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 Operator 4.0. Our guest is David Romero, Professor of Advanced Manufacturing at Tecnológico de Monterrey University in Mexico. 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. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. David, welcome to the show. How are you? DAVID: Fine, fantastic. Looking into another exciting year pushing more the human centricity in manufacturing. TROND: Yeah, it's going to be an interesting year for sure. There has been some automation already. You're not new to automation. You've been looking at it for a while. First, I'm curious, always curious how people got into manufacturing. I'm going to make an attempt to sort of summarize what you've been up to, and you tell me if I'm getting it right, David. So you got your Ph.D. from Brisbane in Australia, if I'm not mistaken, from Griffith. You have a sort of a mix of science, and engineering, and management background. And you are a mix, also, of academic and practitioners. You emphasize that you're a pracademic. You're trying to solve practical problems. I also notice in your background you are a certified Lego facilitator. That enthuses me quite a bit. So I don't know if this reflects what you're up to, but obviously, your title is Professor of Advanced Manufacturing at the Tecnológico in Monterrey University in Mexico. David, all of this stuff, how did it start? So manufacturing and engineering, was that always what you were going to do? DAVID: I always liked technology. So, of course, some years ago, computers were the technology. And somehow, I started when graduating from bachelors. I start programming CNC machines, and I discover the manufacturing world, and then from programming machine tools to programming robots. So I started my journey to, let's say, in practical terms from being a computer scientist, becoming a mechatronic engineer, and then really getting in love with the shop floor, and with the people, and with the processes, and the magic triangle of people, process, and technology. And somehow, I ended up becoming an industrial engineer. That's also why management aspects are relevant for me. And people now it's my main motivation in the shop floor, how we can support them. TROND: So how does this gaming approach come in, serious games and this whole game-like approach? At some point, you took this facilitator course. DAVID: As a professor, of course, lecturing is an important aspect of your job. It is not just doing research. So for us, it was always interesting to look at how we can make our lectures more engaging. But somehow...just recently, with some colleagues who were from West Virginia University, we were writing a paper on gamification of manufacturing. And I guess, you know, in many podcasts, you have discussed about this topic of the challenge of attracting young generations into the shop floor. So it seems that these gamifications, you know, all these studies, are becoming handy nowadays. TROND: Academically, you have made yourself a name around this concept of operator 4.0. So I thought we would dive straight into that. What does operator 4.0 mean, David? DAVID: It means really that we need to change our mindset. And just to give you a little bit of background; actually, you interviewed also for another podcast Johan Stahre from Chalmers University of Technology. So what we noticed was in 2011, the term industry 4.0 made its debut in Hannover Messe. And in 2015, there was this famous article in the BBC about if a robot will take your job. And to be sincere, I was quite disappointed, and I called Johan, and we started discussing, you know, why we have this mindset of human versus technology, why we're thinking in this way, why we cannot think in terms of human plus technology. What would be the possibilities of that? And we started to look into how we can treat these new industry 4.0 technologies not as replacing technologies but as collaborative and augmenting technologies. And we say, okay, so if you have an exoskeleton and you put it into a human, you make it stronger, and it has more endurance. Okay, so this is sort of a type of augmentation. If you have a collaborative robot, it's a third arm for the human. So this is sort of collaborative technology and how we can call all this way of seeing technology in a different way. And then we started looking into a sexy term. And we saw that nobody had claimed, at that point, the term operator 4.0. So we said, let's call it operator 4.0, and let's try to bring a more human-centric perspective into the Fourth Industrial revolution technologies. TROND: Yeah, I mean, it's fascinating. So in one of the original articles, I believe it was back in 2016, David, you set up eight scenarios you called them because I guess you were really talking about something that hasn't fully emerged or hadn't fully emerged by 2016. So if I am going to try here to summarize, and maybe you can give me some meat on the bone, but you divided it into all these different capabilities. So one is quite separate, I guess, because, you know, super strength, so that has to do with physical strength. But most of these other aspects are cognitive aspects, but you had these divisions between them. So you talked about the augmentation capability, what others would call AR perhaps, and then the virtual capabilities of not having to be there at all. But you also brought in the notion of being healthy, so the idea that workers can have trackers that are monitoring their health, I guess, during what they're doing, which I found kind of interesting. There's one of them where you talk about being collaborative with robots, so the cobots sort of aspect of automation and augmentation. And then there's even a social aspect where you talk about, I guess, enterprise social networking type factors. And then lastly, I think we're at eight, is the analytical aspect; some workers are now able to fully