Augmented Podcast

In episode 66 of the podcast, the topic is: Bridging the Physical-Digital Divide in Industrial Tech. Our guest is Rony Kubat (@kubat), CTO and co-founder, TulipIn this conversation, we talk about the complexity of the shop floor and programming a physical-digital environment. What does Digital Lean mean to you? What is augmentation? What's next in industrial tech?Augmented is a podcast for industrial leaders, process engineers and shop floor operators, hosted by futurist Trond Arne Undheim (@trondau), presented by Tulip (@tulipinterfaces), the frontline operations platform.Trond's takeaway: The physical-digital environment is no joke. When you speak with a real technologist who not only has imagined what the future would look like, but who is involved in building it, integrating software and hardware on the factory floor, you realize how difficult it will be to transform industrial work. It is not just about industrial tech, it is about people. It is not just about neat software, or fancy hardware. It all has to work together. And, more importantly, it has to fit into the overall context of what people are already doing.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 44, No-code for IoT in the Cloud, episode 47, Industrial Machine Learning or episode 29, The Automated Microfactory. The Augmented podcast is created in association with Tulip, connected frontline operations platform that connects the people, machines, devices, and the 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. You can find Tulip at Tulip.co. Please share this show with colleagues who care about where industry and especially 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:LinkedIn: https://www.linkedin.com/company/augmentedpodFacebook: https://www.facebook.com/AugmentedPodcast/Twitter: https://twitter.com/AugmentedPodYouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQAugmented--industrial conversations that matter. See you next time.  Special Guest: Rony Kubat.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. Scott Phillips, founder of i4Score, joins us in this episode for a deep-dive conversation about the journey towards a data-driven culture. We discuss the three big challenges small- to medium-sized manufacturers face when trying to adopt new technology; the core principles of Industry 4.0; and how to use technology to automate, autonomize, and augment. If you like this show, subscribe at AugmentedPodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 93: Industry 4.0 Tools (https://www.augmentedpodcast.co/93) with Carl B. March, or Episode 109: Augmenting Workers With Wearables (https://www.augmentedpodcast.co/109) with Andrew Chrostowski. 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: Industry 4.0 is indeed a journey, and there is a lot to potentially care about, a lot of places to start, and a lot of options that won't always lead firms to scale in a healthy manner. As long as the roadmap is owned by the organization itself, at least, the mistakes, which undoubtedly will be made, will be real lessons, not externally imposed. First among the challenges is to avoid transforming only to discover that you are yet again locked into solutions that you cannot fully make use of. Special Guest: Scott Phillips.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. Jim Huntzinger, President of Lean Frontiers, joins us in this episode for a deep dive into the lean business model and all things lean accounting. We explore value stream versus product costing, the importance of lean coaching, the principles of Toyota Kata, and how these strategies can drive processes improvement and product development simultaneously. Throughout the conversation, we examine the value of transforming traditional business practices and the potential impact on organizational decision-making and growth. If you like this show, subscribe at AugmentedPodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 108: Lean Operations (https://www.augmentedpodcast.co/108) with John Carrier, or Episode 84: The Evolution of Lean (https://www.augmentedpodcast.co/84) with Torbjørn Netland. 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: The lean business model is attractive to many manufacturing firms and still elusive to some of them, despite many examples of the principles in action popping up constantly. The business community should still spend more time on the interface between tech, logistics, and IT, and how all of that might interface with lean accounting. Strikingly, what we might think of as lean companies don't necessarily use lean practices across their business. Special Guest: Jim Huntzinger.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode, we’re speaking with Anna Waldman-Brown, PhD candidate in political economy and researcher at MIT. Our discussion dives deep into how manufacturers are automating welding processes, the role humans and robots will play in the future of the industry, and what these trends mean for small- and medium-sized enterprises in particular. We also explore the importance of collaboration between greener, tech-savvy automation engineers and the experienced shop floor operators whose skills and expertise are necessary to drive the production process. If you like this show, subscribe at AugmentedPodcast.co (https://www.augmentedpodcast.co/). If you enjoyed this episode, you might also like Episode 92: Emerging Interfaces for Human Augmentation (https://www.augmentedpodcast.co/92) with Pattie Maes, or Episode 7: Work of the Future (https://www.augmentedpodcast.co/7) with Elisabeth Reynolds. 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/). Special Guest: Anna Waldman-Brown.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Operator 4.0. Our guest is David Romero, Professor of Advanced Manufacturing at Tecnológico de Monterrey University in Mexico (https://tec.mx). In this conversation, we talk about the emergence of a smart and skilled operator who is helped by cognitive and physical augmentation, how this trend emerged, and how it will shape the future where we need more resilience. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 104: A Scandinavian Perspective on Industrial Operator Independence with Johan Stahre (https://www.augmentedpodcast.co/104). 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: The operator is again at the center of the industrial process. This is a curious thing that seems to happen a few years after every major technological breakthrough or implementation once we realize how adaptable and capable a human workforce can be. That does not mean that technology is irrelevant but only that training humans to know every step of the work process is important in order to capture value by addressing and fixing errors and suggesting improvements. Special Guest: David Romero.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Executing on Manufacturing Technology" and our guest is Jane Arnold, board member at Aperio.ai (https://aperio.ai/about/) and former VP of Manufacturing Technology at Stanley Black & Decker (https://www.stanleyblackanddecker.com/). In this conversation, we talk about advanced manufacturing technology, the importance of material flow, transparency, throughput, cost cutting, and captivating users with digital tools. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 100: Innovating Across the Manufacturing Supply Chain (https://www.augmentedpodcast.co/100). 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: Execution is everything in manufacturing. You can have any technology you want, but it's only going to be as good as the execution, both among executives and among managers all along the supply chain and all across the factory. Special Guest: Jane Arnold.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Augmenting Workers With Wearables." And our guest is Andrew Chrostowski, Chairman and CEO of RealWear (https://www.realwear.com/). In this conversation, we talk about the brief history of industrial wearables, the state of play, the functionality, current approaches and deployments, use cases, the timelines, and the future. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you liked this episode, you might also like Episode 92: Emerging Interfaces for Human Augmentation (https://www.augmentedpodcast.co/92). 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 wearables have come a long way. There is a big need for assisted reality in many workforce scenarios across industry. There are now companies taking good products to market that are rugged enough, simple enough, and advanced enough to make work simpler for industrial workers. On the other hand, we are far away from the kind of untethered multiverse that many imagine in the future, one step at a time. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented reveals the stories behind the new era of industrial operations where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Augmenting Workers With Wearables. And our guest is Andrew Chrostowski, Chairman and CEO of RealWear. In this conversation, we talk about the brief history of industrial wearables, the state of play, the functionality, current approaches and deployments, use cases, the timelines, and the future. Augmented is a podcast for industrial leaders, for process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Andrew, welcome to the show. How are you? ANDREW: Hi, Trond. Great to be here. I'm doing great. TROND: You know, you are a poster child entrepreneur engineer, Oregon State, University of Southern California. You are actually an expert on the future of work. There are so many people that say they talk about the future of work. You are implementing and, selling, and evangelizing a true future of work product, not just a story. We're going to be talking about augmented, assisted all kinds of reality and collaboration, Andrew, because that's, I guess, what it's all about. And you lead the industrial wearable company RealWear. But first, I want to get to the fact that you're a certified firefighter. Now, how does that fit into this? ANDREW: That's really a great question. And one of the things that's been passionate for me from the beginning is being close to the customer. It was true when I was an Air Force officer designing for systems that would support our warfighters and putting myself in their situations in life and death. Certainly, I think about it in terms of customers, and we were dealing with other lines of business and trying to understand the customers' perspective, and especially the frontline workers that create those products. And when I took over the Scott Safety business when I was part of Tyco, their particular market was firefighters. They were the leading provider of air tanks, cylinders, respirators, what we call SCBAs, self-contained breathing apparatus for firefighters. Now, I know a lot of things about a lot of areas of technology. But I didn't know anything about firefighting. And so when I took over that business, the first thing I did was go to Texas A&M and actually get trained and certified as an interior firefighter. So I actually put on all the bunker gear, timed donning just like you do when you're in the fire station, fought real fires that were built, and to understand really the challenges they faced. And I came out of that training really having a greater appreciation for just how challenging that work is. And I know it's shocking to your listeners, but everything we ever see on TV and movies about firefighting is wrong. Basically, firefighting, besides being terrifying, and difficult, and dangerous, is basically blind. You're in the smoke. You're in the dark. And my background in the Air Force thermal imaging systems and multispectral systems came back to me. And I said, "You know what we need to do is give predator vision to firefighters and give them the chance to see the unseen in the dark." And so, coming out of that training, I initiated an in-mass thermal imaging system for firefighters that went to the market about 14 months later at Scott site. TROND: Wow, that's some real background there. I'd like to start with that story because it reminds me that what we're about to talk about here, you know, wearables, it's not a joke. These are, you know, in industrial environments, these are not optional technologies once they really, really start working. And you can sort of say that they're first-line technologies. They better work every time. So this is not a case where you could kind of, well, you know, let's install another version and restart and whatnot. These are eventually going to be hopefully systems that the modern industrial worker really starts to trust to perform their job efficiently. Before we get into the nitty-gritty of all of the different things that RealWear is trying to do, I wanted to just ask you a basic question, what is assisted reality? It's a curious phrase. It's like, why does reality need assistance? [laughs] You know, where does that even come from? ANDREW: You can deny reality, but you can't deny the effects of denying reality. When we talk about assisted reality, it's a point on the spectrum what we call XR, the extended reality. It starts with reality and ends when that virtual reality, the fully immersive digital environment that we experience and what we talk about a lot in the metaverse. Then coming from reality forward, you have assisted reality, which is a reality-first, digital-second environment, which is what we focus on. It is the idea that this is the technology available now that allows a worker to be productive and work safely in a real-world environment. When you get into augmented reality, which is something that we think of when we think of products like HoloLens and other similar types of products, that's where this digital environment begins to overlay the actual environment. It imposes a cognitive load on the brain so that you're now having to focus on things that aren't really there while there are things that are really around you that could hurt you. This is great when you're in a safe environment, in a classroom, in a design area, when you're collaborating in the office to be able to immerse yourselves in these three-dimensional digital objects. It's much different when you're walking on the deck of an oil rig or you're potentially working around a cobot that can hurt you when your attention is distracted. And then we have sort of that virtual reality game that we started with in the metaverse where people are now kind of transposing themselves into a fully digital atmosphere. We at RealWear have focused on making a difference for the future of work and focusing on those 2 