Plug and Play Industrial Automation? It's Only a Matter of Time

In this episode of the OnTrack Podcast, we are pleased to host a thought-provoking conversation between Tech Consultant Zach Peterson and Dr. Philip Voglewede, Professor and Associate Chair of the Department of Mechanical Engineering at Marquette University and Director at the Omron Advanced Automation Lab.

Zach and Phil have a very intriguing conversation about the role of automation in the current and future industrial landscape. Anyone interested in the current state of industrial automation, manufacturing, or labor trends won't want to miss Phil's insights, many of which are rooted in his work for the ground-breaking Omron Lab.

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Show Highlights:

• Intro
• Phil & Omron Advanced Automation Lab
• Pushing to Fail
• A Space to Play
• Omron's Early Achievements
• De-Siloing & Student Response
• Companies Noticing Student Skills
• Students Handling Complex Problems
• Grappling with the Role of Automation
• Where Do We Get ROI?
• Management is Adapting
• The TOTAL Dollar Amount of Manufacturing Costs
• Industrial IoT is the Achilles Heel
• Plug & Play is the Goal
• Make It Like Starbucks
• Who Will Lead the Needed Standardization?
• Will the Big Manufacturers Cooperate to Standardize?
• Standardization is Only a Matter of Time

Links and Resources:

• Read related blogs:

  • A Day in the Life of the PCB Manufacturing Process

  • PCB Manufacturing Reshoring, Automation, and Sustainability with Alun Morgan

  • Data-Driven Smart Manufacturing

  • Connect with Dr. Philip Voglewede on LinkedIn

Transcript:

Phil Voglewede:

Who's going to take the lead? Maybe software, but we need to be able to say, "Hey, we're going to have to give something up. There's going to be a trade-off." I can't say that, "Hey, I got to use that, this is the only way that you're going to interact with this machine." Because then all of a sudden you have all these translators and things that have to make it all work together. I want it to be like Starbucks. I just bring in my laptop. I don't care who made it, it just works.

Zach Peterson:

Hello everyone and welcome to the Altium OnTrack Podcast. I'm your host, Zach Peterson. Today, we're talking with Phil Voglewede, professor and associate chair of the Department of Mechanical Engineering at Marquette University, he is also director of the Omron Advanced Automation Lab. The trend with onshoring recently has of course driven this side conversation around automation, and so I thought it would be great to talk with Phil today about this important topic. Phil, thank you so much for joining us.

Phil Voglewede:

Thank you for having me.

Zach Peterson:

So the Omron Advanced Automation Lab, you're the director of this lab, and I thought it would be great if you could, to start, just introduce yourself and how you came into this position to work with Omron to develop this lab.

Phil Voglewede:

Yeah. So it's been a great mutual beneficial relationship. We approached Omron from Marquette about some donations, and then they came back and asked for a bigger kind of ask, if you will, and it developed into a $1 million gift from Omron to establish this advanced automation laboratory. What we pitched, which was different than the other labs that they've done at other institutions is this was going to be a lab of failure rather than a showcase of perfection. So what we try to do in the lab is try to fail and try to understand why it's so hard to do automation and why it's so hard to put these things together in a very coherent and systematic way and what causes those kind of issues.

Zach Peterson:

When you say our goal is to fail, to me, I interpret that as we're pushing the envelope as far as we can to the point where our existing capabilities eventually give out and we can then try to further our capabilities by examining what went wrong. Is that an okay interpretation?

Phil Voglewede:

Yeah, I think that's part of it. I think part it is to do that is to push the envelope of what we can do and try to do that. So we remain very flexible in the lab. Things are on drop down so you can move the equipment, the wiring is readily available and it's not everything is set in stone from that standpoint. But we've also noticed is some of those fundamental things of failure of just how to start are just as difficult, not only pushing the envelope, but also just where do you start? How do you just bring something in and get it to go when you don't know where to begin? Those are the kind of figures that we're seeing that a lot of people are having in the industry. They just don't know where to begin. It's so overwhelming to do these things. So understanding just how you can fail, just where to begin is just as important as pushing the envelope on the end.