build on data analytics during their work. So how distinct are each of these? And when you called them scenarios in 2016, does that mean that they're still not fully effectuated? Are they still kind of a future vision? DAVID: No. I think we were quite surprised recently with the people of the World Economic Forum. I was asked to just give a brief overview of what has happened exactly over the last years and from 2015, and this famous article that I mentioned about industry 4.0 and a robot will take your job. Now to 2022, where in Davos, we had this paper on the "Augmented Workforce," it seems that we quickly, in just seven years, changed our mentality in regards to the technology. And now we are really looking at technology and the possibilities of technology and the whole spectrum of using technology to create new ways of working. And, of course, these new ways of working will still include full automation because, of course, there are some activities which are repetitive. They are ergonomic and so one where automation is relevant. And there are some activities where we just need some little help as workers to conduct our work appropriately. And then we have assisted work there because, of course, we want to keep the work engaging for the workforce. And there are some collaborative technologies where we really need help. It is not just a simple assistant. It is really to have help to do the work with performance and the quality expected. And then, of course, there's augmentation. So it's the whole spectrum of possibilities that we want to look at that now we see that industry is starting to play with this whole spectrum. And now, the whole spectrum is being simplified and called workforce augmentation phenomenon. And I think that's really making a reality what, at that point for us, was a vision for the operator 4.0. And we describe it in terms of these eight types of visions of the operator 4.0, how technology could play a supporting role for an augmenting role for the work, being in the physical capabilities of the human or the cognitive capabilities. TROND: Industry 4.0 is, by some people, viewed as a very technology-heavy and technology-driven certainly solution or an idea. Nowadays, would you say that the approach that goes more towards an augmented workforce is becoming more value-driven because of that? And where do we stand on that argument? I believe you had another fairly recent article where you were talking about the coming shift towards more value-driven approach. DAVID: History goes in cycles. I mean, for me, it's interesting to go back, perhaps, and look at what was happening in the '80s. In the 80s, we had this vision of the lights-out factory. We still use that term. General Motors has spent close to $2 billion in trying to create such types of factories without humans. And they spent almost a decade trying to do that. And then, most recently, we had the case of Elon Musk and their Gigafactory, trying to have a factory dominated by robots and machines. And after a couple of months of operations, they had to fire the robots and bring back the humans. And it's very interesting to see because even if I go a little bit more from the research perspective here, we were talking about computer-integrated manufacturing in the '80s, and the whole idea was how to fully automate the factories. And a decade later, we change this vision, and the IT guys start to talk about, okay, perhaps we cannot fully integrate systems, but we need to make them talk, so let's talk about interoperation of systems, interoperability. And the people from operational technologies say, okay, let's talk about balanced automation. It's not really going to full automation. Even the people from the lean manufacturing world talk about lean automation, where to apply the right amount of automation to a given task so we can make that task more reliable, more simple, more robust. And I'm bringing this story because if you look into this new industry 4.0 transition into industry 5.0 vision that the European Commission now is presenting, what we're aiming for is for these kinds of things. We want to be able to have a workplace that is more resilient, that is more robust, and so on. And I guess the best way to achieve this is by having the right amount of collaboration between human and technology. And this is not new, I mean, this is something that sometimes we forgot, and we tried to push really hard technocentric vision. And somehow, a couple of years after, we corrected ourselves. Thank God this time, it just took us seven years. Last time, it took us more than 10. TROND: So is that the difference then between operator 4.0 and 5.0? Because operator 4.0 is basically piggybacking on the notion of industry 4.0. So it starts from the technology perspective, and you were describing these different technologies that go on top of the process and the different kinds of aspects and how it impacts the operator. But now you're saying the EU vision for operator 5.0 is a little bit about resilience and a little bit about augmentation on the human aspect of work. And then, of course, with the green challenge, it's also about sustainability and stuff. But largely, it seems to me that operator 5.0 is operationalizing the broader scenarios that you were talking about in terms of making the worker more efficient. DAVID: I mean, we always try to make things smarter. We try to augment things. We talk about smart operators. We talk about smart machines. Coming back a little bit into the history, by the end of the century, we figured out that the most important thing is to design certain capabilities in our production systems. They need to be agile. They need to be flexible. They need to be sustainable. They need to be energy efficient. So at the end, it doesn't matter if you're achieving this with industry 3.0, 4.0, 5.0 technologies. It doesn't matter which balance you are between full automation and manual