billion frontline workers who could work more safely and more productively if they were connected. And it makes perfect sense to us. If we learned anything from the COVID lockdowns, we learned that this idea of working from anywhere, the idea of the office worker working from home, working from the coffee shop, all of this now has become just a given. We know that we need these digital tools to collaborate remotely. What we only have begun to just crack the code on is that there are, again, 2 billion people working with their hands on the front line who could work more productively and more safely if they were connected workers, if they had access to information, if they had access to collaborating in a hands-free way with their counterparts across the world. And so RealWear, our focus is this mission of engaging, empowering, and elevating the performance of those frontline workers by giving them an assisted reality solution that is extremely low friction and easy to use. TROND: I like the distinction there. Even though this podcast is called augmented, I like the distinction between AR and assisted reality. Because there's really, I guess, you can see it more clearly in the consumer space where it sounds so fascinating to enter these virtual worlds. But in industry, the virtual is really subservient and needs to be subservient to the very reality. So I guess assisting reality is the point here. It's not the endpoint that is necessarily the virtual. You're using the technologies, if I understand it, to strengthen the ability to survive and be very, very efficient in reality as opposed to entering some sort of virtual space where you are simulating more. You're talking about critical applications in the physical industrial reality, so that's now clear to me. Having said that, this is not easy to do, is it, Andrew? ANDREW: No. I mean, there's a lot that comes into this idea of making technology that's human-centric. And all the things you were just talking about really bring us back to this idea that this kind of assisted reality solution is about helping the human being at that nexus of control operate more safely and effectively in a variety of environmental conditions. It is really important that we think about the technology serving the person and not so much technology that is imposing itself on people, which is oftentimes what we see as we try to roll out different kin

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Lean Operations." Our guest is John Carrier, Senior Lecturer of Systems Dynamics at MIT. In this conversation, we talk about the people dynamics that block efficiency in industrial organizations. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). 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: The core innovative potential in most organizations remains its people. The people dynamics that block efficiency can be addressed once you know what they are. But there is a hidden factory underneath the factory, which you cannot observe unless you spend time on the floor. And only with this understanding will tech investment and implementation really work. Stabilizing a factory is about simplifying things. That's not always what technology does, although it has the potential if implemented the right 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. And our vision is a world where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Lean Operations. Our guest is John Carrier, Senior Lecturer of Systems Dynamics at MIT. In this conversation, we talk about the people dynamics that block efficiency in industrial organizations. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip. John, welcome to the show. How are you? JOHN: Trond, I'm great. And thank you for having me today. TROND: So we're going to talk about lean operations, which is very different from a lot of things that people imagine around factories. John, you're an engineer, right? JOHN: I am an engineer, a control engineer by training. TROND: I saw Michigan in there, your way to MIT and chemical engineering, especially focused on systems dynamics and control. And you also got yourself an MBA. So you have a dual, if not a three-part, perspective on this problem. But tell me a little bit about your background. I've encountered several people here on this podcast, and they talk about growing up in Michigan. I don't think that's a coincidence. JOHN: Okay, it's not. So I was born and raised in the city of Detroit. We moved out of the city, the deal of oil embargo in 1973. I've had a lot of relatives who grow up and work in the auto industry. So if you grew up in that area, you're just immersed in that culture. And you're also aware of the massive quote, unquote, "business cycles" that companies go through. What I learned after coming to MIT and having the chance to meet the great Jay Forrester a lot of those business cycles are self-inflicted. What I do is I see a lot of the things that went right and went wrong for the auto industry, and I can help bring that perspective to other companies. [laughs] TROND: And people have a bunch of assumptions about, I guess, assembly lines in factories. One thing is if you grew up in Michigan, it would seem to me, from previous guests, that you actually have a pretty clear idea of what did go on when you grew up in assembly lines because a lot of people, their parents, were working in manufacturing. They had this conception. Could we start just there? What's going on at assembly lines? JOHN: I'm going to actually go back to 1975 to a Carrier family picnic. My cousin, who's ten years older than I, his summer job he worked at basically Ford Wayne, one of the assembly plants. He was making $12 an hour in 1975, so he paid his whole college tuition in like a month. But the interesting point was he was talking about his job when all the adults were around, and he goes, "Do you know that when they scratch the paint on the car, they let it go all the way to the end, and they don't fix it till it gets to the parking lot?" And I'll never forget this. All the adults jumped on him. They're like, "Are you an idiot? Do you know how much it costs to shut the line down?" And if you use finance, that's actually the right answer. You don't stop the line because of a scratch; you fix it later. Keep the line running. It's $10,000 a minute. But actually, in the short term, that's the right decision. In the long term, if you keep doing that, you're building a system that simply makes defects at the same rate it makes product. And it's that type of logic and culture that actually was deeply ingrained in the thinking. And it's something that the Japanese car companies got away from. It's funny how deeply ingrained that concept of don't stop the line is. And if you do that, you'll make defects at the same rate that you make product. And then, if you look at the Detroit newspapers even today, you'll see billion-dollar recalls every three months. And that's a cycle you've got to get yourself out of. TROND: You know, it's interesting that we went straight there because it's, I guess, such a truism that the manufacturing assembly line kind of began in Detroit, or at least that's where the lore is. And then you're saying there was something kind of wrong with it from the beginning. What is it that caused this particular fix on keeping everything humming as opposed to, I guess, what we're going to talk about, which is fixing the system around it? JOHN: There's a lot of work on this. There's my own perspective. There's what I've read. I've talked to people. The best I can come up with is it's the metrics that you pick for your company. So if you think about...the American auto industry basically grew up in a boom time, so every car you made, you made profit on. And their competitive metric was for General Motors to be the number one car company in the world. And so what that means is you never miss a sale, so we don't have time to stop to fix the problem. We're just going to keep cranking out cars, and we'll fix it later. If you look at the Japanese auto industry, when it arose after World War II, they were under extreme parts shortages. So if one thing were broken or missing, they had to stop. So part of what was built into their culture is make it right the first time. Make a profit on every vehicle versus dominant market share. TROND: Got it. So this, I guess, obsession with system that you have and that you got, I guess, through your education at MIT and other places, what is it that that does to your perspective on the assembly line? But there were obviously reasons why the Ford or the Detroit assembly lines, like you said, looked like they did, and they prioritized perhaps sales over other things. When you study systems like this, manufacturing systems, to be very specific, how did you even get to your first grasp of that topic? Because a system, you know, by its very nature, you're talking about complexity. How do you even study a system in the abstract? Because that's very different, I guess, from going into an assembly and trying to fix a system. JOHN: So it's a great question. And just one thing I want to note for the audience is although we talk about assembly lines, most manufacturing work is actually problem-solving and not simply repetitive. So we need to start changing that mindset about what operations really is in the U.S. We can come to that in the end. TROND: Yeah. JOHN: I'll tell you, I'm a chemical engineer. Three pieces of advice from a chemical engineer, the first one is never let things stop flowing. And the reason why that's the case in a chemical plant is because if something stops flowing for a minute or two, you'll start to drop things out of solution, and it will gum everything up. You'll reduce the capacity of that system till your next turnaround at least. And what happens you start getting sludge and gunk. And for every class I was ever in, in chemical engineering, you take classes in heat transfer, thermodynamics, kinetics. I never took a class in sludge, [laughs] or sticky solids, or leftover inventory and blending. And then, when I first went to a real factory after doing my graduate work, I spent four to six years studying Laplace transforms and dynamics. All I saw were people running around. I'm like, that's not in the Laplace table. And, again, to understand a chemical plant or a refinery, it takes you three to five years. So the question is, how can you actually start making improvement in a week when these systems are so complex? And it's watch the people running around. So that's why I focus a lot on maintenance teams. And I also work with operations when these things called workarounds that grow into hidden factories. So the magic of what I've learned through system dynamics is 80% to 90% of the time, the system's working okay, 10% or 20% it's in this abnormal condition, which is unplanned, unscheduled. I can help with that right away. TROND: So you mentioned the term hidden factories. Can you enlighten me on how that term came about, what it really means? And in your practical work and consulting work helping people at factories, and operations teams, and maintenance teams, as you said, why is that term relevant, and what does it really do? JOHN: Great. So I'm going to bring up the origin. So many people on this call recognize the name Armand Feigenbaum because when he was a graduate student at the Sloan School back in the '50s, he was working on a book which has now become like the bible, Total Quality Management or TQM. He's well known for that. He's not as well known for the second concept, which he shoul

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Explainability and AI." Our guest is Julian Senoner, CEO and Co-Founder of EthonAI (https://ethon.ai/). In this conversation, we talk about how to define explainable AI and its major applications, and its future. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 103: Human-First AI with Christopher Nguyen (https://www.augmentedpodcast.co/103). 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: Explainability in AI, meaning knowing exactly what's going on with an algorithm, is very important for industry because its outputs must be understandable to the process engineers using it. The computer has not and will not use the product. Only a domain expert can recognize when the system is wrong, and that will be the case for a very long time in most production environments. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented reveals the stories behind a new era of industrial operations where technology will restore the agility of frontline workers. Technology is changing rapidly. What's next in the digital factory, and who's leading the change? In this episode of the podcast, the topic is Explainability and AI. Our guest is Julian Senoner, CEO and Co-Founder of EthonAI. In this conversation, we talk about how to define explainable AI and its major applications, and its future. