Smart Manufacturing and the Supply Chain

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Episode 763 03.22.22

Thorsten Wuest, associate professor, West Virginia University, joins Peggy to talk about smart manufacturing and the supply chain. He addresses three key things that smart manufacturing brings to the table that have a supply chain implication, how to invest in the younger generation, and how to invest in smart manufacturing.

Below is an excerpt from the interview. To listen to the conversation from the Peggy Smedley Show, click here or go to https://peggysmedleyshow.com/ to access the entire show.

Peggy Smedley: Well, I’m delighted to have you, because smart manufacturing is so important today, and it’s such a great conversation that I’m delighted that we’re going to spend some time together. And I think it’s really important to talk about smart manufacturing, especially as it relates to the supply chain, and putting the two together, I’d love for you to start our conversation perhaps in that direction.

Thor Wuest: Alright. No, I couldn’t agree more as you know, I guess, smart manufacturing is really at the core of supply chain or digital supply networks as we tend to refer to it. When you think of how we perceive supply chain in the recent, well, two years, three years I guess, the COVID pandemic really brought to light all the little bits and pieces that might not have been perfectly aligned for such a black swan event, but that’s not really the caveat that caused all that. It was there before, and smart manufacturing, I’m a strong believer in that, is a mechanism that can help us overcome that in the future.

Smedley: Do you think when you say can help us overcome it, is it because we’re going to see a lot of the data that we need to see much more information? Do you think that it’s going to displace the way we did old things with new things? What’s going to be revealed by this? Is it technology? What’s your overall thought that it’s really going to help us here? Because I think, in my mind we’ve had this evolution of Industry 1.0, 2.0, 3.0, now we’re at 4.0. It’s this whole evolution, I think, when you think about smart manufacturing. And in my mind, when we think about the supply chain, we’ve learned so much, as you said, from COVID and the black swan event, I think that’s a great way of illuminating in our mind what it really was, but there’s so much, I think most people don’t understand, but those of us in the industry really do. I know I’m throwing a lot at you, but can you peel back the onion a little bit for me?

Wuest: Absolutely. And I think, yes, smart manufacturing is so broad that it pertains to so many different things on the shop floor and beyond. And I think three things are key, what smart manufacturing brings to the table that have a supply chain implication, in my opinion. One of course is the data that you mentioned, like the transparency that we can predict. The port of LA has a traffic jam, so to speak, how can we get our parts to the assembly line on time? Can you predict that better? Can we say, instead of getting notified tomorrow you won’t get your part, three months from now, there will be a better event. We might be delayed, maybe sourced differently. So, the data transparency technically is already there, but now we are dealing with the business issue. We’re talking about competitors that work together and have to share data, that data sharing data in different formats, across different systems. A lot of challenges still to overcome to really do that. And a lot of it is, well, political, not in a legislative sense, but in a company strategy sense.

The second way, and I think that is really impactful, and we see that already in Europe, in the U.S., and in Japan, high wage countries have no choice. When they want to have production in the country within their own nation, we have to be competitive, and smart manufacturing is a way to leverage highly skilled labor and still be competitive on a global scale. So, in order to have production close to where the consumption happens, smart manufacturing or Industry 4.0, however you want to refer to it, is not optional. It’s a necessity, otherwise we cannot compete.

And the last piece, I already mentioned labor. We are facing a skills shortage already, not that many people want to work in manufacturing. And the lot, in my opinion, has to do with the perception of manufacturing as dark, dirty, dangerous, and so on that is still portrayed in movies, always the welder in a dirty shop. That’s not how manufacturing happens anymore, and it will not happen like that in the future. It’s a high-tech workplace that is exciting, that is innovative, that you can play with the newest toys like AR (augmented reality), VR (virtual reality), you name it. And that should help us attract the digital natives.

Smedley: So now that leads to an interesting point, because I want to get to the human and the operator side of this, because I think you talk about AR, VR, the floor, and everything, but then we look at Europe because, again, you really did peel back the onion and talk about the three key points. We’re advancing beyond 4.0, and Europe is talking about 5.0, and I’m not even sure I understand what that means, which I want you to explain that, because we still have this idea of explaining here in the States, why manufacturing is not dirty, and you talked about that too.

So, let’s start with what’s happening in Europe. And then let’s come back to why we have to educate the next generation about why it’s so important we need manufacturing. So, it feels like we have this ying yang thing going on that we have to get past in order to understand the value of manufacturing. I think that’s what we’re struggling with. We don’t understand why we need manufacturing, and that’s our biggest problem. The skilled labor shortage problem, you and I both know we’ve had for years; this is nothing new, and this is a problem we had. But now it’s a bigger problem, because you said this collaborative effort, we need with competitors is revealing everything. Now we’re going to have to look at blockchain among competitors and sharing information. So now we’re going to have to look at technology, but we’re also going to have work together. So, this 5.0 thing is really appealing to me, yet very intriguing.