work. You are using the technologies and your workforce. At the end, as a company, you need to achieve these capabilities to remain competitive. And one of the things that we look into industry 4.0 and operator 5.0 is that after COVID, one of the things that we recognized was that our production systems were not as resilient as we expected. And the most flexible and agile, and resourceful resource that we have in the shop floor is actually humans. But at the same time, we are the most fragile ones; we get sick, we get tired. So we were saying, okay, so can we use these augmentations that we have with operator 4.0 that we look into how to augment certain physical and certain cognitive capabilities to make that fragile system of the production system, which is the human system, more resilient? And then how, again, we can combine it with different sorts...and this is a little bit perhaps two of the aspects of the operator 4.0. typology that we see, again, really becoming a trend, what we call the healthy operator 4.0, using the operator and the trackers. And we saw how trackers were used to check if the worker had any symptoms or not regarding to COVID. But then we say, okay, yeah, we can relate stress levels into productivity and stress levels and productivity into quality. So when we actually need to give a worker a little break, we maintain the quality that we expect from its performance. And moving forward, for us nowadays, we're looking into the future. Meanwhile, the operator 4.0 was a mindset of human plus technology. And it was about workforce augmentation, augmenting work, and, of course, yes, augmenting equipment, building intelligent machines. Looking into the future, we think that we are going to talk about a mindset which is human multiplied by technology. So I think that as we look into the future, what is going to be interesting is to look into this human-machine interaction, human-robot interaction, human-AI interaction, and augmentation, which actually is what is going to allow us to build production systems, I mean, there's in this academic work -- TROND: Yeah, I'm just curious, if we go back to some of these use scenarios, what are some company examples and industrial sub-sectors that are using some of these? So I know you worked with BMW. You worked with, obviously, some larger Mexican companies as well. When did they start exploring these operator-centric augmentation-type technologies? What is their experience? Because, surely, what you're saying here has derived from watching this in some of your research and consulting engagements too. DAVID: Sure. I mean, we started to see the trend appearing in the shop floor around 2017, so very quickly after we start because, you know, industry inspires us. That's why I always say that I'm a pracademic. I go to the shop floor and look at what is happening and try to support the shop floor with a little bit of science. We published this in 2016. By 2017, we already saw some companies starting to play with this idea of making their workforce superheroes and creating the Tony Stark of the shop floor if we want to put it in a more funny way. So the first guys we started looking into exoskeletons was in the Ford assembly line, the BMW assembly line. They were really trying to push this idea of an operator plus an exoskeleton to create the super-strength operator 4.0. And they wanted to do that because they wanted to support ergonomics, and they wanted to support the endurance of their workers so the production line can become more productive. Then we started to see Volvo and also BMW playing with augmented reality to create the augmented operator 4.0. And they wanted to do this for training purposes but also for supporting quality, so guaranteeing that everything was assembled correctly the first time and for people to learn how to assemble things. We started to see also virtual reality, so the operator plus virtual reality, the virtual operator 4.0 in Opel, in Volvo. When they were ordering a new production line, they were waiting for the real production line to arrive. So they start the training, and then they figure out they already had the production line because the production line was designed in a computer-aided system. So what they did is they took those CAD files and made them an interactive virtual reality environment where they can start the training of the workers before actually, the real production line arrives. And then the ramp-up for the new production line is reduced, and that's, of course, money for them that justifies why it was relevant to push for the idea of the virtual operator 4.0 or the operator plus the trackers. Do we have the healthy operator 4.0? We see General Motors. We see BMW with the smart gloves, and the smart watches using it again to guarantee that, for example, smart tools when they're using certain torque in certain machines that you're using the right force in your hand or just to check how is your stress level. Especially we were also doing a project with [inaudible 20:31] furnace company. And we were really checking in real time the temperature of a worker that has to smelt all the iron of the furnace. And then, of course, you really want to provide, because of safety reasons, depending on your body mass. We use it that way. But it's not the most efficient way to do it to really control the temperature of the worker and then suggest really when it's right to take the break, not just an average because every worker has a different mass. If we go to collaborative robots, the idea of the collaborative operator 4.0...BMW, Škoda many companies, especially collaborative robots, become a big hype in warehouses. I think Amazon is one of the biggest examples of using collaborative robots and also augmented reality for pick-and-place operations. It's incredible to see an industry how fast they have adopted all these wearable technologies and how engaged they feel about developing these kinds of projects. 