan-bolognese-sauce.html

Augmented - the industry 4.0 podcast
Episode 95: Smart Manufacturing for All

Augmented - the industry 4.0 podcast

Play Episode Listen Later Aug 31, 2022 46:21


Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In episode 17 of the podcast (@AugmentedPod), the topic is: Smart Manufacturing for All. Our guest is John Dyck, CEO at CESMII, the Smart Manufacturing Institute.After listening to this episode, check out CESMII as well as John Dyck's social profile:CESMII: (@CESMII_SM) https://www.cesmii.org/ John Dyck: https://www.linkedin.com/in/johnsdyck/ In this conversation, we talked about  democratizing smart manufacturing, the history and ambition of CESMII (2016-), bridging the skills gap in small and medium enterprises which constitute 98% of manufacturing. We discuss how the integration of advanced sensors, data, platforms and controls to radically impact manufacturing performance. We then have the hard discussion of why the US is (arguably) a laggard? John shares the 7 characteristics of future-proofing (interoperability, openness, sustainability, security, etc.). We hear about two coming initiatives: Smart Manufacturing Executive Council & Smart Manufacturing Innovation Platform. We then turn to the future outlook over the next decade.Trond's takeaway: US manufacturing is a bit of a conundrum. How can it both be the driver of the international economy and a laggard in terms of productivity and innovation, all at the same time? Can it all be explained by scale--both scale in multinationals and scale in SMEs? Whatever the case may be, future proofing manufacturing, which CESMII is up to, seems like a great idea. The influx of smart manufacturing technologies will, over time, transform industry as a whole, but it will not happen automatically.Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 8 on Work of the Future, episode 5 Plug-and-play Industrial Tech, or episode 9 The Fourth Industrial Revolution post-COVID-19. Augmented--the industry 4.0 podcast. Transcript: TROND: Augmented reveals the stories behind a new era of industrial operations where technology will restore the agility of frontline workers. In Episode 17 of the podcast, the topic is Smart Manufacturing for All. Our guest is John Dyck, CEO at CESMII, the Smart Manufacturing Institute. In this conversation, we talked about democratizing smart manufacturing, the history, and ambition of CESMII, bridging the skills gap in small and medium enterprises, which constitute 98% of manufacturing. We discuss how the integration of advanced sensors, data, platforms, and controls radically impact manufacturing performance. We then have the hard discussion of why the U.S. is, arguably, a laggard. John shares the seven characteristics of future-proofing. And we hear about two coming initiatives: Smart Manufacturing Executive Council & Smart Manufacturing Innovation Platform. We then turn to the future outlook over the next decade. Augmented is a podcast for leaders hosted by futurist, Trond Arne Undheim, presented by Tulip.co, the manufacturing app platform and associated with MFG.works, the manufacturing upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9:00 a.m. U.S. Eastern Time, every Wednesday. Augmented — the Industry 4.0 podcast. John, how are you today? JOHN: I'm well, Trond. How are you? TROND: I'm doing well. I'm looking forward to talking about smart manufacturing. What brought you to this topic, John? We'll get into your background. But I'm just curious. JOHN: This is my favorite topic, as you probably know. So I appreciate the chance to pontificate a little. I've been at this nexus between IT and OT for the last two decades of my career or more and found over these past two decades that this is one of the most complex pieces of manufacturing period, this sort of unique challenge between the world of operations and the world of IT. And the work I did at MESA (Manufacturing Enterprise Solutions Association) on the board and as the chairman of the board exposed me to a lot of the great vendors in this ecosystem. And through that work, I found that most of them struggle with the same things. We're all struggling in different ways. And so the opportunity to take one step back and look at this from a national and a global perspective and try to find ways to address these challenges became a very unique opportunity for me and one that I've enjoyed immensely. And so just the prospect of making a real difference in addressing these challenges as a nation and as an ecosystem has been just a privilege and one that I get really excited about. TROND: So, John, you mentioned your background. So you've worked in both startups...I think you were raising money for a startup called Activplant, but also, you have worked in large manufacturing for GE and Rockwell, so the big guys, I guess, in a U.S. context for sure. When this institution, C-E-S-M-I-I, CESMII, got started, what was its main objective, and what was the reason why this institution got launched? I guess back in 2016, which is not an enormous amount of time back. Give us a little sense of who took this initiative. And what is the core mission of this organization right now? JOHN: So Manufacturing USA is the umbrella organization under which these institutes, CESMII being one of them, were created. There are a total of 15 of these institutes, all funded with the exact same business model and funding model, and each of them having a different lens on the specific manufacturing problem that they're addressing. And ours, as the Smart Manufacturing Institute, is directly focused on creating a more competitive manufacturing environment by addressing innovation and research challenges that inhibit manufacturers from doing what they need to do in this fourth industrial revolution. So our mandate is to cut the cost of implementing smart manufacturing by 50%. Our mandate is to drive energy productivity, energy efficiency. Fundamentally, the agency that funds CESMII is the Department of Energy, which means that our overarching objective is to drive energy productivity as a basic metric. But we also believe that whether that's a direct challenge meaning addressing energy, performance energy efficiency directly, or an indirect outcome from a more efficient process, or a more effective supply chain, whatever that manufacturing initiative is, that we'll create a better product, a better process that will have direct and indirect impact on energy productivity, which is the connection back to our agency and the source of the funding that we have to accomplish these really important goals. TROND: And one of the really big identified gaps, also it seems, is this discrepancy between the big and the small industry players. So small and medium enterprises famously in every country is basically...the most of industry is consisting of these smaller players. They're not necessarily startups. They're not necessarily on this growth track to become unicorns. But they are smaller entities, and they have these resource constraints. Give me a sense of what you're doing to tackle that, to help them out, and to equip them for this new era. And maybe you could also just address...you called smart manufacturing industry 4.0, but I've noticed that that's not a term that one uses much. Smart manufacturing is kind of what you've opted for. So maybe just address that and then get to the small and medium-sized. JOHN: This is, I think, one of the really important observations that we try to make and the connections that we try to make to say that the status quo, the state of the industry today, Trond, is the result of three or four decades of what we did during the third industrial revolution. We began talking about the fourth industrial revolution many years ago. But we can't just turn that light switch on and assume that overnight everything we do now, despite the cultures we've created, the technologies we've created, the ways of doing things we've created, is now all of a sudden just new and exciting and different, and it's going to create that next wave of productivity. So when I talk about smart manufacturing and equating it with the fourth industrial revolution, it's truly the characteristics and the behaviors that we anticipate more so than what we're seeing. Because the critical mass of vendors and systems integrators, application and software products in this marketplace still resemble more of industry 3.0 than they do industry 4.0. And it's part of our vision to characterize those two only in the context of trying to accelerate the movement towards industry 4.0 or the fourth industrial revolution. Because it's that that holds out the promise of the value creation that we've been promised for ten decades but really aren't seeing. So that's the way we see the industry 4.0 versus the other concepts that we talk about. Digital transformation is another important term. All of that happens in the context of some initiative in a manufacturing operation to improve. We've been improving for three or four decades. What's different today? Well, it's not just relabeling [laughs] your portfolio to be industry 4.0 compliant. So anyway, that's a pet topic of ours just to help as a national conversation, as a set of thinking and thought leader organizations and individuals to put the spotlight on that and ensure that we're doing the things that we can to accelerate the adoption, and the behaviors, and the characterizations of what it really means to be industry 4.0. So to your point -- TROND: Yeah, I was just curious. The term revolution anyway is interesting in a U.S. context [laughter] and in any society. So it implies a lot of things, but it also certainly implies a speed that perhaps isn't necessarily happening. So there's all this talk now about how things are speeding up. But as you point out, even if they have some revolutionary characteristics, at the edge, there are some other things that need to happen that aren't necessarily going to happen at the speed of what you might imagine when you use the word revolution. It's not going to turn over like a switch. JOHN: That's exactly right. Well said, Trond. Manufacturing and bleeding edge never come together in the same sentence, and so it takes time for...and more so on the OT side than the IT side. Right out of the IT world, we have industrial IoT platforms. We have augmented reality. We have powerful AI machine learning tools. But what is the true adoption on the plant floor? Well, that's where the behaviors, and the cultures, and the characteristics of how we've always done things and the reluctance to adopt new things really comes in. And it's as much a part of the vendor and systems integration ecosystem as it is on the manufacturing side. And that's, again, this whole thing becomes...to drive (I really don't think it's a revolution to your point.) an evolution or accelerate the evolution towards Industry 4.0 requires the ecosystem to get engaged and to recognize these really important things have to change. Does that make sense? TROND: Yes. A lot of them have to change. And then to these small and medium enterprises, so I've seen a statistic that even in the U.S., it's around 98% of manufacturing. That is an enormous challenge, even for an association like yours. How do you reach that many? JOHN: Here's an interesting epiphany I had shortly after I came to CESMII and was working through exactly this challenge: how does an organization like ours access and understand the challenges they face and then look at the ecosystem that's there and available to serve them? The epiphany I had was that in my entire career with both big global corporations like Rockwell Automation and General Electric and specifically even the startup organization that I helped raise VC for and venture capital funding for and build and ultimately see acquired; I had never been in a small and medium manufacturing plant environment. The entire ecosystem is focused on large brands, recognized brands, and enterprises that have the potential for multisite rollouts, multisite implementation. And so the business models, the marketing models, the sales, the go-to-market, the cost of sales, everything in this ecosystem is designed towards the large enterprises called the Fortune 1000 that represent the types of characteristics that any startup, any Global Fortune 500 organization is going to go pursue. Which then says or leaves us with a really important conversation to say, how can the small and medium manufacturing organizations become part of this dialogue? How can we engage them? What does an ecosystem look like that's there to serve these organizations? And where an implementation organization like a good systems integrator can actually make money engaging in this way. And so that's where the needs of that ecosystem and our specific capabilities come together. The notion that democratization which is going to help the big manufacturers, and the big vendors, and the big integrators, and the big machine builders, the same things that we can do to cut the cost of deploying smart manufacturing for them, will enormously increase the accessibility of smart manufacturing capabilities for the small and medium manufacturers. And so that's where typically -- TROND: John, let's talk specifics. Let's talk specifics. So smart manufacturing, you said, and I'm assuming it's not just a community effort. You're intervening at the level also of providing a certain set of tools also. So if we talk about sensors, and data, and platforms, and control systems, these are all impacting manufacturing performance. To what extent can an association like yours actually get involved at that level? Is it purely on the standardization front, sort of recommending different approaches? Or is it even going deeper into layers of technology and providing more than just recommendations? JOHN: So the short answer is it depends on the domain, and the area of networking, and sensors and controls. Those are areas where longer-term research and investment to drive innovation to reduce the cost of connecting things becomes really important. And that's one of the threads or one of the investment paths that we pursue through what we call roadmap projects where there are longer, larger in terms of financial scope and further out impacts. We're hoping we'll have a dramatic impact on the cost of connecting machines and sensors and variable-frequency drives and motion systems or whatever sort of data source you have in an operation. So that's one track. The other piece which gets to the actual creation of technologies is more on the data contextualization, data collection, data ingestion side. And you mentioned the word standards. Well, standards are important, and where there are standards that we can embrace and advocate for, we're absolutely doing that. Part of the OPC Foundation and the standards that they're driving, MQTT and Sparkplug, becomes a really important area as well. And the work that MTConnect is doing to solve many of the same challenges that we believe we need to solve more broadly for a subset of machine classes more in a CNC machine tool side. But this effort, smart manufacturing, is happening today, and it's accelerating today. And we can't wait for standards to be agreed on, created, and achieve critical mass. So we are investing in a thin but vital layer of technologies that we can drill into if you'd like as a not-for-profit, not to compete in the marketplace but to create a de facto standard for how some of these really important challenges can be addressed, and how as a standard develops and we fund the deployment of these innovations in the marketplace and kind of an innovation environment versus a production environment. Not that they don't turn into production environments, but they start as an innovation project to start and prove out and either fail quickly or scale up into a production environment. So this idea of a de facto standard is a really important idea for us. That's our objective. And that's what we believe we can build and are building is critical mass adoption for really important ideas. And we're getting support from a lot of the great thought leaders in the space but also from a lot of the great organizations and bodies like, as I mentioned, the OPC Foundation, The Industrial Internet Consortium, the German platform industry 4.0 group responsible in Germany for industry 4.0. We're working towards and aligning around the same principles and ideas, again, to help create a harmonized view of these foundational technologies that will allow us to accomplish the dramatic reduction of the cost of connecting and extracting information from and contextualizing that information. And then making it available in ways that are far more consistent and compelling for the application vendor. The bar or the threshold at which an application developer can actually step into the space and do something is in a pretty high space. If you kind of look back, and I know this analogy is probably a little overused, but what it took to build applications for devices and phones, smart devices, and smartphones before Apple and Android became commonplace meant that you had to build the entire stack every single time. And that's where the industry is today. When you sit down in front of a product, you're starting from scratch every time, regardless of the fact that you've created an information model for that paper-converting machine 100 times in 20 different technology stacks. When I start this project, it's a blank slate. It's a blank sheet of paper every single time. Is that value-add? Is that going to help? No. And yet it requires a tremendous amount of domain expertise to build that. So the notion of standardizing these things, abstracting them from any individual to technology stack, standardizing on them, making them available in the marketplace for others to use that's where democratization begins to happen. TROND: So what you are about to create is an innovation platform for smart manufacturing. Will that be available then to everybody in the U.S. marketplace? Or is it actually completely open for all of the industry, wherever they reside? And what are the practical steps that you would have to take as a manufacturer if you even just wanted to look into some of the things you were building and maybe plug in with it? JOHN: So we're not about to build, just a minor detail there. We've been working on this for a couple of years. And we have a growing set of these implementations in the marketplace through the funded projects that we were proud to be able to bring to the marketplace. So the funding, and right now within the scope of what we're doing here as an institute, the funds that we deploy as projects, these grants, essentially mean that we spend these grants, these funds in the U.S. only. So in the context of what we do here, the smart manufacturing innovation platform, the creation of these profiles, the creation of the apps on top of the platform by our vendor ecosystem and domain experts in this ecosystem those are largely here and exclusively here in the U.S, I should say. So from that perspective, deployments that we have control over in terms of funding are uniquely here in the U.S. What happens beyond that in terms of where they're deployed and how they're deployed, we know we live in a global manufacturing environment. And as our