Zach Peterson:

That's really interesting because usually when a company attaches their name to a lab, whether it's at a university or a corporate lab, they probably have some end goal in mind that they're trying to reach, which means at some point they got started or they developed an idea or a concept so they at least know the direction they want to go. And it sounds like companies like Omron probably aren't even at that stage, they don't even know where they need to go next.

Phil Voglewede:

Well, I think Omron knows, but the question is, do the companies that Omron is trying to sell to know? And so, that's what I think really excited them about the lab was they understand that a lot of the people they're trying to sell to get nervous, they don't know where to begin, they don't know what they don't know yet, and how much is that going to cost and what that going to be. And so, they were very open to the idea of given this neutral space, a playground, a sandbox of where companies could come in and ask the stupid questions. And that's what excites them is they want to educate, they want their equipment to be used more effectively and in the right way.

And so, from their standpoint, they know some of these things, but they also fall into that trap too. Their showcases all wired up, everything is beautiful so people can come in and see the end failures, how far this can go and stuff like that, but they wanted the space to be more adaptable to, hey, what happens when you come in and there's nothing there, or the wires are still not connected? How do you address those kind of failures?

Zach Peterson:

That's really interesting. Is this the first instance or one of the first instances where a company has created I guess you could call it a safe space to play around and fail with something? It just goes back to my earlier question about companies usually have a goal that they want to hit and instead of what you guys-

Phil Voglewede:

Yeah. Omron has done several of these labs at different places, and I think their goal is to obviously sell more of their equipment, but it's also to use automation and it fits their vision, a bettering of society through automation, empowering people and the like. And that's all part of their goal. And they saw it in these other labs that they became just what they already had. And so, I think this is new for them because they were like, "Well, we could build another lab that does everything that the other labs do, or we could go in a different route, and take a risk." There wasn't a lot of risk of this because they have those other places. And so, they were really looking for a place to do this in a new way.

And to my knowledge, it's the only place that exists like this. Most academic labs are consortiums and it's where to push the envelope, so all those things at the end, the failures at the end are really where they're looking to go because that's most times academic environment. But I think what we're trying to do is do it differently and see if that works and see if we can get the people at the beginning so that way they can go to the end here or go other places, go to another facility that has this equipment and say, "Oh, that's why they did it that way and that's why it's set up this way." But because of that, now they have these other issues that they have to address and these are the limits that they're fighting because of the things that they had to decide early on that they may have done incorrectly or because that's the only way they'd known to do it.

Zach Peterson:

So, what are some of the big achievements so far, or maybe what are some of the big things that you're hoping to achieve?

Phil Voglewede:

Yeah. Yeah. Well, so far we're early, we're just finishing up year one of the gift. So we have a robotic cell that we've created, and one of the things that we wanted to really do was expand this into other areas other than just traditional engineering and let's bring in computer science, let's bring in business. So, one of the big achievements we've had so far is we've partnered with the ops' management class here at Marquette and brought their students in because they're the ones that are going to have to deal with this automation, and how do you get parts to there, and how do you get the finished product out, and how do you deal with the flow of the parts from this different automation, and what decisions were made with the automation to do that. So we brought them over and we're still developing the cell.

So what we told them is, "Well, help us program it." So I was teaching business majors how to program robots and how to do this, and it's a wonderful experience. Now, granted there is some handholding there, and we've gotten through some growing pains of that, we failed on how to teach these next generation of ops management or supply chain on how to deal with automation, what automation is. They came in and they were arms folded and they didn't want to touch the robot because they're told that robots can hurt them. And that's true, but we have cobots in here, which allows us to really start to break down those barriers that business people can understand what's going on here. Not all the things, they don't understand the fundamentals of feedback control, but they do understand that when you put it in torque control free mode, that it moves with them and it responds to them, but there's a lag. And they also understand that teaching something and having it go to the same spot is really great, but the problem is you can't get the part at the same spot all the time.