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TROND: So, David, would you say that in these, I guess, less than ten years that have passed has the movement towards more augmented approaches, including embedding with technology onto the worker in terms of, like you said, even with augmented reality and wearables it has gone from just hype and experiments, in your mind, to truly deploying it at scale? Or are we still in many of these eight scenarios? Are companies still sort of testing them out? Or are they launching them wholesale for their whole workforce? DAVID: For sure, they're convinced, and I think we're just in that moment where we are just leaving the pilot purgatory, as it's called, and moving to the scale-up. And even I think that originally, a lot of these ideas were more thought for the regular, let's call them, the regular worker to make them more resilient, more productive. What we're seeing also is applications of this vision in order to support more inclusive workforce because, of course, all these augmented technologies can't support senior operators, can't support workers with a certain disability, can't support the apprentice operators. So I think that there's further potential to the workforce augmentation beyond what we regularly think in terms of the regular operator. I think for me; it's like when we see into the demographic challenges. The idea of workforce augmentation and aiding for certain cognitive and physical capabilities is going to become very handy. TROND: I'm curious because in traditional automation, the downsides are well-known. And you pointed to this article, and there were many articles, but there was, in particular, this UK work from these Oxford economists talking about robots taking over. There are many other studies that were starting to show that, and then some of it has been debunked. But when it comes to this more operator-centric augmentation, are there any downsides there still, even if you are mindful that the technology has to work with humans? One thing that I could think of is, of course, the privacy aspects because if someone's monitoring your health at every moment, maybe the employer gets to know too much about you from your comfort level. Are there any other sort of downsides that you think are very important for a company to keep in mind as they are implementing these more advanced technologies that are mindful of humans, but they're obviously, you know, issues start to arise because it is more advanced? DAVID: The typical one is the one you mentioned, how we should handle personal data. I think it can be handled. I mean, when we look into different IT architectures and how information flow, basically, certain encryption systems can be built through different layers so only the operator can have its own personal information. But then you can aggregate that, anonymize that and push it up into the automation pyramid. But I think the main challenge that we have now, and perhaps it's shifting, is that steel companies are really good at investing in technology but not as much on skills development of the workers. And technologies are as good as their users. And many times, companies say, "Okay, I want to go into this new industry 4.0, industry 5.0 world, but I don't have the money to make the investments in the technology." And my answer is invest in the people. Because once the technology arrives, if your people are trained on how to use the technology, then you're going to reduce the return of investment time of that technology. So it's challenging because also from practice what I've seen is when you look into this capex formats that companies have when they're going to make investments, capex formats or capex are investments in assets. And these templates don't include, let's say, the cost of training the workforce. So many times, you find companies already have the technology at their facilities, but now they're starting to negotiate with the human resources department for the budget for the training. And then that means that the technology that you bought is just sitting down in the warehouse for a couple of months till the workforce is ready with the skills needed to use that technology. So I think we need to really bring closer the shop floor and the human resources department, so these workforce augmentation initiatives at the shop floor are done jointly together. Because nowadays, the reality is training budget is in human resources department, and technology investment it's in the shop floor department. So we need to really bring them together. TROND: Yeah, that makes a lot of sense. But isn't there an argument to be said that technology should become simpler as well, the way it has for consumers in other areas? So enterprise technology on the office worker side has become arguably quite easy to use. I mean, there are far less training sessions when a new social software or even productivity software is introduced. The newer generations are plug-and-play. They're easier to use. And there's the no-code movement also in manufacturing. Shouldn't most of these technologies, despite becoming more advanced, should they not be as easy to use as a cell phone eventually? DAVID: Exactly. And this is actually what I reflect a lot of the time when we talk about human-centric manufacturing or human-centric automation. It's like, are they really human-centric? And this is exactly what you're touching on. Are they simple enough for the workers to understand the technology in such a way that they're actually the ones that are pulling that technology into the shop floor? Technology is so easy for me to understand, and I can really see how technology can help me on the show floor. That me, the worker, I'm the one going to my supervisor and saying, "Hey, you know, I would like to be able to deploy this technology to make my work more productive," not having the top management come in with