members who want to deploy these capabilities outside of the U.S., those are all absolutely acceptable deployments of these technologies. TROND: But, John, so all of these deployments are they funded projects so that they're always within involvement of grant money, or is some part of this platform actually literally plug and play? JOHN: So there are several threads. The projects that we fund are obviously one thread. There's another thread that says any member of ours can use any implementation of our platform or can use our platform and any of the vendors that are here as a proof of concept or pilot, typically lasting 3,4,5,6 months for free of charge. What happens then that leads to the third component is after your pilot, there's one of two things that's going to happen. The system will be decommissioned, and you ideally, well, I shouldn't say ideally...you fail fast, the system is decommissioned, and folks move on. Ideally, the pilot was a success. And that generates a financial transaction for the parties involved in that. And that organization moves towards a production rollout of these capabilities. So CESMII's role then diminishes and steps away. But this notion of a pilot actually came from a conversation with one of our great members here at Procter & Gamble. They talk about innovation triage and the complexity of just innovating within a large corporate environment like Procter & Gamble. The fact that just to stand up the infrastructure to invite a vendor, several vendors in to stand up their systems costs hundreds of thousands of dollars and takes months and months and months just to get started. This notion that we can provision this platform in minutes, bring our vendor partner technologies to bear in minutes allows them to execute what they call innovation triage. And it really accelerates the rate at which they can innovate within their corporation, but it's that same idea that we translate back down to small and medium manufacturing, right? The notion that you don't have to have a server. You don't have to sustain a server. You don't have to buy a server to try smart manufacturing in a small and medium manufacturing environment. If you've got five sensors from amazon.com and lightly industrialized Raspberry Pi, you have the means to begin the smart manufacturing journey. What do you do with that data? Well, there are great partner organizations like Tulip, like Microsoft Excel, even Microsoft Power BI that represent compelling democratized contemporary low-cost solutions that they can actually sustain. Because this isn't just about the cost of acquiring and implementing these systems, as you know. This is also about sustaining them. Do I have the staff, the domain expertise as a small and medium manufacturer to sustain the stuff that somebody else may have given me or implemented here for me? And so that's just as an important requirement for these organizations as the original acquisition and implementation challenges. TROND: It's so important what you're talking about here, John, because there's an additional concept which is not so pleasant called pilot purgatory. And this has been identified in factories worldwide. It's identified in any software development. But with OT, as you pointed out, with more operational technologies, with additional complications, it is so easy to just get started with something and then get stuck and then decide or maybe not decide just sort of it just happens that it never scales up to production value and production operations. And it seems like some of the approaches you're putting on the table here really help that situation. Because, as you mentioned, hundreds of thousands of dollars, that's not a great investment for a smaller company if it leads to a never-ending kind of stop and start experimenting but never really can be implemented on the true production line. JOHN: Yeah. Spot on, Trond. The numbers that we're seeing now...I think McKenzie released a report a couple of months ago talking about, I think, somewhere between 70% and 80% of all projects in this domain not succeeding, which means they either failed or only moderately succeeded. And I think that's where the term pilot purgatory comes in. I talk almost every chance I get about the notion that the first couple of decades of the third industrial revolution resulted in islands of automation. And we began building islands of information as software became a little more commonplace in the late '80s and '90s. And then the OTs here in the last decade, we've been building islands of innovation, this pilot purgatory. The assumption was...and I get back to the journey between where we thought industry 3.0 or the third industrial revolution became the fourth industrial revolution. The idea was that, man, we're just going to implement some of these great new capabilities and prove them out and scale them up. Well, it gets back to the fact that even these pilots, these great innovative tools, were implemented with these old ideas in these closed data siloed ways and characterizations. And so yeah, everybody's excited. The CEO has visibility to this new digital transformation pilot that he just authorized or she just authorized. And a lot of smart people are involved, and a lot of domain experts involved. The vendors throw cash at this thing, and the systems integrators, implementers, throw cash at this thing. And even if they're successful, and broadly, as an individual proof of concept, there are points of light that say, we accomplished some really important things. The success is not there, or the success isn't seeing that scaled out, and those are the really nuanced pieces that we're trying to address through this notion of the innovation platform and profiles. The notion that interoperability and openness is what's going to drive scale, the notion that you don't have the same stovepipe legacy application getting at the same set of data from the same data sources on the shop floor for every unique application, and that there are much more contemporary ways of building standardized data structures that every application can build on and drive interoperability through. TROND: Yeah, you talk about this as the characteristics of future-proofing. So you mentioned interoperability, and I guess openness which is a far wider concept. Like openness can mean several things. And then sustainability and security were some other of your future-proofing characteristics. Can you line up some of those for us just to give some context to what can be done? If you are a factory owner, if you're a small and medium-sized enterprise, and you want to take this advice right now and implement. JOHN: Yeah, we've tried as an association, as a consortia, Trond, it's not just CESMII staff like myself who are paid full-time to be here that are focused on identifying and developing strategies for the challenges that we believe will help manufacturing in the U.S. It's organizations that are members here and thought leaders from across the industry that help us identify these really fundamental challenges and opportunities. And so, as an institute, we've landed on what we call the smart manufacturing first principles. There are seven first principles that we believe characterize the modern contemporary industry 4.0 compliant, if you will, strategy. And just to list them off quickly, because we have definitions and we have content that flushes out these ideas, sort of in order of solve and order of importance for us, interoperability and openness is the first one. Sustainable and energy efficient is the second one, security, scalability, resilient and orchestrated, flat and real-time, and proactive and semi-autonomous. And so these we believe are the characteristics of solutions, technologies, capabilities that will move us from this world of pilot purgatory and where we've come from as an ecosystem in this third industrial revolution and prepare us for a future-proof strategy whether I'm a small and medium manufacturer that just cares about this one instance of this problem I need to solve, or whether I'm a Fortune 10 manufacturing organization that understands that the mess that we've created over the last 25 years has got to make way for a better future. That I'm not going to reinvest in a future...not that I can rip and replace anything I've got, but I've got to invest in capabilities moving forward that represent a better, more sustainable, more interoperable future for my organization. That's the only way we're going to create this next wave of productivity that is held out for us as a promise of this new era. TROND: John, you have alluded to this, and you call it the mess that we've created over the last 25 years. We have talked about the problems of lack of interoperability and other issues. This is not an easy discussion and certainly not in your official capacity. But why is the U.S. a laggard? Because, to be honest, these are not problems that every country has, to a degree, they are but specifically, the U.S. and its manufacturing sector has been lagging. And there is data there, and I think you agree with this. Why is this happening? And are any of these initiatives going to be able to address that short term? JOHN: So this is probably the most important question that we as a nation need to address, and it's a multifaceted, complex question. And I think the answer is a multifaceted, complex response as well. And we probably don't have time to drill into this in detail, but I'll respond at least at a 30,000 foot-level. Even this morning, I saw a friend of mine sent me a link about China being called out today officially as being a leader in this digital transformation initiative globally, as you've just alluded to. So, from our perspective, there are a couple of important...and like I said, really understanding why this is the case is the only way we're going to be able to move forward and accelerate the adoption of this initiative. But there are a number of reasons. The reason I think China is ahead is in part cultural, but it's also in part the fact that they don't have much of the legacy that we've built. Most of their manufacturing operations as they've scaled up over the last decade, two decades, really since the World Trade Organization accepted China's entry in this domain, their growth into manufacturing systems has been much, much more recent than ours. And so they don't have this complex legacy that we do. There are other cultural implications for how the Chinese manufacturing environment adopts technologies. And there's much more of a top-down culture there. Certain leaders drive these activities and invest in these ways. Much of the ecosystem follows. So that's, I'll say, one perspective on how China becomes the leader in this domain very quickly. Europe is also ahead of the U.S. And I think there are some important reasons why that's the case as well. And a part of it is that they have a very strong cultural connection to the way government funds and is integrated with both the learning and academic ecosystem there in most of Europe as well as with the manufacturing companies themselves. It seems to have become part of their DNA to accept that the federal government can bring these initiatives to the marketplace and then funds the education of every part of their ecosystem to drive these capabilities into their manufacturing marketplace. We, on the other hand, are a much more American society. We are individualistic. The notion that the government should tell manufacturers what to do is not a well-accepted, [laughs] well-adopted idea here in the U.S. And that's been a strength for many manufacturers, and for many, many years. The best analogy that I can come up with right now in terms of where we are and where we need to go and CESMII's role in all of this, and the federal government's role in all of this, which I think brings a healthy blend of who we are as a nation and how we work and how we do things here together with a future that's a little more also compatible with these notions of adopting and driving technology forward at scale, is the reality that in 1956, President Eisenhower convinced Congress to fund the U.S. Interstate Highways and Defense Act to build a network of interstate highways, a highway network across this country to facilitate much more efficient flow of people and goods across this country. Apparently, as a soldier, many decades before, he had to travel from San Diego to Virginia in a military convoy that took him 31 days to cross the country [laughs], which is a slight aside. It was apparently the catalyst that drove the passion he had to solve this problem. And that's the role that I think we can play today, creating a digital highway, if you will, a digital catalyst to bring our supply chains together in a much more contemporary and real-time way and to bring our information systems into a modern industry 4.0 compliant environment. And that's setting those, creating those definitions, defining those characteristics, and then providing the means whereby we can accelerate this ecosystem to move forward. I think that's the right balance between our sense of individualism and how we do things here in the U.S. versus adopting these capabilities at scale. TROND: That's such a thoughtful answer to my question, which I was a little afraid of asking because it is a painful question. And it goes to the heart, I guess, of what it means to be an American, to be industrial, and to make changes. And there is something here that is very admirable. But I also do feel that the psychology of this nation also really doesn't deeply recognize that many of the greatest accomplishments that have been happening on U.S. soil have had an infrastructure component and a heavy investment from the government when you think about the creation of the internet, the creation of the highway system. You can go even further back, the railways. All of those things they had components, at least a regulation, where they had massive infrastructure elements to them whether they were privately financed or publicly financed, which is sort of that's sort of not the point. But the point is there were massive investments that couldn't really be justified in an annual budget. JOHN: That's right. TROND: You would have to think much, much wider. So instead of enclosing on that end then, John, if you look to the future, and we have said manufacturing is, of course, a global industry also, what are you seeing over this next decade is going to happen to smart manufacturing? So on U.S. soil, presumably, some amount of infrastructure investment will be made, and part of it will be digital, part of it will be actually equipment or a hybrid thereof that is somewhat smartly connected together. But where's that going to lead us? Is manufacturing now going to pull us into the future? Or will it remain an industry that historically pulls us into the future but will take a backseat to other industries as we move into the next decade? JOHN: Yeah, that's another big question. We've been talking about smart manufacturing 2030, the idea that smart manufacturing is manufacturing by 2030. And a decade seems like a long time, and for most functions, for most areas of innovation, it is, but manufacturing does kind of run at its own pace. And there is a timeline around which both standardization and technologies and cultures move on the plant floor. And so that's a certain reality. And we were on a trajectory to get there. But ironically, it took a pandemic to truly underscore the value of digital transformation, digital operations, and digital workers, I can certainly say in the U.S. but even more broadly. So a couple of important data points to back that up. Gartner just recently announced the outcome of an important survey of, I think, close to 500 manufacturing executives here in the U.S. in terms of their strategic perception of digital transformation, smart manufacturing. And I think they specifically called it smart manufacturing. And it was as close to unanimous as anything they've ever seen; 86% or 87% of manufacturing executives said that now digital transformation, smart manufacturing is the most strategic thing they can invest in. What was it a year ago? It was probably less than half of that. So that speaks to the experience these organizations have gone through. And the reality that as we talk about resilience, some people talk about reshoring, and some of that will happen. As we talk about a future environment, that's...I shouldn't say disruption-proof but much more capable of dealing with disruption not just within the four walls of the plant or an enterprise but in the supply chain. These capabilities are the things that will separate those that can withstand these types of disruptions from those that can't. And that has been recognized. And so, as much as these executives are the same ones that are frustrated by pilot purgatory, it's these executives that are saying, "That's the future. We've got to go there." And we're seeing through this pandemic...we hear CESMII are saying the manufacturing thought leaders understand this and are rallying around these ideas more now than ever before to ensure that what we do in the future is consistent with a more thoughtful, more contemporary, future-proof way of investing in digital transformation or smart manufacturing. TROND: John, these are fascinating times, and you have a very important role. I thank you so much for taking time to appear on my show here today. JOHN: Trond, I appreciate that. I appreciate the privilege of sharing these thoughts with you. These are profound questions, and answering the easy ones is fun. Answering the hard questions is important. And I appreciate the chance to have this conversation with you today. TROND: Thanks. Have a great day. JOHN: You too. TROND: You have just listened to Episode 17 of the Augmented Podcast with host Trond Arne Undheim. The topic was Smart Manufacturing for All. Our guest is John Dyck, CEO at CESMII, the Smart Manufacturing Institute. In this conversation, we talked about democratizing smart manufacturing and the history and ambition of CESMII, bridging the skills gap in small and medium enterprises, which constitute 98% of manufacturing. We discuss how the integration of advanced sensors, data, platforms, and controls radically impact manufacturing performance. We then have the hard discussion of why the U.S. arguably is a laggard. We heard about two coming initiatives: the Smart Manufacturing Executive Council & the Smart Manufacturing Innovation Platform. We then turned to the future outlook over the next decade. My takeaway is that U.S. manufacturing is a bit of a conundrum. How can it both be the driver of the international economy and a laggard in terms of productivity and innovation, all at the same time? Can it all be explained by scale, both scale in multinationals and scale in SMEs? Whatever the case may be, future-proofing manufacturing, which CESMII is up to, seems like a great idea. The influx of smart manufacturing technologies will, over time, transform industry as a whole, but it will not happen automatically. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 8 on Work of the Future, Episode 5 on Plug-and-play Industrial Tech, or Episode 9 on The Fourth Industrial Revolution post-COVID-19. Augmented — the Industry 4.0 podcast. Special Guest: John Dyck.