So, that talks about fixturing, and how you present parts, and how do you use vision to be able to account for that. So these are all these great learnings. And so, that in year one has been a great achievement that we had, I'm trying to think, 30 to 40 students come over and work in the lab and take that learnings out there and be able to better specify and understand how to deal with automation from a business aspect. In the meantime, we're also doing it with our engineers, from freshmen engineers to senior engineers down to the nitty-gritties of feedback control to how do you do torque control and what does it mean when you change certain gains to, hey, just how do you interact with this as an engineer when you don't have a lot of the information as a freshman. To companies, and we've brought in one company and taught them on, they were looking and saying, "We've heard about cobots, but how do these work? Where do you start?"

So they brought in mock-up of their press die and said, "Okay, can you present the parts into this die correctly?" So we worked with them and started to look. And then they really quickly understood what are the limitations at the beginning and also with limitations at the end, how fast can it do it, and if we use vision to be able to do it versus fixturing and stuff like that. So, we started to really expand the workforce that work with automation. And so, that in year one has been a great achievement and we hope to go even further in years two, three, four, and five.

Zach Peterson:

So this is really interesting because it's the de-siloing that is so important, especially I think in knowledge and skill heavy fields like this in order to get all of those people in the room. And you mentioned you've got the business people, which extremely important in an academic environment, but then you've also got the computer scientists, probably folks who are doing software and firmware. And then I'm going to assume you've also got the electronics engineers in there who are actually putting these systems together and deciding this is how we're going to engineer a piece of equipment in order to accomplish this goal that we think is going to be relevant to somebody out there.

So, that de-siloing, I'm going to assume tracks a lot of different students. What's the response like from students? Is this inspiring students to really pursue a career in manufacturing? Because when I was younger, manufacturing was not something that you were generally encouraged to go work in. And now doing PCB design, I get to help companies with manufacturing, and I talk to manufacturers now and it's extremely interesting to me. But when I was younger, I was really surprised because manufacturing was not seen as a career you would aspire to as a young person back in the early 2000s.

Phil Voglewede:

Yeah. Now, I don't have any data. I mean, we're still early on, but I think so far it has been tremendous. I have people knocking on the door, literally knocking on the door to come in and work in the lab. They see what's going on in there that they want to be part of it. I understand that I'm maybe not the most approachable being a professor and stuff like that, I have students working in there and when tours come by, the students are inviting the other potential students coming in or the parents, and they all get excited about this because it's like I finally can touch and interact with these things where I wasn't able to do that before where usually behind glass, where behind safety, that whatever you see is just a demonstration of what the end result is. And this lab is never that way, it's always influx, we always got things that we're wiring up, we're always trying to add this thing, we're always going to change this thing.

We've started to add holy plates on to present things to the robots so that way people can say, "Wait a second, what if I rapid prototype some kind of fixture to solve that problem?" "Great. Here, you put it in our grid, wherever you want to put it, where's the best place you want to put it?" And so then it gets them excited because they feel like, "I can do this. I can contribute no matter if I'm a freshman or a senior or a computer scientist or a business person." Manufacturing is changing, it's no longer just everyone sitting in a line shooting a screw, it's now this connection of everything together, that systems thing, which really excites people because then they can start to say, "How do I make these things work together?"

And that's that de-siloing that you're talking about. So I think that's exactly what this lab is doing, and I think that's a side benefit that Omron didn't understand that they were like, "Hey, let's take a chance on this failure lab and see where it goes. And all of a sudden it starts to say, allows the people that are afraid to come in because it's okay. It's okay to fail and it's okay to be not knowing. And so, we purposely not get the people that are specifically designed to know that working on that aspect. So maybe the computer scientist isn't setting the IP addresses of all the robots, and maybe the mechanical engineer is doing the programming to get that cross-functional because they know nothing and they know that's okay, and that's what we're supposed to learn, and then we can learn from each other and then do that.

And then as that, once you get that, like you said, the excitement comes through, the students just like, "Wow, this is different than what I anticipated manufacturing was." And then we start applying that in different places, whether it may be forging or assembly or machine, which was now what was considered, "Oh, we don't want to do that because that's not going to use your technical knowledge." It will right. Now, how do you put those things together and also work with the operators to be able to do that to make their lives easier? So, I think you're absolutely right. I think it's de-siloing, and that de-siloing, it allows people to become excited about manufacturing and what it can do. And especially in Milwaukee where we are so manufacturing dense, it's such a wonderful, wonderful place to do it.