Wuest: Yeah. I have, well, a more hate than love relationship. If that’s true, to be honest.

Smedley: I love hearing this. Go on, you’re going to have to explain this to me, because this is very interesting.

Wuest: Well, I think when we look at the Industry of 1.0, 3.0 and so on, the first revolution was a real revolution, with burning down a factory, sending the military, a real revolution. The second one was a little bit more smooth with automation and the moving assembly line. And then the third was sneaking in computers on shop floor. And for a long time, I refer to what is now called Industry 4.0 as a 3.8, because I was not fully convinced that it’s a real revolution. It’s part of a revolutionary step.

Smedley: Agreed.

Wuest: And now this Industry 5.0, just when I gave my okay personally in my mind to say, okay, I can use 4.0, they start with a 5.0 and say the main difference is to put the human at the center. I fully disagree because I believe in Industry 4.0, the early definitions, always put the human ingenuity at the center and say, hey, it’s a cognitive automation. We enable the human to not do the repetitive strenuous, dangerous tasks, boring tasks, repetitive tasks, but enable them to problem solve to apply their human ingenuity within this digital workspace. So, in my mind Industry 4.0 is already centered around a human worker. So, Industry 5.0 introduces nothing new, but I think it has to do with the European Commission wanting to be on par with Japan, which introduced society 5.0. And it just sounds good. And politicians need every four years a new term, I guess.

Smedley: So then let’s think about that, because that’s an interesting point because at the same time, if they’re saying that, is it a way to transition people to think, look, because we called HMI, the human machine interface years ago, that’s not anything new, you and I both know that when we made the transition from M2M to IoT. We tried to get away from all of it. This is the transition when we talked about the machine and manufacturing and us at the shop floor, and you just said, we tried to get rid of those competitive tasks that were tedious, that we didn’t want us on the plant floor. We got all that. And I understand that.

So now when we look at this, in this human machine operator kind of thing, what’s the role then of the human operator then on the shop floor, or what are we trying to say? We don’t want those repetitive tasks. I got that. And now what we’re saying is, how do we transition that so that people and workers understand manufacturing, I use the word because that’s the way they want to describe it, is appealing or sexy, exciting, that the young worker wants to come to it. Is that why it’s 5.0? It’s inviting, we want to say it’s gaming. What’s the right word?

Wuest: I don’t know why it’s 5.0, I think 4.0 is appealing enough. I see that just as my students, when we talk about that in class, it’s like their eyes open and they’re interested. You see a change in behavior in how they listen and how they’re excited about how they can wear AR glasses and talk to somebody, the facility across the country or another continent to help them fix the machine. I think the big transition that I see is that, you’re right, we had HMIs, we had PLCs (programmable logic controller) and MES (manufacturing execution system) systems on the shop floor for a while now, which really helped, of course. But now I think the role of the human will transition further.

They don’t have to look at control charts all day and analyze them. They get the insights from 10,000 control charts over time, controlled for different parameters, and can make a decision, wait, maybe we should change the whole process. Maybe we have to rethink the design of the part and how that impacts our quality, beyond just the repetitive task that says, oh, we have to find the quality issue in our process. We can think we have a quality issue, maybe a very small one, but we can still make it better. How do we do that? And AI (artificial intelligence), and these new data insights can give us this edge to really improve beyond what is possible today. And I find that extremely appealing. It’s like being a detective on the shop floor.

Smedley: And that’s a very interesting and exciting point. So, are we combining both the physical and the cognitive? Are we making it immersive, so that now that idea, that detective you just described is saying, look, you can be innovative in ways that the imagination can create new solutions to global problems? Is that what the manufacturing world of today can be?

Wuest: Maybe of tomorrow, but very close tomorrow.

Smedley: But why does it have to be tomorrow? Why can’t we excite, I didn’t mean to interrupt, but let me ask you, why does it have to be tomorrow, because the students of today that you’re working with, to get them excited about innovation, that we need to have them creating and manufacturing, because we have a worker shortage. If we want them to leap into understanding what they can do, that they can change the world today, why do we have to let them think it has to be tomorrow and not today?

Wuest: Okay. I think I misunderstood. I thought like, can we go to the shop floor and do that today? And I would say in most shop floors we can’t, because the infrastructure is not there yet. You can buy it, you can install it, you can make it happen. And in some factories, you see that. But I think this transition of enabling all the cyber-physical systems that provide all the insights and the capability to the human workers, here’s still some ways to go to install that.