F1 Mode Push
Episode 5: From Waffles to Tulips

F1 Mode Push

Play Episode Listen Later Aug 30, 2022 61:55


Jeanne and Buzz review the Belgian GP, from the odd quali combined with grid penalties to Red Bull's blistering pace. They also preview the upcoming Dutch GP, the latest F1 news, and conclude with some career coaching for Danny Ric. Don't miss Buzz's Cultural Attache intro to The Netherlands. -Email Buzz and Jeanne with comments or questions about anything F1 related at ModePushPodcast@gmail.com or message them on Twitter @F1ModePush. They may read your email/message on a future episode. -Follow the show on Instagram and Facebook at: F1 Mode Push.

Pick, Place, Podcast
A Conversation with The Awkward Engineer

Pick, Place, Podcast

Play Episode Listen Later Aug 29, 2022 71:08


In this episode, which might just be our nerdiest one yet, we are joined by Sam Feller, aka The Awkward Engineer.  First and foremost he would like everyone to know that he is the awkward one, the engineering is top notch.Sam is a long time Worthington/CircuitHub customer, product manager at Tulip, former engineer at Amazon, and founder of the Awkward Engineer where he works on quirky hardware project and now does consulting! It was a pleasure to have Sam on the show. Some of the topics we touch on include: Why having common stock parts set up on reels is not actually the simplest idea to execute.Interesting sourcing stories.Soldering techniques for building prototypesThe importance of having structured processes in place for your hardware of software development team .Sam's vickrey auction for his Voltmeter ClocksIf you want to get in touch with Sam you can email him at questions@awkwardengineer.com

Art of History
Flower Power: Tulipmania and Those who Painted It

Art of History

Play Episode Listen Later Aug 25, 2022 64:54 Very Popular


Tulipmania has stuck in our collective memory as one of the biggest economic calamities to ever strike the western world. The popular narrative holds that in 17th century Holland, ​​homes were mortgaged, reputations were ruined, and livelihoods were lost—all so that tulip bulbs could be bought at higher and higher prices. And when the “bubble” burst, chaos ensued. In fact, the truth was far less sensational. But contemporary 17th-century artworks can shed some light on the real Tulip Fever, and perhaps give us some clues as to why Tulipmania continues to hold such power over our notions of the Dutch Golden Age. Today's Images: Jan Breughel the Elder, Still Life with Tulips, Chrysanthemums, Narcissi, Roses, Irises and other Flowers in a Glass Vase (1608-1610). Oil on copper. The National Gallery, London. and Jan Brueghel the Younger, A Satire of Tulip Mania (c. 1640-1650). Oil on Panel. Frans Hals Museum, Netherlands. Jan Brueghel the Younger, Allegory of Tulipomania (c. 1640-1650). Oil and gold on Panel. Private collection, France. ______ New episodes every month. Let's keep in touch! Email: artofhistorypod@gmail.com Patreon: https://www.patreon.com/matta_of_fact Instagram: @artofhistorypodcast Twitter: @ArtHistoricPod TikTok: @artofhistorypod // @matta_of_fact Learn more about your ad choices. Visit megaphone.fm/adchoices

Whispers: Plant Spirit Medicine
Episode 98: Tulip Poplar and Your Golden Heart

Whispers: Plant Spirit Medicine

Play Episode Listen Later Aug 25, 2022 12:37


* Tulip Poplar * Golden Heart * Golden Compass * Illumination * Maps * Atlas * True North * Rose * Heart Medicine * Lamp * Light * Psalms * Embodied Apprenticeship: EMBODIED APPRENTICESHIP | alchemillas * Amanda's IG: Amanda Nicole (@alchemillasplantmedicine) • Instagram photos and videos --- Support this podcast: https://anchor.fm/amanda-dilday/support