Zach Peterson:

Yeah. That brings up another question. Usually when these types of experiments pop-up in universities, you start getting companies coming around poaching for students who are soon to graduate. Have you seen that yet?

Phil Voglewede:

Oh, yeah. Yeah. They see who's working in the lab, they see the people that are doing that. I also combine it with another one of the classes I teach. The companies realize that the people that come through the lab, that people that see this stuff that are not afraid to fail and then can talk about that, that's what the companies want. They want to say, "Yeah, we want you to come in, and we realize that." So yeah, they're absolutely just dying for those people. And they're like, "Let us come into the lab to see the people that are there. We want to recruit them, we want them in our facility, we want them at our company because they have the right attitude and they see maybe the light of what automation can do." And they're excited about it and they want to do that at the...

Zach Peterson:

So when students have the opportunity to approach these complex problems, devise a unique potential solution, whether it's electrical, mechanical, or if they're a computer scientist algorithmically, I would imagine it gives them a little more credibility when they start to go out and look for a job because now they can speak to how they approach a complex problem and what failed, what worked, and how would they do it differently.

Phil Voglewede:

Yeah. Yeah. And I've integrated that into my class that I run in the lab, and I have two lab experiences where it's very open-ended and I tell them, "Go measure something on one, and the other one go control something." And the students love it because they use these things when they... I also tell them that they have to fail, that they have to fail in what they did, and I wanted to do this, I couldn't do this because. And that's that because that is very beneficial because that's what the companies are looking for. I can't do this because, but I know why.

And then if I had this or I had more money, or if I had more resources to be able to do this, I can tell you exactly what I can achieve with this different dollar amount rather than just specifying something that's completely over specified. Companies love that and students love talking about that because they can say, "Hey, in typical interviews, give me an example of where you had to face adversity or you had to face failure and what did you do about it?" And they can go straight to the class and say, "Yeah, I was required to fail and I was required to find this adversity. And because of that, now I feel better and I feel more comfortable in that space."

Zach Peterson:

So given that there is a nearshoring, onshoring trend and that more jobs are moving back to the US specifically in the manufacturing sector, I think it brings up the question about the role of automation. And I see your lab is really being directly involved in exploring what that role is going to be as well as preparing a group of students to really be proficient in it as well as be innovators in it. So with that in mind, automation is sometimes cited as one of the only ways to make American manufacturing cost competitive with other parts of the world where we have seen supply chain issues arise, and then of course there's the geopolitical tensions and things like that. So, do you buy into that that you have to have some level of increased automation, or is there a different narrative we should be pushing when we talk about bringing manufacturing into the US, into the Europe, really into the end markets where those products are going to be sold?

Phil Voglewede:

Yeah. Yeah. I mean, it gets to the crux of the matter of automation. There's this fear of the whole elimination of jobs and that sort of thing. Part of the automation equation is, yeah, it's going to be most likely cost competitive to do that, but there's times where automation is not the solution and maybe there's some other, if you're familiar with the different Industry 4.0, different revolutions, maybe you need an Industry 2.0 kind of technique. Maybe that's the one that you need and maybe that will help you do that. There's still a lot to be done that automation doesn't solve everything. It's not the panacea and just to reshore everything and say, "We need automation and that's the only way we're going to survive," I don't think it's right, I think it's having the right mentality. And if you look at the lean manufacturing of understanding the root cause of the problems and really driving efficiency, that can be done with automation, but it doesn't have to be, you got to have automation with the right attitude.

And sometimes automation works and sometimes it doesn't. So, I think you're right that that automation is part of the reshoring equation, but it's not the only thing that we got to have the right attitude. And that actually also what I'm trying to get in the lab as well, and that's part of the business aspect when I started to say, "Well, wait a second, do you have to have these robots here? Could we get this efficiency if we just place things together? Could we get this efficiency if we just started talking about pole manufacturing rather than push manufacturing and one part flow? And could you get that without automation? Because automation may dictate that, but could you get that without it and still be competitive?" And the answer, may be yes, depending upon your product mix and all the different things that you have going on, that has to be part of the equation. So I think you're right. I think this is something that we have to grapple with and this lab is a great place to do that.