But yes, I agree. On the motivational level and the transformational level that students nowadays can engage into, we are there, because the technology’s there and the current workforce often is not that, how do you say that, does not understand the capabilities as much as recent grads that had a chance to work on a project in a lab or in an internship, they often get the opportunity to run a project on working with a cobot, trying to automate a system where a robot works with the worker closely together because they’re digitally capable. They’re motivated. They have the skillset. And of course, they’re new. So, they have already heard that in class, these new principles, they understand what OPC UA (unified architecture) is. They have a working knowledge in Python, which really helps them in that environment beyond being able to machine a part.

Smedley: So, you actually understand the same point I’m making, that in all of this, the problem then isn’t that students aren’t interested, or the younger generation’s not, it has to be a greater investment then in manufacturing and enabling the infrastructure. That’s what I’m seeing then, because you have students and the next generation that says I’m interested, but there has to be even a greater investment I think in the manufacturing world and faster than they’re doing. And I know it’s very expensive to change machines side by side, but if we want, and we can’t keep saying there’s a worker shortage. Part of the challenge is the investment has to be faster and move just as technology’s moving faster, manufacturing has to move faster it seems like, because what’s happening is they’re going to other industries. If manufacturing wants to get to them, they’ve got to move faster, quicker, and see the changes that are happening, otherwise it’s that same perception of manufacturing being dark and dirty.

Wuest: Oh yeah. No, I can’t argue with any of that. I fully agree. Let me give you an example. I visited a facility not too long ago, a foraging facility, and they had their own workshop to make their own dyes with a milling machine. And it was an analog, like not a CNC (computer numerical control)-enabled milling machine. And it took them three weeks to make a dye. Now they ordered a new five axis CNC. And it’s predicted to make a dye in three hours. That is a big difference. And that investment, the ROI of that investment will be there in no time. But the ROI, I think is a dual-sided sword, because I feel in the U.S. a lot of the manufacturers are either cash strapped to not be able to make such a large investment or have a shorter horizon when they expect the ROI to be achieved.

And some of this equipment, you mentioned it’s really expensive. And when you have legacy equipment that still works, a lot of smaller companies need help to upgrade that. And there’s a lot of interesting initiatives out there that you take 30-year-old equipment with an outdated PLC, put a small single-board computer to it and enable it to collect data, stream the data connected to the cyber-physical system overall. And that is a very important step. Of course, in an ideal world, we would upgrade everything to the newest house or whatever system that has all that built in, but that’s unrealistic for a lot of the companies. And not necessary, because this capability improvement with just having access to the machine and the codes and the data that stream from it is already enabling so much opportunity. And once they have that, the investment, normally doesn’t stop because they see the value in it. So, it’s like feeding them a little bit and then they understand and are willing to invest more.

Smedley: So, what you’ve just said, we’ve all learned since COVID that manufacturers who were reluctant to make investments had to. They’re reluctant if they were to make investments in AI or ML (machine learning) systems due to the high costs, are seeing that they have to, and this is now, and it is happening. And if they don’t, they’re going to be behind. That’s what I’m hearing you say that COVID has said, it’s made everything exponentially change in our marketplace and manufacturing and now moreover tools and everything, is that because we’re seeing the data that comes out of it, we’re seeing the results, and they’re user friendly, everything’s happening. Is that what you’re telling me?

Wuest: Yeah. I think COVID accelerated all that tremendously, companies that had travel restrictions couldn’t send a rep or maintenance worker to the facility, so they had to do it remotely. And to do that remotely, when it’s technology-enabled with AR or another, like a connected machine where they can access it from their computer at home, made it possible to keep production running, so to speak. So, it really divided between the haves and have nots, and the have nots realized that they need to have it in the future.

Smedley: So, we’re talking about operational technology now for smart manufacturing. So, we’re seeing that you have to make these investments, one, to survive, two, to get the best talent, the worker of the future that’s today. So, if you don’t invest in it, you don’t invest in this technology and the infrastructure. So, what’s the role right now that these manufacturers, because now they also have to have greater collaboration even with their competitors, that we always worked within the silo of four walls. So manufacturing is changing so fast it has to be making small, medium, and large manufacturers make their head spin. These executives probably don’t even know how to compete because this is unlike anything they ever imagined in the less than two years.

Wuest: Yeah. And I think you said survive, I would say, survive and thrive. I think it’s a very thin line between the two. And when we think of the division that you made, just with small, medium, and large. The large companies are already there. They know they have to do it. And if they don’t, it’s a rational decision. For a lot of smaller companies, unfortunately, it’s more like they don’t really know what it would help them with. And then they don’t have a dedicated IT department, they don’t have a dedicated innovation task force, because they don’t have that additional overhead. So, they really need our help. And I think the federal government does a really great job with NEP and so on that helps to reach out and helps them to inform, to educate what they could do within their smaller facility. Because not everything makes sense. We cannot say, oh, you need to buy all the technology and get up to standard and invest billions of dollars.