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip. Julian, welcome to the show. JULIAN: Hello, Trond. Thank you for having me. TROND: I'm excited to have you. You know, you're a fellow runner; that's always good. And you grew up in the ski slopes.; that makes me feel at home as a Norwegian. So you grew up in Austria; that must have been pretty exciting. And then you were something as exciting as a ski instructor in the Alps. That's every man and woman's dream. JULIAN: Yeah, I think it was very nice to grow up in the mountains. I enjoyed it a lot. But, you know, times have passed, and now I'm happy to be in Zurich. TROND: You went on to industrial engineering. You studied manufacturing and production at ETH. And you got interested in statistics and machine learning aspects of all of that. How did this happen? You went from ski instruction to statistics. JULIAN: Yeah, I was always impressed about watching stuff being made. I think it's a very relaxing thing to do. And I always wanted to become an engineer. When I was five years old, I wanted to become a ship engineer. So it was always clear that I wanted to do something with manufacturing and mechanical engineering. So I started actually doing my bachelor's in Vienna at Technische University. And for my master's, I moved to Zurich and studied Industrial Engineering. ETH has historically been very strong in machine learning research. Every student, no matter if you're interested or not, gets exposed to machine learning, statistics, and AI. It caught my attention. I thought there were very interesting things you can do when you combine both. So that's how I ended up doing research on interface and becoming an entrepreneur in this area. TROND: Yeah, we'll talk about your entrepreneurship in a moment. But I wanted to go to your dissertation, Artificial Intelligence in Manufacturing: Augmenting Humans at Work. That is very close to our interests here at the podcast. Tell me more about this. JULIAN: There is a lot of hype about AI. There's a lot of talk about self-aware factories and these kinds of things. These predictions are not new. We had studies in the 1970s that predicted there won't be any people in factories by the 1980s; everything will be run by a centralized computer. I never believed in these kinds of things. During my dissertation, I was interested in looking into how we can develop useful AI tools that can support people doing their jobs more effectively and efficiently. TROND: Right. But you already were onto this idea of humans at work. Where did you do your case studies? I understand ABB and Siemens were two of them. Give me a little sense of what you discovered there; pick any one of them. JULIAN: Sure. I'd love to start with the case that we ran with Siemens. I've worked quite a lot with Siemens in different use cases, but one of them was supporting frontline workers in complex assembly tasks on electronic products. So the aim was to help the worker check if the product has been assembled correctly. There are many connectors that could be missing or assembled in the wrong way. So the idea was to have a camera mounted to the workstation, and the worker would put the final product under the camera and get visual feedback if it has been assembled correctly or not. What we did here is really studying the psychological aspect of that. I would say most of my Ph.D. was really math-heavy and about modeling, but here we were interested in the psychological aspect. Because, in the beginning, we thought perhaps andon lights with green or red signals would be enough. But we got intrigued by the research question of does the worker actually follow these recommendations if it's just the green or red light? So we did an experiment, which I'm very excited about. So we got 50 workers that volunteered within Siemens to participate, which I'm very grateful for. We basically divided factory workers in two groups. We looked into the effect of explainability in the decisions that the AI makes. So we had one group that got basically just a recommendation to reject or to pass the product. And we had another group that got the exact same recommendations. But in addition to that, we provided visual feedback indicating the area where the AI believes that there could be an error. And the results of this experiment were perhaps not too surprising, but the effect size clearly was. We found that the people that did not get explanations for these recommendations were more than three times more likely to overrule the AI system, although the AI was correct. And I think this is a really nice finding. TROND: Well, it's super interesting in terms of trust in AI. And this topic of explainability is so much talked about these days, I guess, not always in manufacturing because people overlook that sometimes, people who are not in the industry. And they think about whether machines will take over and what decisions they're taking over and, certainly, if the machines are part of the decision making, what goes into that decision making? But as you were discovering more about explainability, what is explainability? And how is it different from even just being able to...it starts, I guess, with the decision of the AI being very clear because if that's not even clear, then you can't even interpret the decision. But then there's a lot of discussion in the industry, I mean, in the AI field, I guess, about interpretability. So can you actually understand the process? But you did this experiment, and it became very clear, it seems, that just the decision is not enough. Was it the visual example that was helping here? Or what is it that people want to know about a machine decision to make them trust the decision and trust that their processes, you know, remains a good process? JULIAN: I think I kind of see two answers to this question; one is the aspects of interpretability and explainability; perhaps I start with that. So these terms are often used interchangeably, and academics are still arguing about the differences. But there is now a popular opinion that I also share that these two things are not the same. So when we talk about interpretable AI, we think about models that have basically an interpretable architecture or functional relationship, so an example would be a linear regression. You have a regression line; it has a slope, it has an intercept. And you know how an X translates into a Y or an input to an output. Explainable AI is a fairly new research branch, which it's slightly different to that. It looks into more complex AI models like deep neural networks and ensembling techniques, which do not have this inherently interpretable model architecture. So a human, just by looking at it, cannot understand how decisions are formed. And what explainable AI methods do is basically reverse engineer what the model is doing by approximating the inner behavior of the model. So, in essence, we're creating a model of a model. Coming to your second question, so why might this be important in manufacturing? Basically, what I discovered during my research is that AI is still not trusted in the manufacturing domain, so people often do not understand what AI does in general, and I think explanations are a very powerful tool to simplify that. And a second use case of explainability is also that we can reduce complexity. So we can use more powerful methods to model more complex relationships. And we can use explainability on top of that to, for example, conduct problem-solving. TROND: Wow, you explain it very easily, but it's not easy to explain an actual AI model. Like, if you were to say, you know, here is the neural network model I used, and it had eight layers, good luck explaining that to a manufacturing worker or to me. JULIAN: So I think that explaining what a model is is also a different topic, and perhaps it's not even needed. You can still treat this as a mathematical function. I think it's really more about the decisions

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Post Lean." Our guest is Frode Odegard, Chairman and CEO at the Post-Industrial Institute (https://post-industrial.institute/). In this conversation, we talk about the post-industrial enterprise going beyond digital and higher-order organizations. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 102 on Lean Manufacturing with Michel Baudin (https://www.augmentedpodcast.co/102). 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 a fundamental perspective on human organizations, but clearly, there were things not foreseen in the lean paradigm, both in terms of human and in terms of machine behavior. What are those things? How do they evolve? We have to start speculating now; otherwise, we will be unprepared for the future. One of the true questions is job stability. Will the assumptions made by early factory jobs ever become true again? And if not, how do you retain motivation in a workforce that's transient? Will future organizational forms perfect this task? 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 Post Lean. Our guest is Frode Odegard, Chairman and CEO at the Post-Industrial Institute. In this conversation, we talk about the post-industrial enterprise going beyond digital and higher-order organizations. Augmented is a podcast for industrial leaders, process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Frode, welcome to Augmented. How are you? FRODE: Pretty good. TROND: Yeah. Well, look, talking to Norwegians living abroad that's become a sport of mine. You were born in Norway, software design from there, became an entrepreneur, moved to Silicon Valley. I also know you have an Aikido black belt; we talked about this. This could have become its own podcast, right? There's a long story here. FRODE: [laughs] Absolutely, yeah. TROND: But you're also the CEO of the Post-Industrial Institute, which I guess used to be called the Post-Lean Institute. But in any case, there's a big connection here to lean, which is a global community for leaders that are driving transition towards something post-lean, post-industrial, post-something. So with that context, tell me a little about your background and how you ended up doing what you're doing. FRODE: Born in Norway, as you pointed out. My folks had a process control company, so that was kind of the industry I was born into was industrial controls, which included visiting factories as a child and installing process control systems. So I was doing, you know, circuit board assembly at age eight because when you grow up in a family business, that's what you get to do. And I quickly gravitated towards software. I think I was 13 when I was working on my first compiler. So my first passion was really programming and language, design, implementation, and that sort of got me interested in theoretical computer science. So very far from what I do today, in some ways, but I think theoretical computer science, especially as a software architecture and all that, teaches you how to think and sort of connect the dots, and that's a good life skill. At 17, I started a software company in high school. And when I was 22, I immigrated to the United States after some trips here. I was on a Standards Committee. I was on the Sun User Group board of directors as a European representative. It was a weird story in itself, how that happened. So yeah, 1990, 1991, I'm in Silicon Valley. TROND: So you jumped ship, essentially. Because, I mean, I've heard a lot of people who come to the U.S. and are inspired, but you just basically jumped off the airplane. FRODE: Yeah, I like to say I was here as an entrepreneurial refugee. Things are different now in Norway, but for a long time, they had strange taxation rules, and very difficult to start companies and scale them. But also, they didn't really have the fancy French word. They didn't really have the milieu. They didn't have a community of people trying to build companies in tech. So tech was very much focused on either military applications, that was its own little industry and community, or the energy industry, the oil industry in particular. TROND: All of that seems to have changed quite a bit. I mean, not that you or I, I guess, are experts on that. As ex-pats, we're outside, so we're looking in, which is a whole other story, I guess. But I'm curious about one more thing in your background so Aikido, which, to me, is endlessly fascinating, perhaps because I only ever attended one Aikido training and, for some reason, decided I wasn't going to do it that year, and then I didn't get back to it. But the little I understand of Aikido it has this very interesting principle of using the opponent's force instead of attacking. That's at least what some people conceptualize around it. But you told me something different. You said there are several schools of Aikido, and one of them is slightly more aggressive, and you belong to that school. I found that quite interesting. FRODE: [laughs] Now I'm wondering about my own depiction of this, but the Aikido that I study is known as Iwama-style Aikido, and it's called that because there was an old town in Japan, which has been absorbed by a neighboring city now, but it was called Iwama, and that's where the founder of Aikido moved during the Second World War, and that's where he sort of completed the art. And that's a long technical story, but he included a fairly large weapons curriculum as well. So it's not just unarmed techniques; it's sword-knife stuff. And it's a really beautiful art in that all of the movements with or without weapons are the same, like, they will follow the same principles. In terms of not attacking, of course, on a philosophical level, it calls itself the art of peace. In a practical sense, you can use it offensively to, for example, if you have someone who is grabbing your child or something like that, this person is not attacking you, but you have to step in and address the situation, and you can use it offensively for sure. TROND: Very interesting. I was going to jump straight to what you're up to now, then, which is, I guess, charting this path towards a different kind of industrial enterprise. And you said that you earlier called your efforts post-lean, and now you're calling them post-industrial. It's this continuity in industry, Frode. Tell me a little bit more about that. FRODE: I think a good way to think about approaches to management and understanding the world around us is that various management practices, and philosophies, and ideas, and so on, have been developed in response to circumstances that were there at the time. So if you think about Frederick Taylor and the problems that he was trying to solve, they initially had a lot to do with just getting work organized and standardized. And then, in 1930s, you start seeing the use of statistical methods. Then you start seeing more of an interest in the psychology of work and so on. And lean kind of melts all of these things together. A great contribution from Toyota is you have a socio-technical system and organizational design where you have a new kind of culture that emphasizes continuous learning, continuous problem solving using some of these ideas and tools that were developed much earlier. Now, in the post-war years, what we see is information technology making business more scalable, also contributing to complexity, but certainly making large companies more scalable than they would have been otherwise. And what we see in the mid-1990s leading up to the mid-2000s is the commercial internet, and then we get smartphones. That's the beginning of a new kind of industrial landscape. And what we see then is instead of an increasing tendency towards centralization in firms and business models, you start seeing this decoupling and decentralization. And what I discovered was that's actually a new thing for the human species. Ever since the invention of agriculture 10,000 years ago and then cities in the Bronze Age a little over 5,000 years ago, and then the industrial revolutions, we've seen a culmination of improved mastery of the world, adapting the world to our needs, which is technology and increasing centralization. You had to move to where the work was, and now we're sort of coming out of the pandemic (Let's hope it doesn't come back.) that has accelerated in the pandemic, so you have this decentralization, decoupling. And this continuity and the way I started using the term post-lean, and we can jump back and forth as you'd like, it was just because a lot of the assumptions behind the lean practices and how those practices were implemented were based on the idea that you had organizations that lasted a long time. You had long employee tenures. You had a certain kind of a...I don't like this term, but a social contract between the firm and workers and managers and workers. And they would come and do their work on-site in person at the factory, and this world is kind of disappearing now. And so there's all of this work now being done. I think manufacturing labor forces peaked at a third of the workforce some decad