Zach Peterson:

Yeah, lab, it's really important place to do that, but I like that you bring in the business side of it as well, because things like reshoring, onshoring, building a new facility, a more advanced facility, it all takes capital. And at some point, the people who are investing in it, they want to see a positive ROI. I know that there are subsidies out there right now, but that's not going to last forever and that's not sustainable. So at some point, there has to be positive ROI, and when you start to look at automation, that also requires some level of investment, and that could be wholly separate from just the building of a facility. So, it sounds to me like you would advocate taking a look at it from that standpoint as well in order to see not just where do we get monetary ROI, but where do we get efficiency throughput, any of these other metrics, quality ROI.

Phil Voglewede:

Yeah, absolutely. You got to look at it from the system standpoint, and that's what we're going for is a holistic view and a holistic look at the entire process, you are only going to be successful if you do that. So what you talk about is a lot of the things that we did with robotics in the 1980s where we automated everything and we weren't there yet. We weren't there yet, there was a lot of different things that were causing the issue, and we just thought, "Oh, if we just put that in there, it'll solve our problems, and it didn't.

In the '80s, we overpromised and under-delivered, and we need to now look at this differently and start to say, "Where does it make sense to do this?" And it may make sense to go all in and try to automate everything, or it may be say, "Wait a second, maybe we need a cobot here to just automate some aspect of this and then use this in a more flexible kind of way, and use that as an entry, and be able to say that this is little bits by little bits and get ROI little by little." And then looking at the overall mentality of how you do your entire process, and the efficiency may be in some other place, and it may not be totally in automation.

Zach Peterson:

I think it's interesting that you bring up the case of the 1980s because it wasn't too long after that that you started to see a lot of offshoring. And I wonder how much of that was a failure of the '80s. And of course we have the quarter to quarter thinking that a lot of companies thinking and they say, "Well, we didn't see the ROI we expected now, so we're just going to throw up our hands and go overseas."

Phil Voglewede:

In my opinion, yeah. Now granted I have no data to back this up, but I think that's a lot of it. I am a big proponent of Deming and all his thought. I think really it was a management mismanagement issue that, "Hey, we didn't know what to do. Management didn't know what to do. We went all in on robotics and then management got nervous and they didn't see the ROI at the immediate thing, and they still needed to do, and there was this carrot out there of offshoring and being able to do that and that would solve your problems really quickly." And that was management's kind of, in my opinion, solution to it, just, "Well, okay, it didn't work and this other one is much easier, we can just do that and build a facility in some foreign country and be able to get it."

But I think that that's changing now with the supply chain and also our attitude. And I think management has learned, I think at least I hope so, that they've learned that there's no easy solution. When you go overseas, you got the whole transport thing and you had the whole supply chain and how to get these things going and you need to look at this holistically. And again, that's what we're trying to do.

Zach Peterson:

Yeah. I think in the past, it was so much easier to just boil it down to a dollar amount too, because globalization was just beginning and we weren't so exposed to a lot of the supply chain issues and the geopolitical tensions existed, but at least they didn't exist where people were setting up factories, so it was kind of an out of sight out of mind thing. When we were talking to Happy Holden on an earlier podcast episode, he provided some numbers for cost comparisons for building a plant, I think he said in Virginia versus building a plant in Taiwan, and it's like night and day. And if your only factor that affects your decision is the dollar amount, then of course all of that investment is going to chase the lowest dollar amount.

Phil Voglewede:

Yeah. But I think what you have to do is you haven't really accounted for the total dollar amount if you think about this. You think about the other things, the supply chain and those kind of things also have a monetary effect as well. Hey, if I have to fly parts in because of supply chain issues and I have to move them all across the globe to be able to make this thing happen, that costs money too. And I think it was a very narrow focus of what we are looking at as far as cost, and I think we really need a bigger picture of costs and we better understanding of what those costs are. Because you can put dollar amounts on those things just like you can with the total capital, but we were so focused on just what that capital cost was and not the operating cost, and the other things that go on into it, that it was a very narrow focus.

And again, I think that was management's nearsightedness and mismanagement from the '80s, which I hope we have learned from and we got a better idea. And obviously because of the pandemic, we actually got a lot of understanding of supply chain issues and what does that mean and what does it mean to be tied to one specific facility and one specific place and that sort of thing, and we had to have a better understanding of how to diversify this.