Augmented - the industry 4.0 podcast
Episode 94: Digitized Supply Chain

Augmented - the industry 4.0 podcast

Play Episode Listen Later Aug 24, 2022 45:10


Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In episode 43 of the podcast (@AugmentedPod), the topic is: Digitized Supply Chain. Our guest is Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT, Johnson & Johnson.In this conversation, we talk about why J&J puts operators at the center of its strategy, the empowerment effect of frontline operations apps, the evolution of personalized production, and how supply chain becomes an integral part of product development.After listening to this episode, check out J&J as well as Arun Kumar Bhaskara-Baba's social medial profile: J&J (@JNJNews): https://www.jnj.com/ Arun Kumar Bhaskara-Baba: https://www.linkedin.com/in/bhaskarababa/Trond's takeaway: "Operators are the key to the next phase of industrial evolution, that which involves the deep digitalization of manufacturing, its supply chain, production capacity, personalization, and with that the reinvention of factory production itself.Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 21, The Future of Digital in Manufacturing, episode 27, Industry 4.0 Tools or episode 10, A Brief History of Manufacturing SoftwareAugmented--conversations on industrial tech. Transcript: TROND: Augmented reveals the stories behind a new era of industrial operations, where technology will restore the agility of frontline workers. In Episode 43 of the podcast, the topic is Digitized Supply Chain. Our guest is Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson. In this conversation, we talk about why J&J puts operators at the center of its strategy, the empowerment effect of frontline operations apps, the evolution of personalized production, and how supply chain becomes an integral part of product development. Augmented is a podcast for leaders hosted by futurist Trond Arne Undheim, presented by Tulip.co, the frontline operations platform, and associated with MFG.works, the manufacturing upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9:00 a.m. U.S. Eastern Time, every Wednesday. Augmented — the industry 4.0 podcast. TROND: Arun, how are you? ARUN: I'm doing great. How are you, Trond? TROND: Oh, it's wonderful to see you and hear you. I'm very excited. This is a big interview. You have really big responsibilities, Arun. We're going to get to that in a second. But global manufacturing that is a wide, wide topic. ARUN: Yes, indeed. But the bigger responsibility, but more importantly, what we are privileged is how we are impacting the lives of patients and customers around the world with our products. That comes with the privilege to work in the healthcare environment. TROND: Well, I'm glad you said that because as we're sort of tracing, I want to ask you a little bit about how you got to where you are. And I know from public records, at least, that you have part of your schooling in India. So you grew up in India, my assumption is, and you got your computer degree there. You worked in India for a little while for the Tata system. And then you made your way over to Michigan. You have your MBA from there. And then, from what I understand, you then had a bit of a career in automotive and then moved on to Dell. And this brings us to J&J. How did you end up in the U.S.? And how was that journey for you? You've come quite a bit of ways. ARUN: Yes. It's interesting that you asked how I ended up in U.S. For me, it was a choice of either going to Japan or to U.S., And I'm a vegetarian, so for me, U.S. was a better choice. Growing up when you're a kid, you have two years of experience, the decisions that you make, some priorities. TROND: That's funny, but you told me, Arun, that you came here with a briefcase and a $10 bill. ARUN: Yes. I was going to go -- TROND: That's, I guess, not an unusual immigrant story, but it is still quite striking. ARUN: Absolutely. I grew up in a very small middle-class family. So when I landed, I landed with a briefcase and a $20 bill, actually two $10 bills. And out of that, one $10 bill I still have as a reminder of where I started. TROND: Wow. And I cut your career a little short because you have had the opportunity to work in all of the BRIC countries, essentially. And you now manage teams across, I think, at least 28 countries. And that brings us, I guess, up to present day where I was alluding to this, but you have a very wide responsibility. We're going to talk about some of it. Can you tell me a little bit about your current role? ARUN: So, my team supports all the manufacturing operations for J&J across the globe. So we have 100-plus manufacturing plants in pharmaceutical, consumer, medical devices, and vision products. As I mentioned earlier, I am privileged to be in healthcare to serve our patients and customers. We are in 28 countries; my team is spread across. And it's a very humbling experience to really work in a global team and continue to support our operations across the world. TROND: Well, not only that 28 countries, but I understand you operate about 100 manufacturing sites, some obviously state of the art, very big and sprawling, others actually very small or at least mid-size and have all kinds of other issues. And J&J, you know, what is the breadth of products you make? I mean, you make vaccines. You make knees, artificial knees. What else do you guys make? ARUN: This is amazing. I used to work for Ford Motor Company and Dell. Definitely, they are also very strong in manufacturing. However, the manufacturing processes are very similar. It is either assembly process, marketing and manufacturing at Dell. I come to J&J, and any type of manufacturing, you say we got it. Whether you talk about process manufacturing or discrete manufacturing, we have that. So in the pharmaceutical area, we produce biological products where we actually grow live cells and make medicine out of it, as you mentioned, the vaccines and biological products. We also have big chemical products where we actually use big chemical reactions to produce the drugs. In medical devices, we have artificial knees and hips, which are more like a foundry operation. You take a mold, you put it in an artificial knee, and make it happen. And we have sutures that we produce. And in the consumer side, we have different types of liquids, gels, and tablets that we produce. And finally, in vision care is where we produce our lenses in a very high-velocity manufacturing. So if you look at the breadth of the manufacturing processes and products we support, we support almost every aspect of manufacturing. TROND: Well, this brings us to today's topic because we're going to talk a little bit about digitizing these operations, the supply chains, the whole thing, and think about what digital means to all of it, whether it's in pharma 4.0, or indeed, you know, manufacturing and industry 4.0. Can you maybe just kick us off a little bit and say what does digital mean to your business today? And what is your main take on how to approach it? ARUN: The first thing is really I see digital as a means to an end. So if you think about it, it's really why digital is the first and then why digital. We need to be very clearly understanding why we want to digitize. We are in the journey to transform our supply chain so that we can put our patients, our customers at the center of the supply chain and how we can get our products to our customers in a fast, nimble way and in an affordable way. If you think about healthcare, the key is affordability as well as the ability for us to deliver what they need where they need it. And if you think about even the vaccines that we are producing now, we are manufacturing only in some locations, but we have to distribute them everywhere, whether to sophisticated networks like U.S. or developing areas where we don't even have a lot of transportation like Africa. So how do we put the customer and the patient at the center? And how can we actually serve them in a much more faster way and in an affordable way? So that is the why behind our supply chain journey. And digitization is a very critical component of that transformation. How do we provide that end-to-end connectivity so that we can reach our customers and patients? How do we understand what is happening in the markets and react to those things quickly as well as respond quickly using digital? And then ensure that we are delighting our customers beyond just our products, that we have world-class products. But how do we make sure that we are delivering the same customer experience to our patients and customers? So for us, the work from the digital side is how do we build that end-to-end connectivity so that we can reach our customers and we can sense and respond very quickly? And finally, how do we make sure that we significantly improve your customer experience? TROND: I want to pick up on a couple of things, but let me first ask a basic question. I mean, when I think supply chain, I think back to business school where I was teaching for a while, and I think kind of a fairly dry subject that was a specialty subject. You either cared about it, and then you wanted to become an expert and obviously dominate the field. But now you're speaking of it as if it is a much more integrated part of product development, which I think that was certainly taught as two separate courses, even in the very immediate past. But do you think of the supply chain as completely integrated with what you do, what you produce? ARUN: Absolutely. If you think about where the healthcare is headed, if you think about personalized healthcare, if I'm taking a knee right now, we ship like six or seven knees to the surgeons so that they pick the right knee during the operation. And we are getting to a place where we take the picture of the knee, get it back, and make the product, and then 3D print it and give it to the surgeon. Or if you think about how we are personalizing where we are taking the blood from the patient and making the product that is very specific to the patient and shipping it to them. So this whole flow of here is my R&D, and then it goes to supply chain, and then we deliver it versus it is now becoming a connected world where this all comes together. So it's really a very integrated part of product development and supply chain. So we really look at that end to end. And then digital is the one that is actually accelerating that journey. Because I can now connect all of these things as a digital thread and then really push the envelope forward. TROND: But producing for a batch of one, I mean, it's enormously challenging at scale, no? ARUN: Yeah, absolutely. That is the trick, right? How do I produce that batch of one? And if you think about the future, where we can actually get to that and where we can produce batch of one for almost everything that we do is where we are headed. You're right; there are significant investments in terms of our manufacturing operations and the equipment that we need. And there is that balance between the scale that you need to have versus the personalization that is needed. And the balance is I don't think the pendulum can go either one way or the other. But really, we still have a lot more to move to the personalized level. How do we really become a full supply chain so that we can produce that batch of one wherever possible? And look at that from the customer and patient's angle, right? If you have somebody who has a traumatic surgery going on and they have a bone that we need to fix...and it is not the same from one trauma to another trauma. There you can't come back and say, okay, here is a batch of things that I'm producing, and I'm going to give it to you. So the customer expectations are also changing. As a patient and as a consumer, their expectations are also changing. And so we are moving to that batch of one. And how do you do it for different products? And how do you do it for different manufacturing processes is going to be tailored to that business model and then the product. TROND: So another thing that one might assume when we speak about this, because okay, batch of one, but it has to be an advanced system, and it's covering the globe. I mean, historically, if a factory has machinery or systems and digital technologies, it is a very monolithic, massive system. I understand that you have taken at least some care these days to focus on the operators. Why is that so crucial to you? And what does that mean for the kinds of technologies that you're putting into your factories nowadays? ARUN: So that's a very good question. If you think about where manufacturing is headed so that we can drive that flexibility, that approach so that we can quickly respond, we have to relook at our manufacturing operations. That means they need to be a lot more nimbler and a lot more flexible. And a lot of technologies are emerging, and that's all driving. But for us, at the end of the day, it all comes back to that operator. We are here to serve the operator. We call it #operatorrules. Because think about this, we can do all these flexible things. We can bring in automation. We can bring in robots and all of it. At the end of the day, there is an operator at the line who is making it happen. So how do we make sure that we put the operator at the center and then create the experience for the operator so that it makes it a lot easier? If you take any of our plants, the technology is growing very fast. We used to have an ERP system. The operator has to deal with an MES. The operator then has to look at the equipment interface that the equipment provider has given. Now I'm coming from technology and saying, okay, here is the smart glass. Wear the smart glass, and you can look at everything. Think about the operator, how complex we have made the operator's life. So we are trying to take a step back and say, how do we, first of all, make it simple? Number two is how do we empower them? So far, we all said that, oh, technology is either manufacturing engineering or the OT or IT people. We held the keys for the technology. But how do we really empower the operators so that they can make it flexible and then they can make it nimble? So that gives you the velocity that we need at our manufacturing operations. TROND: It's striking when you think about at least digital technologies now clearly. There have been machines in factories for centuries. I mean, that was sort of the various industrial revolution. So there have, of course, been machines that could be operated by operators to some degree. But the kind of control and the detail-level customization that's now becoming possible doesn't come naturally, does it? It takes a lot of attention to create those kinds of platforms. How do you see that evolving? For example, we said you have over 100 different sites, some of them large, others much smaller; what sort of approaches are you taking to experiment with these solutions? ARUN: So it's purpose-driven experimentation. Because to your point, when we have these large, fully automated factories, the key is how fast I can introduce new capabilities into that operation. Whereas when I go to a middle-tier factory with semi-automated or not as much automated, it is a very target problem-driven. I have an OEE problem. Let me figure out how do I experiment to bring the technology. But at both the spectrums, the key is to make sure that there is a good, robust architecture principles. There is good, robust security, and then there is a good data architecture. But from a solutions point of view, how do we make sure that these are modular? Think about the mainframe days where you need to know all those to run the application to now you have apps on your device. So how do we break these monolithic technologies that are running the operations into smaller apps by bite-sized chunks that we can actually deploy very quickly or pull it out? And that gives me the flexibility to say for a large site; I'm going to deploy all these 100 apps so that they can run it as a suite. Whereas when I go to a smaller site, I might only deploy two of those applications for a specific problem. So it's kind of like really breaking down by, number one, by purpose. Number two, having a good consistent architecture. And number three, really breaking these monolithic things into smaller apps and nimble apps that we can drive. TROND: I know that you've tried some of Tulip's solutions. Tulip is an app system. But clearly, the bar to completely replace any number of advanced technologies that have developed over literally decades is not done overnight. How do you see the journey that app developers on the manufacturing shop floor...what sort of journey are they going to have with you to prove themselves over time to gradually solve many of these very ambitious problems? I mean, you describe them pretty eloquently, but they're different in each factory, like you pointed out. And we're dealing with operators, some of whom are very advanced and have taken all kinds of industry 4.0 courses and others who have not. So this is a bit of a journey. ARUN: Yeah, it is a journey, but there are similarities in this journey. If you think about maintenance of the equipment, it used to be a stronghold of those engineers that are sitting somewhere, and they get to the equipment when there is help needed. Look at where we are now. With operator asset care, we are empowering the operators to own that equipment and drive it. So that is the same journey that we have to go through from the digital side. And the key is, first of all, making sure that we have platforms like Tulip and others that help us to be able to quickly develop those apps, of course, in a very consistent framework. Especially for us when we are in a regulated industry, some of those framework and validation things become extremely critical. How do you set those boundaries? The second thing is educate the operators so that they feel empowered that they own the work that they are doing, and they can shape it in the way they need to do it and to continue to train them. And then the third level is to really train the rest of the organization. The management and then the operations leaders all need to be digitally savvy to drive that and then see the value. So it is a journey, but you need to be very clear about why we are doing it and putting the operators at the center and helping them. The thing that is going to help us is this whole COVID pandemic situation. If you think about the digital savvy of almost the entire world, it has significantly improved. Every operator, whether we like it or not, yeah, they might not have a degree, but they know how to order their Uber Eats. They know how to use an app. So we are seeing digital literacy coming up very fast. So this is a great opportunity for us to drive that transformation. But you're right; it is a journey. TROND: But you also mentioned regulated industry. I mean, to what extent can some of these apps kind of slide in between the cracks and do stuff that was never covered by regulation? And to what extent do you actually need to take very, very good care that you are, I guess, also updating the regulations and knocking on the doors of governments and telling them that "Look, there's an app for this too."