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Product Lifecycle Management's Momentum in Manufacturing." Our guest is Jim Heppelmann, CEO of PTC (https://www.ptc.com/). In this conversation, we talk about the why and the how of product lifecycle management's momentum in manufacturing. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 93: Industry 4.0 Tools (https://www.augmentedpodcast.co/93). 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: The momentum is clear, and one indication is the trend that PLM is being elevated to an enterprise system. But why is PLM such a hot market right now? One key word is greenhouse gas reduction because companies need a system of record to track their emissions, and this is not easy to do without a system in place. 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 Product Lifecycle Management's Momentum in Manufacturing. Our guest is Jim Heppelmann, CEO of PTC. In this conversation, we talk about the why and the how of product lifecycle management's momentum in manufacturing. Augmented serves an audience of executives, industry leaders, investors, founders, educators, technologists, academics, process engineers, and shop floor operators across the emerging field of frontline operation. And it's hosted by futurist Trond Arne Undheim and presented by Tulip. Jim, welcome to the show. How are you? JIM: I'm great, Trond. Great to be with you here this morning. TROND: Yeah, Jim. I thought we would talk a little bit about industrial automation and some specifics. But first of all, I wanted to talk a little bit about you. You grew up in Minnesota, got yourself a mechanical engineering degree, and became an entrepreneur, and sold your company to PTC. You were the CTO, I guess, for a while and now the CEO. It's been quite a journey. JIM: Yeah, it's fun. And by the way, industrial automation and related topics is my favorite topic. I was born on a dairy farm in Southeastern Minnesota, part of a very large family. It was a tough life. We never quite had enough money. So I was ambitious. I wanted to do something. I wanted to have a better life than I grew up with, not that it was bad, but maybe I wanted to have a little bit more economic security. I decided to become an engineer because I had spent a lot of time with equipment, machines, using them but also fixing them, taking them apart, putting them back together. I was good at math and science. So I went into mechanical engineering, but right away, I was drawn to software. And so I really got a major in mechanical engineering, a minor in computer science, and focused on how do you use computer science to do engineering? That led me to join a computer-aided design company, a CAD company. As an intern, I was assigned to a new idea they had which they called product data management. It was not very glamorous compared to the graphics of CAD, where you could twirl models around on the screen and so forth. So it's the kind of thing that you assigned to a new intern. As an intern, I took to it; I mean, it made a lot of sense to me. So basically, that's what I specialized in in my career, especially the early part of my career. And I became quite an expert at PLM, or at the time; it was called PDM. That led me, ultimately, when I was exposed to the internet, to say, "Wow, if you really leverage web technology with a light client, a web browser, make it easy for people to engage no matter what company they're in, then you could have whole supply chains working together in a very efficient way. So that led me to create a company called Windchill Technology, kind of a funny name based on a company in Minnesota; that's where the Windchill part comes from. But PTC came to acquire this company, and the business just really took off at PTC. In the ensuing years, I became the Chief Technology Officer across all of PTC, and then, as you said, that led to becoming the Chief Executive Officer a dozen years ago. It's been a great ride. It's been a lot of fun. We've accomplished a lot. The technology has come so far. Hard to imagine in the early days, it would end up here. But it's been a very exciting career trajectory, for sure. TROND: So, Jim, before we move into talking about product lifecycle management, I wanted to ask you a more generic question: what is the most challenging part of being a CEO? So you've gone from being an entrepreneur to being a CEO of a much larger structure here. What's exciting, and what's challenging about that? JIM: Yeah, I mean, I think what is exciting is also challenging, which is so much context-switching. In a single day, I go from worrying about budgets and financial plans to meeting with happy customers, sometimes frustrated customers to meeting with sales teams and R&D teams and R&D projects. And it's just a constant switch from one topic to another, which is exciting because they're all topics I like. But it puts a lot of pressure on you to very quickly remember where you left this conversation off last time you were involved and how to dive right back in and pick it up. And I think there's some pressure that comes from that, you know, to be on your toes ready to go and just switch from topic to topic to topic. And then, of course, there's the pressure of a public company that every 90 days, we have an earnings call. And our investors want to hear good news. Fortunately, we've had a lot of good news, but there's always a lot of pressure to make sure you keep it going. TROND: I wanted to jump then to product lifecycle management which is a specialty topic to you; it's not, right? Because you've been involved with this for a while, [laughs] and it's a passion for you. I guess in industrial automation; there are a lot of three-letter acronyms and such. But if you'd give your best way to explain how this software got started, what was the original intention? I mean, this is a while back now. We're talking 1998 when this software suite got created when Windchill started creating this software. What did it do then, and what does it do now? JIM: Well, PLM is really the system of record for product data. So if you think of salesforce.com, they got started just a couple of years later. They're a system of record for customer information, the 360-degree view of the customer. And in most companies, they have an ERP system, and that's the system of record for the financial data, all the purchase orders, and invoices, and whatnot, and might have a human resource information system, something like Workday, that's the system of record for all your employees. But if you're an industrial company that makes products, you have a lot of product data. And where is the system you can go to to find and interact with that data in your day-to-day job as part of that product development, or manufacturing, or customer support process? And so PLM really has become that system of record. And for an industrial company that makes products, it's a pretty important system of record. Like a CRM system or an ERP system, you're not just collecting and managing the data; you're also transacting against it, applying change orders, and building configurations of it, and whatnot. So PLM has become recognized in industrial companies as a critical anchor system of record. That's the way I like to think about it. TROND: Yeah, and we'll get into some of it after a while. But I guess product lifecycle is something that has gone much higher on the agenda for environmental reasons and others. So, I guess, if you think about a product from its ideation and to its disposal, essentially, it's a long chain of events that such a system, theoretically, could help a company with. JIM: Yeah, for sure. And just to go a little deeper in that, a lot of products are made of mechanical parts, electronic parts, software parts. They come in lots of different configurations. They change from year to year and sometimes month to month, so there are a lot of engineers and product managers involved. And then purchasing gets involved, and supply chain management gets involved because very few companies build everything themselves; they work with a supply chain. Then you're bringing in the factory and production planners, and then ultimately, the production process. They need this data, and they need the right configurations and versions of it. Then you ship the product to the customer, and you provide, in many cases, service and support. And you can't do that well without understanding the configuration of the product and all the versions of mechanical electronics and software parts in it. Really what we're talking about is, yeah, following that product throughout its lifecycle. Sometimes I like to use a golf analogy, like the front nine and the back nine on an 18-hole course. The front nine is everything that leads up to the product being manufactured, and the back nine is everything that happens thereafter. And to really do product lifecycle management, you have to think of all 18 holes, and that's kind of the focus we've had here at PTC. TROND: To what extent is product development kind of a management discipline, and to what extent do you feel like it's a technical discipline? And c

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "A Scandinavian Perspective on Industrial Operator Independence." Our guest is Johan Stahre (https://www.linkedin.com/in/jstahre/), Professor and Chair of Production Systems at Chalmers University in Sweden. In this conversation, we talk about how the field of human-centered automation has evolved, the contemporary notion of operator 4.0, Scandinavian worker independence, shop floor innovation at Volvo, factories of the future, modern production systems, robots, and cobots in manufacturing. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich (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: Human-centered automation is the only kind of automation that we should be thinking about, and this is becoming more and more clear. Operators are fiercely independent, and so should they be. This is the only way they can spot problems on the shop floor, by combining human skills with automation in new ways augmenting workers. It seems the workforce does not so much need engagement as they need enablement. Fix that, and a lot can happen. 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 A Scandinavian Perspective on Industrial Operator Independence. Our guest is Johan Stahre, Professor and Chair of Production Systems at Chalmers University in Sweden. In this conversation, we talk about how the field of human-centered automation has evolved, the contemporary notion of operator 4.0, Scandinavian worker independence, shop floor innovation at Volvo, factories of the future, modern production systems, robots, and cobots in manufacturing. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Johan, Welcome. How are you? JOHAN: I'm fine, thank you, Trond. It's really nice to see you. TROND: Yeah, likewise. JOHAN: Fellow Nordic person. TROND: Fellow Nordic person. And I apologize for this very American greeting, you know, how are you? As you know, I'm from the Nordic region. I actually mean it, [laughs] you know, it was a question. So I do wonder. [laughs] JOHAN: I'm actually fine. It's just ending the vacation, so I'm a little bit sad about that because everyone...but it's a very nice time now because the rest of the world seems to be on vacation, so you can get a lot of work done. TROND: I concur; that is a wonderful time. Johan, I wanted to just briefly talk about your exciting background. You are an engineer, a mechanical engineer from Sweden. And you had your initial degree from Linköping University. Then you went on to do your Ph.D. a while back in manufacturing automation, and this was at Chalmers, the University in Sweden. And that's where you have done your career in manufacturing research. You are, I think, the first Scandinavian researcher certainly stationed currently in Sweden that we've had on the podcast. So I'm kind of curious, what is manufacturing like in Scandinavia? And what is it that fascinated you about this topic so that you have moved so deeply into it? JOHAN: Manufacturing in Sweden is the core; it's the backbone of our country in a sense. We have statistically too many large manufacturing companies in Sweden as compared to, I mean, we're only 10 million people, but we have like 10, 12 pretty large companies in the manufacturing area in automotive but also in electronics like Ericsson, you have Volvo, we have SKF. We have a lot of big companies. Sweden has an industrial structure that we have several small companies and a couple of large companies, not so many in the middle section there. This happened, actually, in the 1800s somewhere. There was a big growth of big companies, and there was a lot of effort from the government to support this, and that has been continued. So the Swedish government has supported the growth of industry in Sweden, and therefore we have a very strong industry and also quite good digital growth and maturity. TROND: So the Scandinavian background to me when I was there, I remember that one of the things that at least Scandinavian researchers think is distinct about Scandinavia is worker independence. And it's something that I kind of wanted to just tease out a little bit in the beginning of this podcast. Am I wrong in this, or is there something distinct about the relationship between, I guess, workers and managers in Scandinavia, particularly? One speaks about the Scandinavian model. Can you outline a little bit what that means in manufacturing if it still exists? It's an open question. JOHAN: From my perspective, Sweden usually ranks very high in innovation, also when it comes to international rankings. And I think some of that has to do with the openness and the freedom of thinking in a sense and not so hierarchical, more consensus-oriented, ability to test and check and experiment at work without getting repercussions from top management. And it is much easier. In fact, if you are at one department in a manufacturing company or in university as such