And that might not make sense, but it might make sense to enable them to digitally communicate with their supply chain, to send invoices automatically instead of calling. Because that would enable them to enter more markets, because some of the larger companies, Walmart and so on, they require their suppliers to digitally communicate. And when they’re not capable they’re out of that market. So, there are small aspects of this digital transformation that really makes sense for every company. And it might be individual decision in what industry, and what area, what supply chain you’re involved in. Which one it is. So, understanding what are the different pockets of technology, different pockets of innovation for your particular situation, I think it’s a crucial task where a lot of companies need help.

Smedley: Looking at this right now. It’s exciting to hear that we’re seeing the transformation occur within companies. What advice would you give manufacturers? It seems like the large manufacturers are the ones that somewhat are ahead of the game. They already know what they have to do, and they can. But the small and medium size ones are the ones that are still in some ways, not understanding they’ve got a lot more that they have to do. And the large ones need the small to medium size. I always say that, because we all have to work together. But I think they have a responsibility to make sure the small and medium manufacturers succeed, because it’s a collaborative world, I think, globally.

So, what advice would you give everyone to work together, because if we don’t all work together, we all fail. I really believe in a sustainable, resilient, circular world, which we have to be. Is there some advice that you would give these manufacturers to say, look, this is how you should be trying to get your larger manufacturers to work, collaboration, encourage them to help you make advanced machinery to get to a smart manufacturing world that you need to be. Are there some tips, some things, what’s your thoughts?

Wuest: Yeah. No, that is an excellent question. And I just want to mention that we are currently in a project that’s sponsored by NIST], where there’s some OEMs (original -equipment manufacturers) involved. And the goal of that project is to enable the smaller companies to enter the supply chain, because you’re right, big companies have an interest to broaden their supply base, and they need help. So, there are projects underway that are sponsored by the federal government, which is excellent and the right way to do that.

But three points that I think are key, when we talk about these technologies, people are in love with technologies, engineers love technologies. I love technology. But we often get a little blind on the process side. So, we say, oh, we want to use AR, where can we use AR? That’s the wrong approach. We have to look at, what is our process now? Where does our process need to go? Is our process efficient? Is it the right process? How will technology impact our process and make it better, create more value, and then make this decision together, process and technology in a holistic sense. And that is done wrongly often with these, what is it called, pilot purgatory, that they say, oh, we have a cobot, the CEO can shake the robot’s hand and have a nice picture in the marketing, for sure. But after the project ends, it’s not really implemented on the shop floor because it’s not really aligned with the necessity of the process. And that needs to be carefully assessed at the beginning, otherwise it’s very expensive.

And then, education on both sides, for small and medium size companies, it’s, I think, essential to start projects even so they might not really yield full results yet, and they might fail. But in the process, your workers, your workforce gets experience, very valuable experience and gets thinking, how can technology help us improve our daily jobs? How can they improve our process? So, it’s an investment and education project at the same time. And on the larger partners, they might reach out to the smaller companies and help them with adaption. Porsche has Porsche consulting for a reason. They can send them to their suppliers to help them get more efficient. It helps the whole supply chain.

And the last point is a very simple one, get started. Don’t push it off and say like, maybe next year. No, do it now. And if it’s a small project, they don’t have to cost much. Buy a few Singapore computers, download pricing, it’s free, and give some folks a few hours a week to install a sensor on your machine tool, just to get used to it, just to see what can be done. And I’m willing to bet on that that will thrive, and innovation will come from it.

Smedley: It’s really interesting, Thor, that you talk about that a lot of, or I shouldn’t say a lot, that companies get lost in project purgatory, because I think that’s something that’s happened for a very long time, especially when we think about the Internet of Things and big data, because we get lost in the data side. Are we getting better at understanding how to take a step back and not get lost in some of that now? Are we getting better than what we did before?

Wuest: I believe so, because now that people know what a pilot purgatory is, I think that is the first step that they try to think of that and how to overcome that. And there’s also efforts to understand the problems behind it, like some of the projects, they had a project fund to fund the project. And once it ran, there was no maintenance funding associated with it. But when you have an AI project, you have to make sure that your models are still accurate when you change anything in the production. And now there’s interesting work being done on model transfer and how you can replicate that gradual transfer in your production, in the model itself so the maintenance can be automated to some extent. Which should make it much more robust in the future. So, we are not 100% there yet, but efforts are on the way, and companies are more aware. So, I think we are on the better end of it.

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