? [chuckles] And we need to upgrade the regulatory framework to take that into account. So it seems to be a bit of both. ARUN: Yes, you absolutely hit the nail on the head. You need to do both. One is, first of all, have a good, robust architecture. That's why the platforms like Tulip will need to ensure that the architecture is robust so that it has enough control so that we can drive this validation and qualification, those things, and giving the parameters of the freedom for the operators within those constraints. And let's not forget cybersecurity, which is a huge thing, especially when we come to the OT cybersecurity as well. And on the other side...sorry. TROND: No, no, go ahead. On the other side... ARUN: On the other side, we need to continue with the regulators and work with the regulators to make sure that they understand what we are doing. We are now working with the regulators to educate them on real-time release. How can we actually use the data rather than having to produce these samples and batches as opposed to relying on continuous data that is coming that shows that your process is in compliance? So working on both sides with the framework so that it is robust as well as regulators to make sure that they understand how the technology is transforming. At the same time, the compliance is improving. Think about it, when you're doing samples, one, you're taking one sample from a batch. But when you're doing continuous sampling, you have the whole sample, whole product batch data you have in your hands. So we'll continue to work with them to make sure that the regulators are also coming with us on that journey. TROND: How is pharma 4.0 going? I mean, the acronym is the same as industry 4.0. Is 4.0 actually happening, or are we still in 3.0? ARUN: In pharma-world, I would say we still have 2.0 to 3.12 to 3.33. And there are some great examples where we have the 4.0 when I talk about what we are doing with the personalized solutions when we talk about how we are bringing IoT to the forefront, how we are doing real-time release with digital twins of our whole process. Now we have digital twins, even for bioreactors, which are very difficult to characterize. So yes, the journey is there. The key is to keep in mind why we are doing it to really make sure that we have the patients that are waiting for our products in mind and then really transform around to support them. So the journey is continuing. Yes, there are very good examples for pharma 4.0. But are we there yet? No. But is everybody working together to get there? Yes. TROND: Let's talk a little bit about this operator and the training of an operator because training the workforce is something I ask a lot of the people who come on this podcast about just because technology is one thing but training people on the technology to implement it in a fruitful way is a whole other challenge. What approach are you taking at the whole J&J complex when it comes to training your existing future and even training your ecosystem around you? ARUN: A couple of things there; one is, first of all, making sure that you start with the user experience in mind and design everything from there. So you need to start with the design aspect. The second thing is how do we make it simple? The more simple you make it, the less training. How many people are getting trained on how to use an iPhone? So really, how do we make it simpler? But actually, in the future, I'm thinking...and this I actually got from one of your podcasts, Trond, is, are we going to get to a point where there is no interface? So can we get our apps to a state where there is no interface, then your training becomes a lot more part of the evolution rather than you have to go; oh, now I need to learn this, and I need...no, it should be so intuitive. It's like gesturing with my hands. So how do I get to that state? Hopefully, that state comes in soon, as you've been discussing with some of them. But for me, it is really how do we keep on making it so simple that it becomes intuitive? And it starts with the design, where you put the operator at the center and design around the operator. TROND: Can we talk a little bit more specifically about the digitized supply chain? Because it is such a core to what you're up to. And I know that there are some characteristics that you care about the most one of them I think you mentioned to me was being very responsive. But what are the priorities when you are redesigning a supply chain? What are the kinds of things that are top of mind for you? And where do you start? ARUN: You start with the customer experience. How do we make sure that that is clear on how it is impacting the customer experience? Now to help with the customer experience, how do we drive that responsiveness in your supply chain so that you can respond very quickly to what is happening at the demand side, the customer side, and then link it back? Then the next one is really the resiliency. How do we build that resiliency in supply chain so that we can react very quickly? If there is one thing that COVID taught us is that resiliency in our supply chains actually helped the world in one way to survive this pandemic and continue to survive. So how do we drive that resiliency in the supply chain? TROND: What do you think about these very traditional concepts that have been part of...and, you know, you had the start of your career in automotive. Lean management is something that everybody wanted to copy, and the Toyota processes and a lot from the country you chose not to study in [laughs] essentially because you weren't convinced they were vegetarian enough. But anyway, what do you think about the heritage from lean and mixed in with some of the agile tradition from software? Is that altogether creating a new paradigm? And what does that look like, and who's describing it? If you would maybe describe where some of your influences come from when you are designing such a large organization around these principles. ARUN: At the heart, the lean principles and agile principles are still really valid. Like, if you think about lean, what it is saying is think about the floor, eliminate the waste, and continue to improve and zero defects as possible. So that mindset has to be there for us to even look at digital. What digital is doing is actually helping us to implement lean even faster. How do you get there? Now, from responsiveness, and we talked a lot about the responsiveness, and reacting, and resiliency that requires this agile mindset, this traditional boundaries of I'm going to go from plan, source, make, deliver. This is becoming a network. The only way you can survive in that network is having that agile mindset where we bring people together very quickly, get the problem solved, deliver that MVP, and don't look back and then move on to the next one. So the agile principles around bringing the teams together very quickly to focus on the key priorities and delivering on the MVP aligned with the lean thinking to make sure that there is no waste and we are really getting the floor done actually is a great combination of these two. And these are the two things that need to come together even for us to roll out the digital solutions very quickly in our operations. And COVID has been a great example if you think about how we came together to deliver a product for the instruments in a very quick way across the world in a virtual way. It has been a great example that shows that it can be done. So that's where the lean foundations and then the agile mindset are extremely critical, even for us to drive this digital transformation. TROND: If you think about how this was built, what are some of the best influences that help you along the way? We talked a little bit about startups that bring the app mindset and maybe some of the agile thinking. It doesn't necessarily come from startups, but certainly, it does exist with startups. Where are these industry practices that you are increasingly embodying at J&J? Where do you think they come from? ARUN: Actually, they come from many places. And for startups, really one of the places where we can actually see how their mindset is there in terms of test and learns, and learning from failure, and more. And even I'm looking at some of the journeys like how companies like Tulip are evolving as well. Especially those companies from a startup to accelerating phase, that's where we are seeing a lot of the learnings that we can learn. And one of the big things that we at J&J look at is how can we look at our CEO and saying, "Hey, we need to act like a 135-year-old startup."? So how do we actually look at it? And to your point, where we are looking for, we are looking for everywhere; one is really those startups. But more importantly, those startups that got that first phase and are now accelerating, that's where all the processes need to come together. And then, at the end of the day, we still have to be reliable. And we are in a regulated industry. So how do we make sure that the patient safety, product quality are the top priority and our processes are reliable? That's where the established companies also help us on how we continue to drive that. TROND: Yeah, because that's what I guess I wanted to drive to because there is an established idea in the established industry to look for industry best practices. And in the manufacturing space, there are these lighthouse projects. Companies on their own might have lighthouse projects that are especially good. And the World Economic Forum has lighthouse factories. In fact, they have designated places around the world where they have tracked and figured out that they are of sufficient quality to put up as inspirational lighthouses for others. What is your view on how well that works as a practice? For example, you have 100 sites. Is it possible to tell one site to become more like Site A? Because look at site A how well they're doing. Isn't that also a bit of a challenging message to communicate? ARUN: Yeah. TROND: No one likes to be like, all right, I understand. [laughs] My golf swing is not up to par, I get it. I need to look at my neighbor over here. It's not always a fantastic message. ARUN: [laughs] But speaking of that, actually, we have five sites that are lighthouse sites. And we have one that is going to come up with one of the projects that we're working on as well is in one of the sites with Tulip for the lighthouse site. But the thing is, knowledge grows by sharing. The more you share, the more you're going to grow the knowledge and the faster the adoption is going to be. You're absolutely right. It does not mean that just because this is a lighthouse site, they are at a pedestal, and then everybody else is in another place. I actually look at it the other way around. What did those lighthouse sites do that we can actually copy and paste, so I don't have to reinvent? And then I can focus on something else as well. So the lighthouse sites are helping us to really share that knowledge so that we can learn from one another. We can build on it. And then we eliminate the need for us to redo the things that they have gone through. But you're absolutely right; that doesn't mean that those are the only sites that are doing everything and everybody else is not. But sometimes, the copycats that are coming behind the lighthouse might be the best of things because they can get lighthouse practices and implement and then really show that they can actually transform their manufacturing operations much more faster. TROND: Well, and that's true in the history of manufacturing that you can actually leapfrog. It is still a field where if you do many things right, you definitely make a difference. I wanted to shift tact a little bit, Arun, and move to coming years. What are some of the industry developments that you are the most excited about? So we've talked generally about digital. We've talked about personalization. What are some of the things that are going to be most crucial to get right and even just like in the year ahead? It's been a very...it's been a wild ride in the last 12 to 15 months. What's going to hit us in the next year, and what are you focused on? ARUN: So let me break it into a few different areas. One is purely from the technology side of it. If we look at how 3D printing is going to evolve and how it is going to help us to change significantly, how the digital twin and digital threads that are coming up fast that we can actually connect. And then, more importantly, how the machine learning and AI models that are coming up that help us to be responding very quickly. So I'm very excited about those areas, how 3D printing is transforming our operations, how we are able to bring digital twins, digital thread, and machine learning to really drive that end-to-end thread all the way to the customer. The second area is, from a mindset point of view, is how resiliency and responsiveness has become kind of like a norm. If you think about the COVID pandemic, what it has done is how that resiliency and responsiveness has become a norm. So how do we actually drive that and don't lose that as we come out of the pandemic and then go forward? And the final one is I'm going to go back and harp on the culture side of it. How do we drive that culture where we let operators be empowered and learn from it and let them be the kings? And we also have the operator hashtag #operatorrules. And we support that culture change, the digital change, and which is really going to be accelerated because they are becoming more and more digital savvy. So there is the technology aspect. And there is actually the responsiveness. And finally, how do we drive the digital savvy across the organization? TROND: So my last question, and I don't know how fair that question is in the context that you're in, because I could imagine that given the amount of factors that are moving at any given moment, very long-term thinking seems perhaps a little farther away from your everyday life. Because there are so many things that could go wrong literally every minute. But if you permit yourself and me to think a little bit longer term, towards the next decade, are these things on the digital side, you know, digital twins, and AI, and machine learning, and 3D printing, as this decade moves to a close, are there other things on your horizon as well that will even more drastically transform the landscape? I mean, are digital factories going to be really coming into the scene and really transforming the way? Are we going to recognize a factory even in the next decade? Or am I kind of overblowing this, and things are just fairly complicated, and it's going to take quite a long time to shake out and integrate all these technologies with all of the workforce challenges and cultural challenges that you just pointed out? ARUN: Imagining the future, first of all, I really love the idea of almost no interface, intuitive use of technology. Can we get to that? That's one. The second thing is, yes, there will still be big manufacturing areas. Some of them are tied to the physics and biology, so we cannot change, but everything else can actually significantly change. And if you think about can we actually do a factory in a box very quickly for vaccine production in a developing world that cannot afford and we deploy it very quickly? So will we get to a point where it becomes more of Lego blocks that we can assemble very quickly and get it up and running and everything has an equal and digital model that we really don't have to worry about it? It is not about the digital twin of my operations. But if I take the digital twin of my patient's body and the digital twin of operations, think about how easy it is for me to actually respond to that personalized request or personalized medicine. Since you let me imagine and let my thoughts flow a little bit more broadly, it's really bringing the digital equivalence. So can I actually take my digital equal and to respond to the digital twin to get the personalized product for me either in a batch of 1 or even maybe a batch of 10 if batch of 1 is not possible? So the factories of the future, yes, some of them might not significantly change, but most of them will be that flexible way to bring them together for specific product or specific customer and being able to re-assemble very quickly to do something else. And then the intelligence, can it move to the equipment so that the equipment itself can rearrange itself based on the customer base? But then, what is the implication to the workforce? And what is the implication to the operators? So this way of getting those operators to be a lot more digital savvy and really helping to manage this complexity will be a great foundation. But at the same time, that is something that we all need to watch. Yes, all of this can happen. But we need to watch for how do we bring our people together? TROND: Yeah, and I could just imagine putting myself back in my old government days, scratching my head about self-regulating systems in the medical field, right? [laughs] ARUN: Yes. TROND: That would seem to be a little bit of a challenge as well. So there are so many interesting challenges. But it seems to me that even if you are occupied every minute with operational challenges and even just digitizing a supply chain without fundamentally changing its logic, it's going to take all men and women on deck. It's a cultural challenge. It is not just a technology challenge. ARUN: Absolutely. It is. It is a cultural challenge. TROND: Well, look, it's been fascinating to hear, and I hope I can check back in with you. It seems to me that if we had had this interview just even just 15 months ago, some of these challenges might have looked a little bit less rosy, and we wouldn't have been discussing about the next decade. I'm assuming that a lot of things for you in your business have really, I guess, opened up throughout this pandemic. Is that right? ARUN: Yeah. TROND: Some of these opportunities just weren't there before. ARUN: Absolutely. A lot of the acceleration...first of all, we are privileged to serve our patients. And we have a big part in helping the world get through the pandemic, our vaccine. And even how we have brought in digital twin into our vaccines in a very faster way was enabled by the pandemic situation. The whole digital acceleration of some of our solutions that were sitting on the shelf for almost six to nine months, the demand for them grew up within the first few months of the pandemic. So the digital acceleration of our operations has happened. The third thing, as I said earlier, is the digital savvy of our day-to-day citizen is helping us to bring these much more faster to our patients and customers around the world. TROND: That's a very interesting statement. Because when you cannot innovate faster than your end client, then you're really dealing with the total ecosystem here. You actually depend on your end client to be caught up with all of these technologies. It's a fascinating challenge and probably very important too because there isn't a little bit of an insurance policy there, no Arun. Because if you cannot be more advanced than your end user is, at least you have the time to, or you have to take the time to educate the end user and get their real feedback on what needs to happen. So that leaves me on an optimistic note, and if you have any last statement...I certainly thank you for your time. And if you have a last challenge, you know, there are so many challenges where you could launch, but if you think to your fellow industry executives, what is the one thing maybe you want to leave them with what you think is a shared challenge that people should focus more on in industry these days? ARUN: Keep the operator at the center #operatorrules. Let's make sure that we empower them. We help them to be as digitally savvy as possible. That will actually help us to move these needles much more faster. TROND: Arun, I thank you so much. It's been a pleasure. And I hope I can invite you back someday. ARUN: Definitely. It has been great, Trond. TROND: You have just listened to Episode 43 of the Augmented Podcast with host Trond Arne Undheim. The topic was Digitized Supply Chain. Our guest was Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson. In this conversation, we talked about why J&J puts operators at the center of its strategy. My takeaway is that operators are the key to the next phase of industrial evolution that which involves the deep digitalization of manufacturing, its supply chain, the production capacity, personalization, and with that, the reinvention of factory production itself. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 21: The Future of Digital in Manufacturing, Episode 27: Industry 4.0 Tools, or Episode 10: A Brief History of Manufacturing Software. Augmented — conversations on industrial tech. Special Guest: Arun Kumar Bhaskara-Baba.