their workforce augmentation initiative and trying to convince the workers. And that means that from a technological perspective, we need to make it simple, not simpler, because, of course, technology needs to deal with the challenges in the shop floor. So we should not put away the real complexity that exists. And I think this is the aspect of building perhaps smarter interfaces so we can hide the complexity when it comes to programming and interacting with AI, or with a collaborative robot, or with any sort of smart system that we can have on the show floor. TROND: Yeah, that makes a lot of sense. But I guess, on the other hand, when you hide complexity, then you have another challenge at your hand, which is the transparency about the complexity. So I guess you can't win on both sides because the argument around AI is also transparency. So, in other words, if you have this tremendously advanced solution and you're not disclosing to anybody what's happening under the hood...so I guess the simplicity here has to be matched with certain amounts of transparency. What are you being subjected to? DAVID: But also, I think that's part of the challenge. I think we need...and one very important thing to do as we build these systems is, as you mentioned, we need to build systems that promote motor learning. And motor learning needs to happen at a certain point; perhaps at the point of running daily the production line, perhaps you don't have the time to stop the production line. But the information needs to be collected for later on to use it for training. And it's very important if we really want to build such resilient manufacturing systems that the industry 5.0 expects to have. That means that we need to be open and build systems in such a way that technology will teach us, and we will teach technology. Perhaps it will not have exactly on the time when the issue has happened, but we need to promote this motor learning for sure if we really want. Because if technology fails, and many of the times it has happened, and I've seen this phenomenon, especially in Japan. Some years ago, we did a project with a company that wanted to learn how to run again manually their production line because, after a tsunami, the electronics are gone. So our typical production planning systems are gone together with the electronics, no computers. But a lot of them the machines are mechanic, and they were able to really bring it up really fast again those machines to work. But they didn't have any longer the knowledge on how to operate their production line, how to do the management of it. And learning manual first, even though you ended up doing fully automated, is important if you really want to have a resilient production system. TROND: That's interesting because that brings us back to the risks of not just technologies but the risks around society overall. I wanted to ask you so we've been going back and forth between operator 4.0 and 5.0, and I'm just curious for you when you think about the future outlook of industry as you see it and as you research and do consulting on manufacturing industries, what is the future for you? Is that some emerging category far off that you put scenarios onto, and you imagine something far into the future? Or is the future more something that is a dynamic aspect that you use, you know, to think about? I'm just trying to imagine, for example, operator 5.0. Okay, so it was a policy document from the European Commission, which means it's something they want to do and, obviously, they think it's coming. But it's also a statement. It's something they want to create. When you think about operator 5.0, is that something far distant into the future, or are you thinking this is so obvious to you because you already worked on the 4.0 perspective? So you could have called it operator 5.0 if you were even more ambitious, I guess, back in 2017 is my point. So what is the future for you, and what are the additional things? So resilience sounds very simple, but it seems to me that we've been talking about it now for a while. It's a lot of different things. Are there other things that you think are important to think about in the future of manufacturing? DAVID: I wanted to mention a couple of comments ago, but once again, I mean, it's as simple as this. It's like, you want to build systems that are competitive. So most of the time, you need to analyze what are the capabilities that you need to remain competitive. And then, based on those capabilities, you need to find the best way. And that's perhaps a little bit of my background from my Ph.D. as a systems engineer. I want to engineer systems. So nowadays, it seems that resilience, because we live in a very volatile, and uncertain, and complex, and ambiguous market economy and so on, it seems that now resilience is the thing to at least do to be competitive and hopefully thrive in this new environment. So the question then is what we can do to do this. For us, the answer is, which is the most flexible, agile, resourceful resource that we can use to remain competitive? And that's human. And also, one of the things that over the time we have, let's say, started to learn...and I hope my colleagues from the technology vending side don't hate me. But I'm not seeing really companies selling unique solutions to companies. And I really love the original definition of smart manufacturing that United States had. They called it smart manufacturing is the marriage between information technology and human ingenuity. And for us, human ingenuity...and that's why I was stressing about skills development and technology is as good as its users. It's like, if we don't really keep this human centricity all the time, then it's really difficult to create a competitive advantage out of your technology acquisition. And that's the big decision always to make when it comes to how much I'd go to change my process. Because you can use the template process