and you want to collaborate with another colleague across the aisle, if you have a two hierarchical system, you need to go three levels up in order to be able to do that. But here, I think it's easier to just walk across the aisle to have this collaboration and establish a cooperative environment. I think that that's part of the reason. Also, we're not so many; I mean, I think historically, we needed to do a lot of things ourselves in Sweden. We were a country up north with not so many people, and we have harsh environments, and I think it's the same as Norway. I mean, you need to be self-sustainable in that sense, and that creates, I think, environmental collaboration. TROND: We'll go more deeply into your research on manufacturing and to what extent a question I asked here matters to that. But do you have a sense just at the outset here that this type of worker and operators sort of independence, relative independence, perhaps compared to other regions, is it changing at all? Or is this kind of a feature that is a staple of Scandinavian culture and will be hard to change both for good and for bad? JOHAN: I think that as everything...digitalization has sort of erased a lot of the cultural differences across the world in that sense. Because when I was a student, there was not this expressed digital environment, of course. The information environment was less complex. But I think now all the young people, as well as my mother, does her banking...she's 90, but she does her banking on her iPad; I mean, it's very well-spread. And I think that we are all moving towards a similar culture, and the technology is spreading so quick. So you cannot really have cultural differences in that sense. But I think that's still the way that we're using this. And I think that the collaborative sense I think that that is still there. The reason why Sweden is comparatively innovative still is that we still maintain our culture and use the technology to augment that capability. TROND: So, Johan, we'll talk about a bunch of your experiences because you obviously are based in Sweden. And because of Sweden's industrial situation, you have some examples, you know, Volvo, a world-famous company obviously, and also famous for its management practices, and its factory practices, we'll get into that. But you've also worked, and you're advising entities such as the World Economic Forum, and you are active on the European stage with the European Institute of Technology. Your activity clearly goes way, way beyond these borders. But why don't we maybe start with some of these Scandinavian experiences and research projects that you've done maybe with Volvo? What is it with Volvo that captured people's attention early on? And what sort of experience and research have you done with Volvo? JOHAN: I think that Volvo is very innovative, and Volvo today is two types of companies; one is the car company that has now gone fully electric. It was introduced at the stock market, most recently owned by a Chinese company, and before that, it was owned by Ford, and before that, it was also public. But you also have the other part, which is the Volvo Group, which is looking at trucks, and boats, and things like that. And they both share a high level of innovation, ambition, innovation, and power, I think, using the experiences already from the '60s, where you had a lot of freedom as an employee. And also very good collaboration with the union in investments and in all the changes in the company I think that has been very beneficial. And it's made them...what is now Volvo Cars was very, very early, for example, with digital twins. They were experimenting with digital twins already in the 1990s. And we work together with Volvo but also with SKF, which is a roller-bearing company here to look at how we can support frontline workers and augment their capabilities because they're very skilled and they're very experienced. But sometimes you need to have sensor input, and you need to have structures, and rules, and procedures, and instructi

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Human-First AI. Our guest is Christopher Nguyen (https://www.linkedin.com/in/ctnguyen/), CEO, and Co-Founder of Aitomatic (https://www.aitomatic.com/). In this conversation, we talk about the why and the how of human-first AI because it seems that digital AI is one thing, but physical AI is a whole other ballgame in terms of finding enough high-quality data to label the data correctly. The fix is to use AI to augment existing workflows. We talk about fishermen at Furuno, human operators in battery factories at Panasonic, and energy optimization at Westinghouse. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 80: The Augmenting Power of Operational Data, with Tulip's CTO, Rony Kubat (https://www.augmentedpodcast.co/80). 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: Physical AI is much more interesting of a challenge than pure digital AI. Imagine making true improvements to the way workers accomplish their work, helping them be better, faster, and more accurate. This is the way technology is supposed to work, augmenting humans, not replacing them. In manufacturing, we need all the human workers we can find. As for what happens after the year 2100, I agree that we may have to model what that looks like. But AIs might be even more deeply embedded in the process, that's for sure. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations in 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 Human-First AI. Our guest is Christopher Nguyen, CEO, and Co-Founder of Aitomatic. In this conversation, we talk about the why and the how of human-first AI because it seems that digital AI is one thing, but physical AI is a whole other ballgame in terms of finding enough high-quality data to label the data correctly. The fix is to use AI to augment existing workflows. We talk about fishermen at Furuno, human operators in battery factories at Panasonic, and energy optimization at Westinghouse. Augmented is a podcast for industrial leaders, process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Christopher, how are you? And welcome. CHRISTOPHER: Hi, Trond. How are you? TROND: I'm doing great. I thought we would jump into a pretty important subject here on human-first AI, which seems like a juxtaposition of two contradictory terms, but it might be one of the most important types of conversations that we are having these days. I wanted to introduce you quickly before we jump into this. So here's what I've understood, and you correct me if I'm wrong, but you are originally from Vietnam. This is back in the late '70s that you then arrived in the U.S. and have spent many years in Silicon Valley mostly. Berkeley, undergrad engineering, computer science, and then Stanford Ph.D. in electrical engineering. You're a sort of a combination, I guess, of a hacker, professor, builder. Fairly typical up until this point of a very successful, accomplished sort of Silicon Valley immigrant entrepreneur, I would say, and technologist. And then I guess Google Apps is something to point out. You were one of the first engineering directors and were part of Gmail, and Calendar, and a bunch of different apps there. But now you are the CEO and co-founder of Aitomatic. What we are here to talk about is, I guess, what you have learned even in just the last five years, which I'm thrilled to hear about. But let me ask you this first, what is the most formational and formative experience that you've had in these years? So obviously, immigrant background and then a lot of years in Silicon Valley, what does that give us? CHRISTOPHER: I guess I can draw from a lot of events. I've always had mentors. I can point out phases of my life and one particular name that was my mentor. But I guess in my formative years, I was kind of unlucky to be a refugee but then lucky to then end up in Silicon Valley at the very beginning of the PC revolution. And my first PC was a TI-99/4A that basically the whole household could afford. And I picked it up, and I have not stopped hacking ever since. So I've been at this for a very long time. TROND: So you've been at this, which is good because actually, good hacking turns out takes a while. But there's more than that, right? So the story of the last five years that's interesting to me because a lot of people learn or at least think they learn most things early. And you're saying you have learned some really fundamental things in the last five years. And this has to do with Silicon Valley and its potential blindness to certain things. Can you line that up for us? What is it that Silicon Valley does really well, and what is it that you have discovered that might be an opportunity to improve upon? CHRISTOPHER: Well, I learn new things every four or five years. I actually like to say that every four or five years, I look back, and I say, "I was so stupid five years ago." [laughs] So that's been the case. TROND: That's a very humbling but perhaps a very smart knowledge acquisition strategy, right? CHRISTOPHER: Yeah. And in the most recent five years...so before co-founding Aitomatic, which is my latest project and really with the same team...and I can talk a lot more about that. We've worked with each other for about ten years now. But in the intervening time, there's a four-and-a-half-year block when we were part of Panasonic. So we had a company called Arimo that was acquired by Panasonic for our machine learning AI skills and software. And I would say if you look at my entire history, even though I did start with my degree in semiconductor all the way down to device physics and Intel and so on, but in terms of a professional working career, that was the first time we actually faced the physical world as a Silicon Valley team. And anybody who's observed Silicon Valley in the last 15-20 years, certainly ten years, has seen a marked change in terms of the shift from hardware to software. And my friend Marc Andreessen likes to say, "Software is eating the world." If you look at education, you know, the degrees people are getting, it has shifted entirely from engineering all the way to computer science. And the punch line, I guess, the observation is that we Silicon Valley people do not get physical. We don't understand the manufacturing world. We don't know how to do HVAC and so on. And so when we build software, we tend to go for the digital stuff. TROND: Christopher, it's almost surprising given the initial thrust of Silicon Valley was, of course, hardware. So it's not surprising to me, I guess because I've been observing it as well. But it is striking more than surprising that a region goes through paradigms. CHRISTOPHER: Yeah. Yeah. And it's a global trend. It's the offshoring of low-end, shall we say, low-value manufacturing and so on. And we're discovering that we actually went a little too far. So we don't have the skill set, the expertise anymore. And it's become a geopolitical risk. TROND: Right. Well, a little bit too far, maybe, or not far enough. Or, I mean, tell us what it is that you're losing when you lose the hardware perspective, particularly in this day and age with the opportunities that we're about to talk about. CHRISTOPHER: Well, I can talk specifically about the things that touch my immediate spheres. Maybe you can think abstractly about the lack of tooling expertise and manufacturing know-how, and so on. But as part of Panasonic, the acquisition was all about taking a Silicon Valley team and injecting AI, machine learning across the enterprise. And so we were part of that global AI team reporting to the CTO office. And we found out very quickly that a lot of the software techniques, the machine learning, for example, when you think about people saying data is the fuel for machine learning and specifically labeled data, right? In the digital world, the Google place that I came from, it was very easy to launch a digital experiment and collect labels, decisions made by users. You can launch that in the morning, and by evening you're building examples. You can't do that in the physical world. Atoms move a lot more slowly. And so when you try to do something like predictive maintenance, you don't have enough failure examples to train machine learning models from. So all of the techniques, all of the algorithms that we say we developed from machine learning that seem to work so well, it turns out it worked so well because the problem space that we worked on has been entirely digital, and they all fail when it comes to manufacturing, the things that you can touch and feel, you know, cars that move and so on. TROND: I want to ask you this, Christopher, because the first company you helped co-found was, in fact, a contract manufacturer. Do you think that reflecting on this long career of yours and these various experiences, what was it that convinced you before others? I mean, you're not the only one now in the Valley that has started to focus on manufacturing and including hardware again, but it is rare still. What does it require to not just think about manufacturing but actually start to do compute for manufacturing? Is it just a matter of coming up with techniques? Or is it a whole