Gardening with Ben
A busy weekend at the allotment garden and Pollen Market in Sheffield

Gardening with Ben

Play Episode Listen Later Aug 21, 2022 14:41


Join Gardening with Ben as he talks about A busy weekend at the allotment garden and Pollen Market in Sheffield. Find out what he has been purchasing for Spring!!!Support Gardening With Ben- Subscribe to our podcasts to stay notified of new episodes.- Check out our merch shop where we have some fantastic gardening hoodies and t-shirts:-www.gardenandallotment.com/shop- Why not check out 2nd Gardening Podcast Channel called Gardening and Allotment Tips:-https://open.spotify.com/show/5WkDHSwgDbEnKDW00dXDiF?si=c3f0090c89ee48a5

The Friendly Bear
226: Jack Pitts - Tulipmania History & Dutch Tulip Bulb Market Bubble Recent Parallels

The Friendly Bear

Play Episode Listen Later Aug 20, 2022 10:21


Episode 226: This is a clip taken from the full episode with Jack Pitts on March 15, 2022. In this clip, Jack talks about use cases of Tulips during Tulipmania and goes over history during that time period regarding the Tulip euphoria. Social MediaJack PittsTwitter: equitydiamondsLinkedin: John "Jack" PittsSLicktionary.com

Karen & Kayleigh are Here for the Right Reasons
Will you accept this tulip? Bachelorettes Season 19 episode 6

Karen & Kayleigh are Here for the Right Reasons

Play Episode Listen Later Aug 18, 2022 51:03


Join Karen & Kayleigh for a recap and review of episode 6 of the latest  BacheloretteS season.  We see some favorites go home this week just ahead of hometowns visits.  Mourn their losses with us this week-- we can always hope to see some of our faves on the upcoming Bachelor in Paradise season.  RIP Nate, Spencer, and Ethan.  we hardly knew ye.