of your vendor, but then that's the same process that he's using as a template for all your competitors. So my question for you is, where's that competitive advantage there? And then, if you really want to have a unique process which gives you the competitive advantage, that means that you need to empower your workforce to understand the process and figure out which are the right technologies and the right amount of automation that you need to bring into that process to make it unique and make it competitive. Again, that's true human centricity. That's what we will call human-centric innovation when we really focus on empowering the human and empowering the process with the technology. TROND: Just the last challenge here because in this EU notion of operator 5.0, there is also not just resilience, but there's this sense of an ecological awareness and also measurement tools and stuff that bring in the industry's responsibilities to be more mindful of not just human-centric, I guess, but ecology-centric. Are you seeing any technology tools there that are promising? So there are carbon monitoring type frameworks. And there's a lot coming down the pike. But do you see anything real in factories today that are making a contribution towards that kind of resilience? So beyond human centricity into ecosystem centricity. DAVID: For us, from the perspective of the operator 4.0, I think what we can do with the trackers of the workers, again, we have this resistance when it comes to sharing personal information and certain mindsets in certain unions around the world. But I can tell you I'm doing nowadays a big project with a company here that we had the chance to put wearable trackers to monitor the health of the workers in the production line. And they were really excited about being able to be monitored. Of course, we say that information will be anonymous, and so on. But they were really seeing the changes in the quality of the work because, for us, in this experiment that we were doing, what we wanted to relate was stress versus productivity. And then, in our way of thinking, just to simplify our experiment, we say, okay, we have a certain rhythm for assembling in the production line. So are we using the right rhythm? And, of course, we can push the workforce to work faster, and they were going to produce more. But then potentially, at the end of the production line, when we go to quality assurance, we will need to rework a lot of things. So for us, it was, okay, what is the right stress level? Because stress is not a bad thing. Like, when you study stress, you have a calm zone; you have a eustress zone, which is the good stress, and then you have the distress stress zone, which is the really bad one. And we want to be able to monitor it to say what is the right stress level. If you're too calm, then you get distracted, and the probability of prompting an error in your assembly goes up. If I push you too much, you're too much stressed and you're working too fast. That's the same situation. It prompts the probability to go up. So if I can find what is the average healthy stress level that just gives the sharpness that we need to the workers, then the probability of errors will go down, and then quality will improve. So there's a positive relation that we can find, what we call digitalizing occupational health safety and productivity of the workforce thanks to these wearable trackers. And this is just like a simple experiment, a simple example of how we can use healthy measures not just to care about the worker but also that these are not in opposition to make a more productive production line. TROND: And I guess that's the key, whether you're measuring individual worker health or you're measuring the environment around the worker or the environment around the factories. It just depends on having the right types of sensors. But the bottom line seems to be that once you start measuring these things, whatever you measure starts to affect the work process, so you have to be sure that you're measuring the right thing. Well, it's interesting. It seems to me that there's this balance and trade-off always between advanced and simple. And when you're engaged in doing industrial work, the mere activity of work is so complex that adding technology tools that make it overly complex is obviously a big challenge. Thank you for outlining some of these things. And I hope I can have you back, and we can talk when operator 5.0 has truly emerged across industry. I'd be interested to see what the workplace looks like then when it is fully resilient. Thank you so much, David. DAVID: No, thank you very much for the opportunity to share with your audience, and it was really nice talking to you. TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was Operator 4.0, and our guest was David Romero, Professor of Advanced Manufacturing at Tecnológico de Monterrey University in Mexico. In this conversation, we talked about the emergence of the 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. My takeaway is that 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. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. And if you liked this episode, you might also like Episode 104: A Scandinavian Perspective on Industrial Operator Independence with Johan Stahre. Hopefully, you'll find something awesome in this or in other episodes, and if so, do let us know by messaging us. We would love to share your thoughts with other listeners. The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, devices, and systems used in a production or logistics process in a physical location. Tulip is democratizing technology by empowering those closest to operations to solve problems. Tulip is also hiring, and you can find Tulip at tulip.co. Please share this show with colleagues who care about where industry and especially where industrial tech is heading. 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