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Lean Manufacturing. Our guest is Michel Baudin (https://www.linkedin.com/in/michelbaudin/), author, and owner of Takt Times Group. In this conversation, we talk about how industrial engineering equals the engineering of human work and why manufacturing and industrial engineering education needs to change because it has drifted away from industrial work and a future where manufacturing is not going away. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich (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 manufacturing might mean many things, but industrial work has largely been a consistent practice over several hundred years, which is not necessarily a bad thing. Having said that, if we want to go about improving it, we might want to stay pretty close to the workforce and not sit in statistics labs far removed from it. Efficiency is tied to work practices, and they cannot be optimized beyond what the workforce can handle or want to deal with. As we attempt to be lean, whatever we mean by that, we need to remember that work is a thoroughly human endeavor. 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 Lean Manufacturing. Our guest is Michel Baudin, author, and owner of Takt Times Group. In this conversation, we talk about how industrial engineering equals the engineering of human work and why manufacturing and industrial engineering education needs to change because it has drifted away from industrial work and a future where manufacturing is not going away. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Michel, welcome. How are you? MICHEL: Fine, thank you. How about yourself? TROND: Things are good. Things are looking up. I'm excited to talk about lean manufacturing with you, having had such a rich, professional background. Michel, you're French. You originally, I think, were thinking of becoming a probability researcher, or you were actually, and then you went to Japan and studied Toyota. You have had this career in English, German, Japanese sort of consulting all the way back from 1987 onwards on exciting topics, lean manufacturing, and especially implementing it, right? The real deal. You've authored at least four technical books that I know about. And I think you listed probably a while back, having written 900 blog posts. You've been very busy. You are the owner of the Takt Times Group, which is a consulting firm on lean manufacturing. And you love math, but you have this very interesting attitude, which we'll talk about, which is math is great, but it's not always the best communication tool. Tell me a little about that to start off. You're a probability researcher that doesn't use math; I think that's fascinating. MICHEL: I use it, but I don't brag about it with people that it turns off. So I have to be in the closet for this because people who work in manufacturing usually focus on concrete things, things that they can see and touch, and abstraction is not something that they respond well to. So whenever you explain a principle, my approach is to state this principle and then dig into some very specific examples right away; otherwise, I'm losing the people I'm talking to. But anyway, that's what I've had to do. TROND: So, did I capture your background okay? I mean, you've had a very international life so far. I hope it's been enjoyable and not just professional because you've spent your time in Germany, and Japan, and in the U.S., So you're really enjoying the different kinds of manufacturing environments. Or is it that you just want to be close to where it's all happening? MICHEL: I've enjoyed living in many different countries. And so you mentioned I'm French. I was born and raised in France, but I'm an American citizen, and I spent most of my life in the U.S. I think of myself as being part French, part American, part German, part Japanese. Because when I'm in a country, I tend to immerse myself in the culture; I don't stay aloof from it. TROND: Well, I'm curious about that because in the abstract... so if we are in the world of math, then you could maybe say that efficiency techniques are global; that was the idea. Some people have that idea, let's say, that efficiency is a global thing, and there's one thing called efficiency, and everybody should just learn it because then it's all better. It seems to me that because you spent a lot of time in three different places, it shows up differently. MICHEL: I don't use the word efficiency so much because it's limited. There are techniques to improve manufacturing performance in every aspect of it, efficiency only being one of them, and these techniques are pretty universal. Now, when you're trying to help people in different countries, it's a postulate. You have to postulate what works in one place will work in another. So far, I haven't found any reason to believe otherwise. I have encountered many people who are saying things like, "This is country X, and these techniques don't work because our people are from country X." It's one of the most common techniques to refuse to implement anything new. The fact is the Toyota Production System wasn't supposed to be applicable to American workers until Toyota applied it with American workers in its joint venture with GM in the early 1980s at NUMMI specifically. It became a showcase. Later, Toyota opened its own factory in the U.S. in Georgetown, Kentucky, and applied the system there. And then, a few years later, it opened its own factory in France, and it worked with French workers. So it's really the idea that this only works in certain cultures or this only works in Japan. It's just the reality is different. It works pretty much everywhere. TROND: Well, that's fascinating, though, because, like you said, you have immersed yourself in these different factory and industrial cultures, if you may, and you are implementing lean in all of them or advising on lean methods. Why don't we start with that, then, perhaps? Tell me a little bit, what is lean to you? MICHEL: Lean to me...and I use the term less and less because I think over the past 30 years, it's lost a lot of its meaning. When it first came out, it was the latest in a number of labels that have been applied to the same thing. In the early 1980s, you talked about just-in-time then there was world-class manufacturing. A number of different terms were used and never really caught on. This one caught on. And the way I took it, I took it to mean generic versions of the Toyota Production System. There are very good reasons why you can't call what you're proposing to a company that makes frozen foods a Toyota Production System. There are also very strong reasons why you can't even go to a car company and do this. It's very awkward for a car company to openly admit to be using a competitor's system. So you have to have a label that refers to the content but doesn't refer to where it's coming from. TROND: So for you, at the basic level, if you strip away everything, it still is essentially the Toyota Production System, and lean is just to you, I'm just paraphrasing, it's a convenient wrapping for a way to explain it in a way that's non-threatening. But it is essentially the lessons from the Toyota Production System from a while back. MICHEL: That's the way I took it. That's why I adopted this label in the early 1990s, but a lot of time has elapsed since then. Because it became popular, very many people started using that label. And the content they were putting under it was pretty much...they were attaching this label to whatever they were doing. It has lost a great deal of its meaning which is why at this point, I rarely refer to it. TROND: So you're saying a lot of people are attaching lean to whatever they're doing, I mean, understandably so, Michel, right? Because it's become a very successful term. It sells books. It sells consulting. It does refer back to something that you think is real. So can you understand why people would do this if you are in consulting, or even in teaching, or you work in an industry, and you're managing something, why people would resort to this label? MICHEL: First of all, consultants have to have a brand name for what they're selling. It was useful. As a brand name, you have to call what you're offering by a given name, and clients look for this. It's a keyword they look for, and that's how they find you. So it's really necessary. I'm not criticizing consultants for using that. TROND: No, no, I understand it. And, I mean, you're also a little bit in a glass box in the sense that you are within the general tent of lean yourself. So I understand that. I fully understand it. MICHEL: What happens when it's successful is that more and more people jump on this bandwagon and say, okay, I'm going to offer a lean. When you look at what they're saying, it does not reflect the original content. By about 2000s, it had evolved into...what most consultants were offering was drawing value

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "How Academia Shapes Manufacturing". Our guest is John Hart (https://www.linkedin.com/in/ajhart/), Professor of Mechanical Engineering and Director at the Center for Advanced Production Technologies at MIT. In this conversation, we talk about John's research on micro and nanotechnology and material science, which universities and colleges that teach manufacturing, the role of MIT in this ecosystem, and why now is a key moment in manufacturing history. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 92 on Emerging Interfaces for Human Augmentation (https://www.augmentedpodcast.co/92). 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: There has never been a more interesting time to be in manufacturing or to watch manufacturing. The tremendous breakthroughs that we are about to witness have been made possible by a confluence of emerging technologies and startup innovations, as well as a growing awareness of the importance of building human-centric technologies. We are indeed at a crossroads with profound challenges in the growing talent shortage, the need for workforce training, an aging industrial base, and the demands for manufacturing competency from the wider innovation ecosystem. We have to make progress fast, and innovations are just maturing to be able to do so at the scale and pace required. It will, again, be amazing to watch the manufacturing industry. Parts of it will perhaps, again, become the industry of industries. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented reveals the stories behind the new era of industrial operations where technology will restore the agility of frontline workers. Technology is changing rapidly. What's next in the digital factory, and who is leading the change? And what are the skills to learn and how to stay up to date on manufacturing and industry 4.0. In this episode of the podcast, the topic is How Academia Shapes Manufacturing. Our guest is John Hart, Professor of Mechanical Engineering and Director at the Center for Advanced Production Technologies at MIT. In this conversation, we talk about John's research on micro and nanotechnology and material science, which universities and colleges that teach manufacturing, the role of MIT in this ecosystem, and why now is a key moment in manufacturing history. Augmented is a podcast for industrial leaders, for process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. John, how are you? Welcome. JOHN: I'm well, Trond. Great to see you. Thank you for having me. TROND: Well, I'm excited to have you talking about...well, hopefully, a lot of different things, but how academia gets to shape manufacturing, this fascinating venture that is manufacturing. But you yourself, John, you grew up in Michigan, is that right? You were close to this from an early age. JOHN: I was close to it. Yeah, I grew up in Royal Oak, Michigan, a suburb north of Detroit. If you know the Detroit Metro area, there are the mile roads, and the Detroit River is sort of Zero Mile. And I grew up between 14 and 15 Mile Roads, so in the hotbed of the good, old U.S. auto industry. TROND: Well, exactly. Because looking a little bit at your background here, you spent quite a few years as a summer intern at General Motors before you got yourself to...or actually perhaps in the beginning, in your undergrad years from UMichigan, is that right? JOHN: I did. After my first year at UofM, I worked as a summer intern at GM and went back a few years in a row in different roles in different areas. And honestly, when I decided to pursue a graduate degree and ended up at MIT, I thought I might just get my master's and go back and work in the auto industry, but things changed, and here we are today. TROND: Well, here we are today. You got yourself an undergrad from UMichigan. And you worked there for a little while, I believe, but then came to MIT with a master's, Ph.D. This is way back. But you won the prize for the best doctoral thesis in micro and nanotechnology. So that set you off on the path to rediscover nanomaterials, I guess. JOHN: Yeah, well, it's a really maybe exotic combination of topics. My master's thesis was on precision machine design, the design of these large mechanical couplings for industrial robots. And then, for my Ph.D., with the same advisor, I worked on carbon nanotube synthesis. But there you have the dipoles of manufacturing research, materials, processing, and mechanical design that have shaped how I've taken things forward since then. TROND: Well, but it is in these unique combinations that innovation starts to occur, right? JOHN: Yeah, exactly, combining different topics. And that's one reason I love manufacturing is that it is the union of materials processing, and automation, and software, and now also getting more interested in the organizational workforce aspects. It's a very rich, multidisciplinary layered topic. TROND: Yeah. And we'll explore this both from the organizational angle, and, indeed, I'm super interested in this material angle on things because it seems to me like you're exploring the very, very small nanostructures, but then you're then printing them on the very large canvas. So you're exploring materials from one extreme to the other. JOHN: Yeah. Well, it depends on your objective and what topic you're working on. There are cases in our research where we need to understand the formation of materials, not quite from the atom up but from the nanoscale or microscale up. And there are cases where we more or less abstract or coarse grain those link scales and focus on macroscale properties. TROND: Well, and then you also focus quite a bit on teaching. I noticed that you actually launched the first massive online course on manufacturing processes, and hopefully, we'll get to this a little bit as well. JOHN: Sure. TROND: But teaching and basically working on the next generation of manufacturers, whether they be the engineers or really anybody else, has certainly been one of the big challenges in manufacturing really forever. What is it that fascinates you so much about teaching this to a grander audience than the usual university audience? JOHN: Well, first, I'll say I believe that the top priority of universities, including in the area of manufacturing, is to educate future leaders and engineers. That said, the number of people we educate on our campus is a small fraction of those who could really benefit from what we teach and the way we teach. And that's not just geographically, but it's also in terms of their role in the workforce. So I believe manufacturing education should address all levels of the workforce. And to get at your question more directly, when I came to MIT, I was asked to take over our core undergraduate manufacturing class in the Department of Mechanical Engineering. And as I learned to teach the class for myself, I was intrigued by this emerging trend of digital learning, and this was 2015, 2016. And I was able to get some funding from MIT internally to create an online version of the course that would be offered free to the world, and probably 100,000 People have taken it so far. And it's been a great experience and evidence of how there is very broad interest in manufacturing really across the world. TROND: 100,000 people have taken this course. JOHN: Yeah. Well, I'll say 100,000 people have signed up for the course. This is the classic trade-off with online courses. It doesn't mean 100,000 people complete the course. It means that number signs up and hopefully took something away from it. It also speaks to the flexibility. You can sign up for a course and maybe just listen to one lecture, but if you take something valuable away from it, that's great. TROND: So I wanted to talk a little bit about how academia shapes manufacturing. And I know that there are, you know, you and I work at MIT, and you've had experiences obviously at University of Michigan. But there are other manufacturing centers and institutes all around the world. Could you lay out this landscape a little bit for us so that we get a sense of where the excellent centers of manufacturing are located? I mean, one structure, just to pick that, is manufacturing institutes, and I know that's sort of dear to your heart for a couple of different reasons that we'll get into. But what are some of the centers beyond MIT where there is activity that is organized in a way that really is something to focus on? JOHN: First, I think of in the U.S., Carnegie Mellon, Georgia Tech, Purdue, Michigan, Stanford, places that have defined manufacturing centers or have a body of work that relates to manufacturing that I would say there's a critical mass of faculty, and students, and affiliation with industry. Also, Penn State in the area of additive manufacturing and product design. It's hard to be comprehensive. I don't want to forget anyone big, but that's a sample of some of the notable ones. Internationally, a lot of activity in Europe; I admire the University of Cambridge, the Institute for Manufacturing there, where manufacturing is more or less a department, or it's within the Department of Engineering, which is analogous to what we would say is a school or college of engineering here in the U.S. And they have a broad set of activities that have been there for decades focused on manufacturing at the IFM. TROND:

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Innovating Across the Manufacturing Supply Chain. Our guest is Antonio Hill (https://www.linkedin.com/in/antonio-hill-3a4916244/), Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker (https://www.stanleyblackanddecker.com/). In this conversation, we talk about lean leadership, productivity, the challenge of digital transformation across operations and supply chains, and how augmented lean means every organization has their own transformation approach. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 94 on Digitized Supply Chain with insights from Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson (https://www.augmentedpodcast.co/94). 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: Stanley Black & Decker is a huge organization where any improvements by tweaking their own operations or by adding insight from what happens along the whole supply chain can mean significant productivity gains. I find it interesting that they have their own version of the augmented lean approach tailored to where they are and, most importantly, building on the insight that the workforce is where the innovation comes from. By giving shop floor workers access to insights on big-picture manager deliberations, they are freed up to operate not only more efficiently but also more autonomously. When all of industry works that way, manufacturing will make tremendous advances more rapidly and sustainably than ever before. 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 Innovating Across the Manufacturing Supply Chain. Our guest is Antonio Hill, Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker. In this conversation, we talk about lean leadership, productivity, the challenge of digital transformation across operations and supply chains, and how augmented lean means every organization has their own transformation approach. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Antonio, welcome to the podcast. How are you? ANTONIO: I'm good. How are you doing? TROND: I'm doing great. I'm looking forward to thinking and talking about manufacturing supply chains and the rollout of digital technology. So, Antonio, you are actually a business major by origin from North Texas, and then your master's is in HR. And then you're fashioning yourself as a lean leader and an operational expert working on productivity and now much on digital transformation. And you're heading the rollout of digital solutions for Stanley Black & Decker. I'm curious, what was it that brought a business major into the manufacturing field? ANTONIO: For me personally, businesses is great. I'm a big advocate of free markets. And so for me, the whole time you think of how widgets are created and wanting to understand that aspect in manufacturing, creating widgets. Like you were saying, with a master's in human resource development, my thoughts there were learning that a lot of the cost from any organization is going to be labor and material. So having that understanding was great. And then transitioning to making widgets and learning under some ultimate awesome leaders in the space along with great engineers that really, really, hand in hand taught me so many things. And then one of the leaders in lean as well having hands-on conversations, walking the site with this person that is known for lean just really, really strengthened my capabilities. But the thought of the digital side is always going to come into our space, in our world. And so to be able to do that for a large fortune 500 company is obviously amazing. I'm like a kid in the candy store. TROND: [laughs] ANTONIO: Those concepts really changed the way from an organizational side because business is business no matter how you look at it. We're trying to improve our margins and capture market share just like anyone else. But ultimately, it's just a different way of doing it. TROND: I wanted to stop a little around lean first because in our pre-conversation you said lean touches everything. I'm just curious, what do you see as the key things in lean that you have learned that you are bringing into this work that we're going to be talking about a little bit? ANTONIO: I think that it boils down to a way to create continuous improvement by impacting ultimately the lead time. I'm part of the global supply chain so obviously, I'm always looking at a holistic approach. That's why it's all aspects for me from a business standpoint. At the same rate, from a lean perspective, we can find waste in anything. So there are always opportunities to improve in that aspect in every single function. Every function within the organization can be an aspect of lean. So that's the part for me that I get excited about, and I've touched every single function. So it's really an opportunity for any organization to continuously improve on and removing what they say muda from the origination of the concept in any organization. TROND: I'm curious; some people would say that lean is or I guess was important early on but that contemporary organizations are somehow different, and digital, which we'll talk about, is one reason, but there are perhaps other things. What are some of the things that you, I mean, I don't know if you agree with this, but what are some of the things that you're incorporating into your thinking here that may be either different or where you have to adjust it to the organization you're actually in at any given moment? I'm just curious. ANTONIO: You're thinking lean from a digital standpoint or just lean? TROND: Well, lean was developed in its original form a very long time ago. So I guess the first question I'm asking is how can you be confident that the original insights are still valid? Is that because you're walking around and experiencing it every day, and it resonates with you? I guess, firstly, just curious about what lean generally means today in an organization like yours, and then obviously, we'll talk about the rollout of digital solutions, which you've been doing so much now. ANTONIO: Right. And that's a great question, and I'm excited to be the person that has to answer that question. TROND: [laughs] Well, you didn't think I was going to give you easy questions, Antonio. [laughs] ANTONIO: Lean, the concept, I think, will never go away. And so for those that think that it will, really do not understand engineering from that standpoint because when you think about engineering, an engineer solves problems. And so we know number one, there's always going to be problems. I'm sure that there are a lot of people that say, "Hey, I got something for you to solve. I got a problem for you," so from that perspective, we know. But then, on top of that, think about innovation from an engineering standpoint, as you see something improved, even if it's making it better, even if it's something like making it better for the customer, ultimately, that transition of change even the slightest or something large, every organization has to do it. They have to embrace it. And so a person that knows those techniques, that are really good and seasoned and experienced, which I would say I do fit in that; I feel mighty confident in that space, and I feel mighty confident in manufacturing, we could see it quickly. You see it immediately. Like, you see a process, and it just stands out. And I think that you can't wish that away to be able to see the inefficiencies of any system. And if you do not have a system in your approach, then that to me is already folly, you know what I mean? Like, that's an error. If you can't create systems, especially in manufacturing, I think that that's no bueno. [laughter] TROND: Got it. I'm then curious, digital. How does digital factor into all of this? So I guess I'm understanding a little bit more of your conception of continuous improvement, lean, whatever you really want to call it, and engineers that are such a crucial part of the kind of organization you represent, Stanley Black & Decker. So now, clearly, there's been a push in most organizations across fields to go digital and arguably, manufacturing organizations perhaps were resisting it a little bit because there was such an amount of automation in there already, and then now comes digital on top of that. And has it been easy? Has it been difficult? What goes into even the decision to say, "We're going to have a major digital transformation?" Tell me a little bit about the journey that you've gone through with Stanley in that respect. ANTONIO: So, really great question. And so I'm going to take you down a little bit of a history lesson and introduce how it impacts. So when you think about things of the world, because you always have to relate to what's going on in the real world, you have the introduction of the smartphone. You have to credit that smartphone for that interaction of this interface because it's putting that into a lot of operators' hands to interface with something. Now, when you think about digital, indus

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "Augmented Lean Prelaunch." Our guest is Natan Linder (https://www.linkedin.com/in/linder/), in conversation with host, Trond Arne Undheim. In this conversation, we talk about the background of our co-authored book, Augmented Lean (https://www.amazon.com/Augmented-Lean-Human-Centric-Framework-Operations/dp/1119906008), a human-centric framework for managing frontline operations, why we wrote it, what the process has been like, the essence of the Augmented Lean framework, and the main lessons of this book for C-level executives across industry. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 96 on The People Side of Lean with Professor Jeff Liker (https://www.augmentedpodcast.co/96). 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 revolutions are rarely chronicled as they are happening, but this industrial revolution will be. There is an ongoing shift in the way technology and workforce combine to produce industrial change, and it is happening now. We are lucky to be situated in the middle of it. And I personally feel fortunate that I was brought along for the ride. It has been a life-changing experience to realize the power and impact of living through a shifting logic of manufacturing and, perhaps more importantly, to realize that as excited as we can be about automation, an augmented workforce represents the best combination of the most important technology we have which is human workers themselves with the second best machines that humans create. The fact that making humans and machines work together is no trivial task has been pointed out before but documenting what happens when it does go well in the biggest industrial companies on the planet feels like a story that deserves to be told. 