Augmented - the industry 4.0 podcast
Episode 93: Industry 4.0 Tools

Augmented - the industry 4.0 podcast

Play Episode Listen Later Aug 17, 2022 46:27


Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In episode 27 of the podcast (@AugmentedPod), the topic is: Industry 4.0 Tools and Analytics. Our guest is Carl B. March, Director, Industry 4.0 at Stanley Black & Decker.In this conversation, we talk about what industry 4.0 means, the importance of upskilling the entire manufacturing industry, and the lessons from Stanley Black & Decker's digital transformation journey.After listening to this episode, check out Stanley Black & Decker (@StanleyBlkDeckr): https://www.stanleyblackanddecker.com/ as well as Carl B. March's profile on social media: https://www.linkedin.com/in/carlbmarch/ You may want to also be aware of the 'Israel meets New England' smart manufacturing event on June 9 and its organizers, the Israeli Trade Mission and Amhub New England:The New England Advanced Manufacturing Hub (AMHUB NE): https://mfg.works/amhub/amhub-new-england/The Government of Israel's Economic Mission to North America: https://embassies.gov.il/washington/AboutTheEmbassy/Pages/Economic-Mission.aspx#:ISRAEL meets NEW ENGLAND: Advanced Manufacturing in Factories and Workplace: https://mfg.works/israel-meets-new-england/Trond's takeaway: Industry 4.0 requires a mindset shift, not just technology adoption. It's not just about you--whether you in this case is a big company or a top leader--rather, it is about bringing people, partners, SMEs, and the entire ecosystem along. To do so openness to learn, having a strategic roadmap so not chase all shiny objects, and investing in lighthouse factories that can illuminate the possibilities are each important ingredients.Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 20, The Digitalization of Körber, episode 14, Bottom up and Deep Digitization of Operations, and episode 9, The Fourth Industrial Revolution post-COVID-19. Augmented--upskilling the workforce for industry 4.0 frontline operations. Transcript: TROND: Augmented reveals the stories behind a new era of industrial operations, where technology will restore the agility of frontline workers. In Episode 27 of the podcast, the topic is Industry 4.0 Tools and Analytics. Our guest is Carl B. March, Director Industry 4.0 at Stanley Black & Decker. In this conversation, we talk about what industry 4.0 means, the importance of upskilling the entire manufacturing industry, and the lessons from Stanley Black & Decker's digital transformation journey. Augmented is a podcast for leaders hosted by futurist Trond Arne Undheim, presented by Tulip.co, the frontline operations platform, and associated with MFG.works, the manufacturing upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9:00 a.m. U.S. Eastern Time, every Wednesday. Augmented — the industry 4.0 podcast. Carl, how are you today? CARL: I'm doing great, Trond. Good to see you. TROND: Yeah, this is fantastic. We've spent a lot of time together, Carl. We've gotten to know each other. This industry 4.0 is bringing us together. CARL: Quite a bit. And there's so much going on in this space, especially here in New England. So it's an exciting time. TROND: Yeah, for sure. Carl, I wanted to talk a little bit about you and your background. You're an engineer. And now you're deeply steeped in industry 4.0. Maybe I'll just ask that question, why did you become an engineer? And how did you end up where you are right now? Was it an obvious path for you? Or did you always want to go into manufacturing? CARL: I guess from the beginning, I was always a tinkerer, so just growing up and hanging around mechanical equipment, my desire was always to break and fix. [laughs] So eventually, I got wind of a teacher who, in fact, was my music teacher. And he asked me what did I want to do? I said I wanted to break and fix equipment and all of these things. And he said, "Well, you want to be a mechanical engineer." [laughs] So I kept that with me from maybe nine years old, and that's the path I went. Eventually, I did my first degree in mechanical engineering. And then eventually, I did an automotive systems engineering graduate degree. TROND: Wow. And so then, in the beginning, you were headed for the automotive industry. CARL: Yeah, yeah. It was always a desire around cars. So my father had all the cars that needed to be fixed. And where I'm from, we're in the Caribbean. I'm from Jamaica originally. It was one of those luxuries that you had where you just dispose of your vehicles once they start giving some problems. So we fixed the cars. [laughs] That's what we had to do. TROND: [laughs] So you ended up with a bunch of cars then, not just fixing them, but you ended up with a bunch that are not used. CARL: [laughs] Exactly. And taking parts from one and putting on the other. [laughs] TROND: That's funny. That's funny. Well, so you did that for a while. And you were in automotive, which is an exciting field in and of itself. And then you went into consulting for a bit as well. So you've done a little bit of that. CARL: And so the interesting thing is once I did my first degree, which was mechanical engineering, I had the opportunity to start working in the manufacturing environment. And I actually started off in mining and refining. So I was in alumina refining for a while, and then I went back and did the automotive degree. And then, coming out of that, it was the wonderful time in Detroit where everything was a bit uncertain. So though I started off in automotive there, after that degree, I went back to my roots of reliability engineering, which is more along the lines of operational excellence in the manufacturing environment. TROND: You know, it's kind of fascinating today because automotive has gone full circle. CARL: Yes, it really has. TROND: It's like, nobody...who would have guessed [laughs] that automotive was going to go from glory days to, like, it's all over to a renaissance of mobility? CARL: I've gotten the opportunity to observe that, especially as a consultant, as I eventually went into consulting. More than half of my 20-plus years in manufacturing has been in the consulting space. So, while consulting, that's where I really started to see many sectors, from the very advanced sectors in aerospace and automotive down to what we call base materials, which is going back to the dirt, the mining and refining pieces. And just seeing the range of technology adoption across all fields as it relates to operational excellence was an eye opener for me. And when I think about this topic of industry 4.0 which really it's not an old topic. It really came about in 2011 or so, which was the mid of my consulting career. And that's when I made a pivot in my consulting, where I started to focus a lot more on the technology enablement within these respective spaces. TROND: Well, let's dig deeper into it. Because you're indeed, you know, you're with Stanley Black & Decker. You run a lot of their industry 4.0 activities, especially on the analytics and the value stream side. But let's get into the topic more because, as you said, 2011 is not a long time ago. And I hear industry 4.0, by the way, seems to be more of a European term than an American term. Here it's like smart manufacturing because manufacturing is the main thing. But at Stanley, you guys somehow chose the international term industry 4.0. Why don't you, for the benefit of all of us, just tell us how you define it? What is -- CARL: So industry 4.0 is this terminology referring to the fourth industrial revolution. So it stems back to the first industrial revolution having to do with mass production and steam being used as a driver. Then eventually, it went into the second, where we started to get some computers in the space and started to be able to take advantage of some of those things. The third having to do more with automation. So we started to put a lot more robots and robotics within the manufacturing space. And interestingly, then we started to do a little bit more sensorization. But in the 2011 or 2010 period of time, that's when we started to make a lot of advances in big data, cyber-physical systems. So that's where those applications started to come into the manufacturing environment, AI, artificial intelligence, anything related to analytics in the manufacturing environment. That's where we're starting to consider the industry 4.0. And one other thing, there are probably three main elements that differentiate the fourth industrial revolution from its predecessors; one is vertical integration. Vertical integration is what we call from the top floor to the shop floor. You're able to pass data back and forth and get information on what's happening at any given time, at whatever level it is in your production process. The second is horizontal integration. And that's where you start to look across your value chain. So you're looking at data coming from your supplier, and data coming from your customer, and data within your own manufacturing environment. And then the third one is integrated product lifecycle. So this is one of the most interesting pieces of industry 4.0 in that you're actually getting feedback, even though the customer doesn't even know you're getting that feedback. And you're getting feedback into your product lifecycle and your product design. And you're designing it to manufacture well, and you're designing it to basically fulfill the purpose of the end consumer, so all of that feedback loop that's taking place there. And what enables it is a part of what we refer to as industry 4.0. TROND: That's super interesting. And can you comment a little bit on how that translates then into Stanley Black & Decker's digital transformation journey? Because, arguably, and I meant to have it here, I have, you know, I have a bunch of tools in my arsenal. [laughs] I might actually run and go get that. But they weren't always digital; mine happens to be battery operated. And hopefully, I can run and get it in a second; I really wanted it in this tape. But it has been a journey for you as well, and I guess it's a continuing journey because sensors and all that stuff take quite a bit to transform an entire kind of suite of products into a set of connected arguably industry 4.0 tools. So I'm curious, where would you say you guys are in that transformation process? And how ready is the world for a fully sensorized reality where everything is connected? I guess the maximal vision of industry 4.0, which is this idea of industrial Internet of Things where everything is starting to connect and yield analytics. Because you took the...these are also difficult things to do, right? The vertical integration, all of these things are difficult. But this full vision, we are a step away from that so far, this full sensorization. CARL: Yeah, it has not all become a reality as yet. And as you can imagine, the maturity is going to be different depending on the sector, the industry that you're dealing with. But if I was to look back for a second on the journey that we've had at Stanley Black & Decker, I joined the company maybe about three years ago when we made a very interesting pivot in the way that we were approaching industry 4.0. I'll speak on that in a second. But prior to that point in time, Stanley Black & Decker has always been an innovator in this space. We do make tools, and we're the number one tools company in the world. But we also serve a lot of our other businesses, automotive and aerospace, in particular, in providing fasteners, et cetera. And as a result of this diversity, it made sense for a company like ours with 100-plus sites to be able to start working in smart manufacturing. And the process was that there were a couple of chosen sites that were given a bit more license to integrate industry 4.0 elements within their four walls, and they were referred to as lighthouse factories. So it was very decentralized, not very organized from the standpoint of having certain standards that would scale well. And this is where we started to see a lot of productivity gains, efficiencies within those sites. Then in 2017, we did a study internally and determined that let's go after this in the right way, which is to organize ourselves to have a program. And as a result of organizing this program, that's where I came in as one of the first few hires within the program to centralize what we're doing. And then, I ended up leading our analytics value stream. We also had value streams related to connected factory, automation, et cetera. And that's where we started to go after it in the right way. And I think as a result of that, the gains that we've had and the learnings that we've had over the past three years have been tremendous. And if you compare this to the typical approach, especially that I've seen in my consulting years, is that there's a term that was coined by either McKinsey or the World Economic Forum, I can't remember now, called the pilot's purgatory. A lot of companies I observed they'll start something. They'll start one use case here, another use case there, nothing linked. And they'll do some form of pilot, but it never scales. It would fizzle out in some way. Somebody would move on from one role to the next. The interest isn't there. So, as a result of that, they will continuously stay in the same place, and there will be no roadmap for movement. TROND: And how do you avoid that destiny of the pilot purgatory? There are many theories on how to do that. And I would say probably every manager of some seniority would say, "Yeah, yeah, I know about that issue, and we don't have that issue here." [laughter] CARL: But if we're honest with ourselves, it's very easy to fall into pilot purgatory because, first of all, it is very easy to move after the first shiny object or the next shiny object that catches our eye. That's just the way human nature is. One of the things that we've learned is the value of having a strategic roadmap and especially related to industry 4.0. So one of the things that I'm currently working on with our small to medium size enterprises, small to medium-sized manufacturers is we're trying to enable them with two things, one is to assess yourselves. And we are currently using a framework from Singapore called SIRI, which is Smart Industry Readiness Index. We're making that available to our small to medium-sized enterprises for us to work with them on assessing where are you with respect to these 16 dimensions of industry 4.0? And you don't need to be at the very top band for any one of these, really. You need to look at where you are with respect to peers, with respect to the best practices, and with respect to where you need to be to meet your business objectives. So once we do the assessment, we are able to filter that out in terms of what should be prioritized on the strategic roadmap. The second thing that we're offering is given what we've done so far; we have a wealth of experience in this space as well as what we've gathered in terms of partners who have been giving us use cases that can apply to these 16 dimensions. We're then able to work with the manufacturer to specify this is what your roadmap should look over the next three to five years if that's your planning horizon. You focus on these elements first, these dimensions first, but more specifically, these specific use cases. And these use cases are foundational. These use cases will provide you with some return that will help to fund the rest of your program, et cetera. So I think those two things between the assessment and having a strategic roadmap are critical enablers to avoiding this pilot purgatory. TROND: That's fantastic. We'll talk a little more about SIRI hopefully later because it relates to the work you and I are doing with the World Economic Forum and our AMHUB network. And we are hoping to bring it in really to play in New England, you know, across the sector. But before we get to that, I wanted to ask you a couple of questions about this physical manufacturing 4.0 facility where I believe you actually work out of sometimes in Hartford, this, I guess, 23,000 square foot center. So it's a physical kind of advanced manufacturing center like its own little kind of demo factory and training center also, I guess, for your smart factory initiatives. How did that get started? Well, it's the middle of a pandemic. But what do you intend to use it for? And what were you using it for before the pandemic? Because I'm assuming you've had a quiet period like all of us. CARL: Yes, we have. We've had quite a quiet period over the past year and some. But in 2019, we opened the space, and what we actually did...I'm referring back to when we started to go about this in a different way in 2017. We had one of our...well, our key leader Sudhi Bangalore was, brought in from the outside to lead this program. And he was named the VP of our industry 4.0. Since then, he's been also named as CTO for global operations. But this was one of Sudhi's visions in that we would not only have the team to do this industry 4.0 enablement in a standardized and centralized way, but we would also have an innovation space that you can physically touch, feel, experience the elements of industry 4.0 all the way from automation. So you'll see the robotics. You'll see the automated mobile robots. You will see the automated conveyors, the machine centers all of these things, as well as data flowing back and forth and analytics being displayed. All these things were intended to be experienced because within our own factory and network; the expectation was that some of what we'll be trying to get to our sights would be new. And we wanted to make sure that individuals, especially plant leaders, would be able to come in and really feel and experience what good looks like. At the same time, it was also a vision of our CEO as well as our CFO to use the space within Hartford, and Hartford was chosen as a location for a specific reason because we wanted to work with the city. We wanted to work with the state around making Hartford some central innovation hub for New England and hopefully the nation. So that's where this space came into being. And we had a grand opening in April of 2019. So it was always intended for us internally, but it was always intended for the public in a measured way to be able to come in and experience it. And then finally, I'd probably say that in terms of what we're thinking going forward, we hope to get back into the space sometime soon. We hope to obviously reopen to manufacturers in the region. But then we also want to be able to utilize more of our partners as well, our technology partners, so that they too can show some of their solutions in the space as well. TROND: It's so important, I think, to emphasize that technology...well, because of the danger in the shiny objects that you just addressed before that, it is precisely for that reason because when you have this experiential sense of what the technology can accomplish, and on the shop floor, there is so much of that right? Robots. It's very visual and tactile. You can clearly much more easily see how you could adopt it. So it sounds quite important to have a demo factory like that. CARL: Absolutely TROND: What do you think is the path forward? So you said you guys are engaging with a bunch of different actors that are not your obvious partners. You're engaging with SMEs in a deeper way than before. You have startup engagements but at a very early stage with the STANLEY+Techstars Accelerator. So you're engaging with organizations that are very different than the mothership. Why do you have such a distributed strategy? CARL: So, I think a lot of this comes from the innovative culture that we live in. We recognize that innovation comes from many places, disparate sources. And we recognize that we won't know everything. We don't know everything. And especially when we're trying to break new ground, we need to be able to tap into all the resources that we can in order to do so and in a relatively efficient but also agile and quick way. So a couple of years, probably also coinciding with the 2017 time period, we started working with a group called Techstars. And as some might know, Techstars is an international organization that basically incubates relatively new startups and helps them along the way. And there's some partial investment, generally, with the program. But our first round of investments in Techstars was companies that were focused on additive manufacturing. The current round, which was just completed maybe a few weeks ago, a couple of weeks ago, had cohorts that were related to artificial intelligence, analytics mostly. And we had a couple of robotics ones in there as well, local robots, which all of this is really to ensure that we're able to keep our pulse on everything that's going on. So to your earlier question about the shiny object, noticing the shiny object is not a bad thing because you have to keep your pulse on what's going on. And as people innovate and as more and more people enter the space and as more things are democratized and commoditized, you want to make sure that you're able to pull in what's needed at any given time. So that's what we've been trying to do in different ways within our industry 4.0 program, specifically within our Techstars program. And then, we also have another group called Stanley Ventures, which also directly invests in some startups as well. So we're doing it on multiple fronts. TROND: That's interesting. I wanted to get into the learning aspect. And maybe the humbling part here is both for you and I, and I'll speak for myself, but we're expected to both be experts on industry developments and then simultaneously be evangelists for the same, which is sort of to intermix roles in industry always. But it's complicated. How do you feel like you are able to stay on top of all these things? Because it's one thing as a company, as Stanley, to have all these investments to have all these things available, theoretically, that you could pull from. But then, now as an individual, I just wanted to address how you, just to take that as an example, how do you engage? Because you and I are both engaged, and we're supposed to be those leaders. And we are building networks that we'll get into in a second that are helping us do that. But how do you reflect around your own ability to cut this balance between looking at all the shiny objects, making sure you don't miss any of them, and then advising not only your company and implementing stuff but then also being an advisor to the general ecosystem about what is worth looking at and where are things in the maturity scale to keep everything kind of calibrated? CARL: Yeah, and it can be difficult. And that's where we have to strike a balance. When we started off our program, we recognized that we couldn't build everything internally. So we had to rely on a robust partner ecosystem, probably having somewhere close to 30-plus different partners doing any one given thing at any one time. And then the learning that we got from that was that as a result of that, we were able to get further quicker. We were able to understand a little bit more about the space and what's truly revolutionary and what isn't. And then we've recognized over time that we still have to have some portion of our time still spent evaluating what's new and coming out. We're able to do that because we are organized in a way to do that, and we have processes around that. And we have individuals who are more focused on innovation versus deployment. And we're probably able to do that because we're a larger company. And this is just how we're set up. Now, the concern that we have for manufacturing, in general, is that the majority of the space is made up of small to medium size enterprises, which don't have this luxury. They have very few individuals. TROND: I mean, it's just not possible. CARL: It's not possible for them to do it, which is why we've made the pivot and said to ourselves if we're trying to uplift the entire system, and as they say, a rising tide lifts all boats, right? If we're to uplift the entire manufacturing sector and manufacturing ecosystem, we need to focus on those who make up the majority of it, which is 95%-plus small to medium-sized enterprise. And we can filter through some of the noise for them. And how we do that is provide a consolidated technology map against a framework so that they don't have to go through the filtering and figuring out what's good, what's not, how much is this going to be worth to me, et cetera. Because we've actually done some of that on our own. And then we just provide to them that based on where you are and your dimensions that you need to focus on, these are the four or five use cases for that specific dimension. Now, let's talk through and filter. Let's cut to the chase here; how much will this be worth to you? What will be the return on your investment based on what this costs and based on what it will give back to you in terms of impact value? And I think being able to assist in that way I think is critical to getting everyone else a bit more involved in industry 4.0. TROND: Yeah, and to that point, you and I are both engaged in...so one of those 30 partners, I'm assuming you would count the World Economic Forum as part of those. And you and I are both engaged in the advanced manufacturing platform there and a bunch of initiatives. CARL: Absolutely. TROND: We're not going to cover all of those, but there's one in particular that you and I are responsible for here in New England, which is the Advanced Manufacturing Hub, which is a global network of organizations which were the forum itself, which also started out with a centralized organization of the largest firms. So the likes of Stanley Black & Decker in all fields have realized a version of the same thing that you were saying that if the entire world of industry is going to really take up industry 4.0, they also need to work in a distributed way. And these networks that we have joined in with...well, maybe you could just give your version. What do you think AMHUB New England is and should be doing? And what are some of the things you are excited about that we are starting to launch here? Because it's very new. It got picked up last year, launched under the worst [laughs] possible conditions during a pandemic. I mean, launch a social network during a pandemic, and you will realize what a tricky task is. But anyway, we're in year two. We're into it. There's still a pandemic, and we're doing some virtual events. What are you excited about? AMHUB New England, what is it to you? CARL: I think the wonderful thing about the network is that we're not the first ones going at this. This is an ever-expanding network within the World Economic Forum. And everyone knows the World Economic Forum like you said, is a collection of all the leaders of the top companies. And then we're focused on the manufacturing space. So we're talking about the top manufacturers in the world coming together and trying to figure this out. And the Advanced Manufacturing Hubs, I think we're probably close to 13 or so now in the network. It changes numbers every now and again, but we're not the first, and we've definitely had the opportunity to learn from some of our predecessors. We've had others in the U.S. that have been at this for a couple of years before we have that we're learning how they've integrated with public organizations, so integrated with the county and the state and non-profit institutions in the region to be able to go after their objectives. So that's one of the things that we're obviously trying to do: bring public organizations and get them involved along with the private. We've also recognized, and I think we've had a passion within our own group here around upskilling. We recognize that this is a critical factor for enabling manufacturing in our region. We need to not only deploy and get new technologies, but we also need to upskill our workforce to meet the demands of these new technologies in our environment. So from my perspective, Trond, we have a lot of work to do. We, fortunately, have a lot of manufacturers, most of them small, within the region who are interested who are enthusiastic about what the path ahead of us looks like. And I think within the next couple of months, or next few months, as we continue to engage that community, we will be able to provide them with more opportunities to upskill and get to where they need to be with respect to their workforce. TROND: Yeah, and it's fascinating. I mean, you said the World Economic Forum has a bunch of related activities. But it's also true, and I just interviewed someone (That's a podcast episode that's actually coming out this morning.) who's on the panel that you are on, Michael Tamasi, as well so about manufacturing in New England. Because clearly, there's an established network and ecosystem here already we're building on. And this happens, I think, in all of the New England states and Connecticut, for sure. You and I have been engaging with some of the actors there. There are trade associations. There are state and federally-funded organizations like the MEP system and various other kinds of manufacturing networks. So from my point of view, it's not substituting for all of this. It's just partnering with all of them and just trying to join the efforts that they're already doing but from the perspective of a global picture. So it's getting, hopefully, if we succeed, the best of breed essentially making sure that all of the activities that we are putting on make local sense here in New England, showcase New England, so there's a showcasing aspect of this, and we have a lot I think to be proud of. I mean, there's Stanley Black & Decker, clearly a behemoth really in industrial tech and in the manufacturing sector worldwide, but there are a lot of other companies also startups contributing and making headway, and then we have a lot to learn. I wanted to maybe just discuss for a second this event that we're putting on in June here on Israel meets New England. What do you think is the attraction of having two regions meet? So, in this case, it's Israeli startups. But in other events, we might bring in, like you said, the SIRI folks from Singapore who you're working with to measure progress and benchmark in the field, or we could collaborate with even with Michigan, which is another major, major U.S. manufacturing hub. Or it could be Italy or Spain and many of the other networks that exist worldwide. What do you think the attraction is to gain that kind of regional cohesion? CARL: I think over time, we've recognized that gone are the days when we think innovation is restricted to a particular country or a region or anything like that. I think we're very much aligned on the fact that technology and innovation in the industry 4.0 space is not restricted. So it makes sense that when we think about sharing of best practices that, we go all over the world, and that's part of the reason why if you think about the World Economic Forum, it has a global network of advanced manufacturing hubs. Each hub may focus a little bit differently on slightly different topics. Some will overlap, but they are also tapping into the expertise and the ideas from their local regions with the intent that we will go across regions and share with each other. So this upcoming event, I think, is a wonderful one sponsored by the Advanced Manufacturing Hub here in that it's allowing us to see a couple of...or have a conversation with a couple of innovators from another region, and in this situation, it's Israel. But in the future, we will use other regions as well to bring them in, hear a little bit more about what they've been working on, what has been important in their region, which might be slightly different from us, and then have a bit of discourse between us around what the future holds for technology and innovation in general. TROND: Well, let me profit from that segue into the future. What is next for you in the digital factory? And what does the next decade look like for you in terms of, I guess, your own business-connected industrial tools, perhaps? You're very, very engaged with the networks and the maker movement. And broadly, your thoughts in industrial tech and where that's heading, and maybe even some comment on this upskilling challenge that you mentioned, I mean, what will happen to all of these things? It's a mixed bag of challenges that they're all somewhat related. You can't have progress in technology without the skilled labor force and all that stuff, and somewhat dependent on technology development. But what do you see happening here? Are we entering at least at the very least a decade where manufacturing will leap forward somewhat faster than it has done before? Will it start to change this impression that manufacturing is hard and difficult and we're dealing with a slow-moving kind of system? Or do you see that that's going to still be the case? CARL: I'm quite optimistic. I think based on what I've seen at least in the past three years, I think, the way that manufacturing has moved, it gives me optimism that there will be a significant leap in what we're doing going forward. It took a little bit of time, as I said, from 2011 till about maybe 2016-2017, for people to start to really gain a certain amount of interest and get past a bit of skepticism. At this point, there are enough proven use cases across the board that individual companies and individuals recognize that this is not just a shiny new object or fly-by-night use case. These are things that are here to stay and will be critical to business going forward. So I think as a result of that, first of all, there will be quite a bit of acceleration of efforts. The second thing is we decry the pandemic and its effects and everything else. But I have to say that there are certain mindsets that have been shifted as a result of the experience. There's more of a need and interest around being able to monitor your remote operations. So now people are more interested in connectivity than there were before. They're more interested in insights and analytics than they were before. Because now they can't necessarily be by the machine, by the production process, by the production line 24/7 or 24 hours a day. But instead, they can benefit from all of these technologies that will allow them to get the most out of their equipment. They also recognize how important the workforce is. We always decry automation has taken away jobs, but I'll say no; in fact, the studies that have been done show that those who lead in innovation actually also have an uptick in workforce of some 50% instead of the opposite, which is what the myth would typically tell you. So all of these things coming together, I think, will help us move forward quicker going forward. And then the third piece that I will mention finally is around upskilling going forward. It's absolutely critical that we upskill our workforce. In the U.S. for many years, and we've seen the charts and the data around the amount of retiring workers in the manufacturing sector, so we have a lot of skills and knowledge that will be leaving manufacturing and have already left. So to replace those individuals, we need individuals of the younger demographic who will, one, come in with knowledge of processes. But the ones that are coming in they're not interested in our grandfather's factory. They're more interested in what can I do differently in this space with the use of technology and innovation to do twice as much work in half as much time? Which is a good thing. We want them to come in with that mindset. And I think with the advancements in technologies; we will be able to do that. But what would be critical is to be able to upskill them, give them the right skill sets around these technologies, around the production processes as well as there's going to be a tremendous amount of marketing and PR to get folks interested in manufacturing. Because manufacturing is a very exciting sector. It's buzzing, and it actually has quite a lot of open jobs, frankly, that need to be filled, but we need to upskill individuals to fill those jobs. TROND: You have just listened to Episode 27 of the Augmented Podcast with host Trond Arne Undheim. The topic was Industry 4.0 Tools and Analytics. Our guest is Carl B. March, Director of Industry 4.0 at Stanley Black & Decker. In this conversation, we talked about what industry 4.0 means, the importance of upskilling the entire manufacturing industry, and the lessons from Stanley Black & Decker's digital transformation journey. My takeaway is that industry 4.0 requires a mindset shift, not just technology adoption. It's not just about you, whether you, in this case, is a big company or a top leader; rather, it is about bringing people, partners, SMEs, and the entire ecosystem along. To do so, openness to learn, having a strategic roadmap so not chase all shiny objects and investing in lighthouse factories that can illuminate the possibilities are each important ingredients. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 20: The Digitalization of Körber, Episode 14: Bottom-up and Deep Digitization of Operations, and Episode 9: The Fourth Industrial Revolution post-COVID-19. Augmented — upskilling the workforce for industry 4.0 frontline operations. Special Guest: Carl B. March.