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 Augmented Lean Prelaunch. Our guest is Natan Linder, in conversation with myself, Trond Arne Undheim. In this conversation, we talk about the background of our co-authored book, Augmented Lean, a human-centric framework for managing frontline operations, why we wrote it, what the process has been like, the essence of the Augmented Lean framework, and the main lessons of this book for C-level executives across industry. Augmented is a podcast for industrial leaders, for process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Natan, good to have you in the studio. How are you today? NATAN: I'm great. How are you? It's been a minute. TROND: It's been a little minute for us. It's crazy with book launches. It takes a little out of you. And you are running a company in addition to that, so you had some other things on your plate too. NATAN: Yep, running a company and having a book coming is an, I don't know if an artifact, but definitely, company is a lot about changing the status quo. And the book tries to capture a movement. So I think they go along nicely. TROND: Yeah, Natan. And I wanted to bring us in a little bit and converse about why this book was written. Certainly, that's not my benefit. You brought it up to me. But what were we thinking about when writing this book? So I want to bring it back to way before I came into the picture with the book because it was your idea to write a book. What was on your mind? What were the main reasons that you thought I really want to write a book? NATAN: When I was coming up as an engineer...and my background, I'm not a pure manufacturing production type engineer, but I've been around it my entire career just because of the type of products that I've been involved with whether it's mobile phones, or robots of all sorts, 3D printers. So you get to spend a lot of time in these operational environments, shop floors, machine shops, and the like. And when we started working on Tulip, it was pretty clear pretty quickly that there's a moment that is emerging in operations that no one has captured the story. And this is back even; I don't know, maybe five or six years ago. We are maybe one or two years old, and I'm already starting to think about this post-lean, or classical lean movement that I'm sure is happening. That really is the genesis of the book in the early, early days. And fast forward to when we started talking, I think we got Tulip off the ground. But really, that was a platform to meet all those different people who helped operations transform digitally, whether it's all sorts of consultants, or academics who are researching operations, or business leaders, you know, tons of factory managers and the engineers that work with them, and the executive, so a whole bunch of people. And they're all basically talking about the same thing and the deficiencies in lean, the complexity of technology, and how they're trying to change, and it is so difficult. So I think that's a good description of the landscape before diving in to try and capture what the book attempts to capture. TROND: Yeah, Natan, I remember some of our early discussions. And we were dancing around various concepts because clearly, lean is a very broad perspective in industrial manufacturing focused on reducing waste and many other things. It's a broad concept that people put a lot of different things into. But I remember as you and I were thinking about how to describe this new phenomenon that we do describe in the book, we were thinking a little bit that a lot of these new influences come from the digital sphere. So there's also this term agile. There are some people who say, well, you know, let's just replace lean because it's an outdated paradigm. And I remember you were quite adamantly arguing that that's not the case. And this goes a little bit to the message in our book. We are in no way really saying that lean isn't relevant anymore. NATAN: On the contrary. TROND: Tell me a little bit about that. NATAN: A really simple way I think to frame it is that whether you're practicing lean formally or some variant of it, of lean, or Six Sigma, or some program that formalizes continuous improvement in your operation...and we're talking about frontline operations. We're talking about factories, and labs, and warehouses, and places like that. You are practicing lean because this is how the world..., even if you're not doing it formally; otherwise, you're not competitive. Even if you're in a bank or a hospital, you might be practicing lean. And that's where agile comes to the picture, and it was adopted widely by operations practice in general and pushed into areas that are not pure manufacturing. So, in a way, lean is a reality. Some organizations are more formal about it, some are less, but definitely, they're doing it. Here's the issue, and this is the main thesis of the book. When lean came about...and we know the catalyzing text. We know the teaching of Taiichi Ohno. We know about The Goal. We know about The Machine That Changed the World. And those are seminal texts that everybody reads. And we know about Juran and lots of great thinkers who thought about operations as a data-driven game, some from the school of thought of quality, some from pure operation research, some from how do you put emphasis on classic just-in-time, Kanban, Kaizen, all those continuous improvement things. But at the end of the day, all of that thinking, which still holds true, was not done when digital was top of mind, where data is everywhere, where people need to live in such data ecology. It was done, so to speak, in analog times. And it doesn't mean that the principles are wrong, but it doesn't mean they don't need to get augmented. And this is maybe the first time where this idea of augmentation, which, to me, augmentation is always about...I always think about augmentation from a people's perspective or an org perspective. It's just a collective of people. That's where it starts, and that's where we had something to say. So that's one aspect to think about. The second big one is actually very simple. It's kind of like; we heard ten years of industry 4.0 is going to change everything, and all we got is this lousy OEE graph. And that's kind of like a little tongue-in-cheek on we were promised flying cars, but we only got 140 characters. I mean, come on, stop talking about industry 4.0. It's like, who cares? If the tools and digital techniques and what have you is not adopted by the people actually doing the work, that then collectively, one engineer, another engineer, another operator, a team lead, the quality lead, and so on come together to transform their org, if that's not happening, then that's not sustainable transformation, and it's not very relevant. Again, augmentation. TROND: Right. And I think, Natan, that's where maybe some people are surprised when they get into this book. Because it would be almost tempting to dismiss us as traditionalists in the sense that we are not really going whole hog into describing digital as in and of itself, the core of this principle. So there is a little bit of a critique of agile as an idea that agile or using that as a kind of a description for all digital or digital, right? That digital doesn't change everything. And I guess I wanted to

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Decarbonizing Logistics. Our guest is Alan McKinnon (https://www.alanmckinnon.co.uk/), Professor of Logistics at the Kühne Logistics University of Hamburg (https://www.the-klu.org/). In this conversation, we talk about the huge tasks of mitigating and adapting to climate change throughout industrial supply chains. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 68: Industrial Supply Chain Optimization (https://www.augmentedpodcast.co/68). 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: Decarbonizing logistics without slowing economic growth is a formidable challenge which requires paradigm shifts across many industries, as well as adopting openness principles from the virtual internet onto the physical nature of the supply chain, as well as facilitating new business models, sharing, and standardization, and eventually dematerialization. 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 Decarbonizing Logistics. Our guest is Alan McKinnon, Professor of Logistics at the Kühne Logistics University of Hamburg. In this conversation, we talk about the huge tasks of mitigating and adapting to climate change throughout industrial supply chains. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip. Alan, welcome. How are you? ALAN: I'm very well, thank you. TROND: I'm super excited to have you, Alan, you know, an academic that has transformed and seen the transformation of a field that barely existed when you started. Some 40 years in academia and logistics and now being part of this exciting experiment with creating a whole new university focused on logistics. It's been quite a journey, hasn't it? ALAN: It certainly has. I think this is my 43rd year as an academic. My colleagues often think maybe it is time to retire, but the subjects in which I specialize, which we'll be talking about in a few moments, like decarbonization, are sort of hot topics at the moment. So I'm very reluctant to phase myself out. So it's been an enjoyable 40-year career, I must confess. TROND: How did you get to pick this area? It's obviously not; I mean, now, because of the pandemic and other things, logistics or at least supply chains is kind of on everybody's mind because we're not getting whatever product we want or maybe some sort of interest in green practices. And we're starting to realize that transportation is becoming more of an issue. People are worried about that. How did you get into this area? ALAN: My interests initially were in transport and particularly freight transport. In fact, right at the beginning, it was actually a crime, believe it or not, which got me into this area. TROND: [laughs] ALAN: Because I'd done my masters at UBC in Vancouver. I returned to London to do my Ph.D. at the University of London. This was in 1976, a long time ago. And I had spent three or four months reading up on the subject of freight modal split, you know, why so much freight goes by road and so little by rail. And I'd compiled all my notes, and my briefcase was stolen. [laughter] So the day before that, I'd been to visit a professor at the London Business School who said to me, "The freight modal split topic has been very much researched." He said, "You're a young man. Why don't you go out and find something new to bring a new perspective to this subject?" And around then, the subject of...it wasn't called logistics back then; it was called physical distribution, right? TROND: Hmm. ALAN: Where you saw freight transport in a broader context linking it to inventory management, to production planning, to warehousing, and so forth. And so I began reading up on that subject. And that then became the main theme of my Ph.D., which I think was one of the first PhDs done in the UK on that subject. So you could say that it was the person that stole my briefcase way back in 1996 [laughs] that played a part in me discovering logistics as a field, and that's occupied me for 40 years in my academic career. TROND: And on that journey, you have entered in and out of different fields. I noticed that you were a lecturer in economic geography in the beginning. So there's a very interesting, I find, physical component to logistics, obviously. How does geography enter into it for you? ALAN: Well, I see transport and logistics as essentially a spatial subject. My Ph.D. focused on the geographical aspects of logistics, you know, where you locate the warehouses, how you route the vehicles, you know, so much logistics planning has a geographical component. But the thing about logistics as an academic discipline is that it's drawn together academics from many different disciplines. Many have come from a mathematical background, from engineering, from economics, in my case, as I said, from geography. And that, I think, is one of the strengths of the subject area, that it has got this interesting interdisciplinary mix. And that allows us, in a sense, to deal with a whole range of policy issues, of industrial issues, I mean, from land use planning to environmental issues, which we'll be talking about in a moment. I've really enjoyed engaging with academics really from different disciplines over my career as an academic. TROND: Well, and we'll talk about these things in a second. But, I mean, it's not just academics, right? Because the subject is so non-academic in a sense, right? [laughs] It's actually very alive, and it affects all of us. So people may not have been super aware of it. But, like you point out, it's very multidisciplinary. Now, how did this startup University concept come about? You've moved to Hamburg or spent a lot of time in Hamburg with this KLU university for logistics, essentially, which sounds to me like a daunting prospect to create a new university based on a new discipline in Germany of all places. ALAN: So I'd been 25 years in my previous university here in Edinburgh where I'd set up a master's program in the subject and a research center. And then, in my late 50s, I got the opportunity to go to Hamburg and to join what was a startup University. I mean, when I joined, I think we only had nine academic employees. We only had about 40 or 50 students in total. So it was a challenge. And a bit of background on the university; it is a legacy project of a very wealthy man, Klaus-Michael Kühne, who is the majority owner of Kuehne+Nagel, which is the world's biggest freight forwarding company. And he also owns about a quarter of Hapag-Lloyd, one of the world's biggest shipping companies. And he, in a sense, wanted to give something back to the industry, and so he founded the university in 2010. So it's now 12 years old, and I think it's been a very successful enterprise. We're still niche, obviously. We've got, I think, about 27 or 28 professors, about 500 students. But we have this focus on logistics and supply chain management. And there are also quite ambitious plans to globalize the university, to open up satellite KLUs around the world. So I was just very lucky really to get involved in this in the early stages and do my bit to help to shape this institution. TROND: Well, you're lucky but obviously enormously accomplished. I wanted to talk a little bit about your 2018 book: Decarbonizing Logistics here. So this came out on Kogan Page. I also published on Kogan Page. It's a great UK-based publisher. Tell me a little bit about decarbonization overall and what you see as the main opportunities but also the challenges. It seems to me there's a lot of talk of decarbonization, but the subject that you are attacking it from is one that points out a lot of the limitations of these visions of changing the world into a decarbonized world. They're very physical limits and very real practices out there in various industries. How can we kick off this discussion on decarbonization? What is the best way to understand the biggest challenge here? ALAN: If we confine that to logistics, to put that into perspective, I think in my book, I reckoned...I pulled together as many numbers as I could, and I reckoned that logistics worldwide accounted for about between 10% and 11% of energy-related CO2 emissions. I've now revised that upwards, so I think it's probably now closer to 11% to 12%, most of that coming from freight transport but some of it from the buildings, from the warehouses, and the freight terminals. To my knowledge, nobody has yet carbon footprinted the IT and administrative aspects of logistics, but that could maybe be up half a percent or thereabouts. And there's a general recognition that Logistics is going to be a very hard sector to decarbonize for three reasons: one, because of the forecast growth in the amount of freight movement worldwide over the next few decades. Second thing is because almost all the energy currently used in logistics is fossil fuel, right? So we're going to have to convert from fossil fuel to renewables. And the third thing is the length of the asset life because ships would typically have an asset life of 25, 30, 35 years; planes, likewise, trucks are a bit shorter, maybe 10 to 15 yea

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 precurso

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