The Cast That Ends Creation
The Cast That Ends Creation Episode 160 - Dan Lee of Tulip

The Cast That Ends Creation

Play Episode Listen Later Aug 16, 2022 33:24


In episode 160 of The Cast That Ends Creation, I interview Dan Lee of Tulip! https://tulipgrind.bandcamp.com/ https://www.facebook.com/tulip.mpls/ https://twitter.com/tulipgrind https://tulipgrind.bigcartel.com/ https://www.instagram.com/tulip.grind/ https://www.youtube.com/channel/UCVElsGGZK5t0rxMRL5JgagA - - - https://www.youtube.com/thecastthatendscreation https://www.facebook.com/thecastthatendscreationpodcast https://www.instagram.com/thecastthatendscreation https://www.twitch.tv/thecastthatendscreation https://www.twitter.com/thecastthatends https://thesoundthatendscreation.bandcamp.com

Predestination on SermonAudio
Election and Evangelism

Predestination on SermonAudio

Play Episode Listen Later Aug 16, 2022 59:00


A new MP3 sermon from TIME in the Word Ministries is now available on SermonAudio with the following details: Title: Election and Evangelism Subtitle: TULIP and Evangelism Speaker: James Moore Broadcaster: TIME in the Word Ministries Event: Sunday Service Date: 8/14/2022 Bible: Ephesians 1:3-14; Romans 9:10-24 Length: 59 min.

From Corners Unknown
#238 | Reviews and Other Rambles: Rigorous Institution, Hermit Knight, White Ward, Sunrise Patriot Motion, and More

From Corners Unknown

Play Episode Listen Later Aug 15, 2022 115:49


Reviews and other rambles about the latest releases from Labyrinth of Stars, Tulip, Cloud Rat, Gonemage, feth, Smug Anime Face, Rigorous Institution, Hermit Knight, White Ward, and many more.Continue reading

Mathcast
Mathcast Episode 84: 8/10/22

Mathcast

Play Episode Listen Later Aug 15, 2022 93:01


This is the 84th episode of Mathcast, in which we discuss new releases from The Wind In the Trees, Tulip, Artificial Brain, Mico, Fromjoy, a somewhat new release from Sleep Torture, and debrief on Mathcore Index Fest 2022. The Wind In the Trees: https://twittbaltimore.bandcamp.com/album/architects-of-light Tulip: https://tulipgrind.bandcamp.com/album/derangement-exquisite-tenderness https://www.youtube.com/watch?v=ZdsPz4cjq1c Artificial Brain: https://profoundlorerecords.bandcamp.com/album/artificial-brain Mico: https://micolandia.bandcamp.com/album/zigurat Sleep Torture: https://sleeptorture.bandcamp.com/album/carrying-water-for-rats Fromjoy: https://fromjoy.bandcamp.com/album/away

You Bet Your Garden
A Fresher Look: Tip Toe Your Tulips to Spring Bulb Success

You Bet Your Garden

Play Episode Listen Later Aug 13, 2022 53:33 Very Popular


On this Fresher Look at an episode of YBYG Mike gets your bulbs ready before the Winter- for success in the Spring! Plus your fabulous phone calls! Originally aired: September 2021

The Holy Spirit’s Curriculum Of Joy
David D'Andre TULIP-The Poisonous Flower Of Calvinism

The Holy Spirit’s Curriculum Of Joy

Play Episode Listen Later Aug 13, 2022 108:54


We hear David share his riveting experiences of how he got to writing his book and connections to A Course In Miracles. Here is the link for the book: https://www.amazon.com/Tulip-Poisonous-Calvinism-David-DAndre-ebook/dp/B0B834GBPS/ref=sr_1_1?crid=Q67U3UGO8INO&keywords=TULIP%20Poisonous%20Flower&qid=1659632884&s=books&sprefix=tulip%20poisonous%20flower%2Cstripbooks-intl-ship%2C100&sr=1-1&fbclid=IwAR05ld4WmcaSx4bnfsXE1yxr1RStoksoeGPaocELNSw5hBLHR9GkSyCNJYY

Grow, cook, eat, arrange with Sarah Raven & Arthur Parkinson
The Best of Autumn 2022 - Episode 80

Grow, cook, eat, arrange with Sarah Raven & Arthur Parkinson

Play Episode Listen Later Aug 11, 2022 40:23 Very Popular


Summer months are waning, and the prospect of darker evenings should encourage us all to bring light, colour and beauty into our gardens throughout the autumn season.That brings a perfect opportunity to dive into the autumn catalogue, and highlight the new varieties and beloved favourites which promise to enrich your space, whether bathing it in strong hues with some of the new Tulips, or filling it with fragrance from incredible Wallflowers.In this episode, discover:The huge array of standout Tulips, from productive perennial varieties to colourful collections perfect for potted plantingStaggering wallflowers with luscious fragrance, and how to make them last as a cut flowerWhich winter salads and edibles are hardy enough to give you so much through the cold months to comeA selection of delightful homeware, from the beautiful Ornate Candelabra, to the Squirrel-Proof Bird Feeder to keep the garden buzzing with wildlifeOrder Sarah's book: https://bit.ly/2TWHJczOrder Arthur's book: https://bit.ly/3xOov7HShop on the Sarah Raven Website: http://bit.ly/3jvbaeuGet in touch: info@sarahraven.comFollow Sarah: https://bit.ly/3jDTvBpFollow Arthur: https://bit.ly/3jxSKK5View all products mentioned and find further advice from Sarah: https://bit.ly/3f2DFiH

Tony & Henry: On The Same Page
So Let Me Show You Actually How We Do This, And How We Used To Do It, And How We Still Do It!

Tony & Henry: On The Same Page

Play Episode Listen Later Aug 11, 2022 72:59


Tony and Henry are back at Tulips for another live episode! Recorded on Juneteenth, they start off by honoring the holiday, and Opal Lee. From there they move to talking about black cinderella, queer baiting, and Tony identifying as thirty years old. They also celebrate Father's Day and Pride Month with a few touching moments. The Episode features interviews from artists, one with Amplify817 and one with Art Tooth. They give you the tea on their friend and artist Lou Charle$ and his festival that they attended the night before.  As Henry takes a bathroom break, their friend and fellow podcaster Robyn (of Corks in Cowtown) takes the stage to fill in and dish a little bit about her podcast. Once Henry gets back, the three of them discuss dating etiquette, meeting celebrities, friendships, and Robyn teaches the boys about pink tax. They close the episode out with a few personal funny stories! 

The Funky Panther
Live from Tulips (817 Day Pre-Show)

The Funky Panther

Play Episode Listen Later Aug 11, 2022 68:12


We are coming at you with a live recording from our favorite venue in fort worth, @tulipsftw.This is a little different than our normal show. We will be sitting down with 3 Amplify817 artists, getting to know them a bit better, and promote the upcoming 817 Day concert which is taking place at Will Rogers Auditorium on 8/17. In this episode, you will get to here interviews with Bencjones ( @bencjonesmusic ), Gr4nt ( @gr4ntofficial ), and Averi Burk ( @averiburk ). You may also notice that we have a Robyn of @corksincowtown (AKA Better  Chad, AKA Chad Thundercock) joining us since Chad skipped out and went to Egypt.So sit back, relax, enjoy and Stay Good!This episode is sponsored by @printedthreads Be sure to check them out for all your Screen Printing, Embroidery, Banners and More!CALL OR TEXT OUR HOTLINE AND LEAVE US A MESSAGE! 817-677-0408Fort Worth MagazineBest of 2022 - Radio Personality/Podcast (Reader's Pick) Show LinksThe Funky PantherMerchYouTube

Baby Giants Investing
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