Zach Peterson:

Sure, that makes sense. Going back to the multidisciplinary nature of automation for just a moment, so you mentioned that you're bringing in computer science students, sounds like firmware, software developer folks who can come in and build some of the, maybe the code that's going to go directly onto these devices as well as maybe the management applications. So, this sounds a lot like industrial IoT to me. And you brought up Industry 4.0 or you mentioned the term earlier, and of course immediately my mind went to industrial IoT. We've been talking about industrial IoT for several years now. It wasn't too long after IoT became a common acronym that then industrial got added onto it. So given that we've been talking about it for so long, I don't know the level of advancement that that, I guess, paradigm has made into the manufacturing space. Can you comment on that?

Phil Voglewede:

Yeah. It's the Achilles' heel. I do a lot of consulting work, and how to get the things to talk together is always, always the issue. We've noticed that even in the lab of just getting one thing to talk to another. Because you look at these things with artificial intelligence and what you want to do with automation, it requires a lot of data and understanding and how that data flows and getting that all together. That's the backbone of the industrial IoT that we're talking about and how to connect those things. There's not an easy solution, at least not yet. And I think that is the thing that's really aggravating to me and in setting up the lab and also dealing with my companies I consult with is just how do you get things to talk together. And I think you start with the people, and getting people to talk together sometimes is difficult from an engineering standpoint, getting engineering to talk to the IT professionals and how you get them to understand what the priority is because IT professionals always are torn in so many different directions, and what is actually needed.

And I think then that's the end thing that you're talking about before, which is the limiting factor is the plug and play of these different things. You need an IT professional to come in to help you because if you try to do it yourself, it's not, "Hey, I want this machine to talk to this machine, let me plug them in together." It doesn't work that way. You need hubs and you need controllers and you need communications and what protocol are you on and what are the IP addresses and what is the subnet mass that you got.

And a lot of this is all important because of cybersecurity, but we got to figure it out, we got to find a way to be able to do that. Because we're not going to be able to do the automation that we want if we still have to wait two months to get an IT professional down there to set the IP addresses with the right mask to make sure that we're secure while the rest of the line just sits there and waits. We got to get faster at being able to do that, and that to me is the big issue that we're trying to solve.

Zach Peterson:

I think when someone hears plug and play in the context of IoT, not thinking of it at the level that you just brought up which was really the networking level, they're probably thinking about it more in terms of, "I have this off-the-shelf piece of equipment, I have another off-the-shelf piece of equipment, I'm going to run a cable between them and now they can talk to each other." And this sounds like that's an overly simplistic view of how production assets have to work together in order to reach a common goal or coordinate what they need to do on a manufacturing line.

Phil Voglewede:

It is. 20 years ago, you were dial up and you were doing all those kinds of things, that's where we're in manufacturing right now, we're in the dial-up age. And people see what you can do in Starbucks, I can take my laptop, it can be a Mac, it could be PC, it could be on Windows, it could be whatever, and it just works. That's what we need for automation. That's the goal. Are we there yet? No. Is it simplistic? Yes, but it's where we want to go and we got to set that out, that's the carrot. Because until we have that, people are not going to do that. Now we're getting closed, we have some cobots in my lab and those can stand alone. And the software that runs that, that's a Window-based software and it's drag and drop to program it, it's icon-based.

I don't need to understand Pascal or COBOL or FORTRAN or C or C++ or understand the different things with libraries or setting up data streams and stuff like that. I just know I want the gripper to open, I want it to move here. That's what we need, we need to get to that point. And we're getting close, but we got to be able to say, "Wait a second, maybe this device, this camera is better, or this sensor is better, and now I want to integrate that in," and I want to be able to say, "Go."

Zach Peterson:

I mean, this sounds like much more of a software challenge than it does a hardware challenge because at the hardware level, when you bring up communication protocols, I mean, we have those and they can be adapted for production assets. I'm sure even if something is legacy, you could find a way to incorporate those enhanced capabilities into a legacy piece of equipment. It's the interlinking and enforcing a common language across all those different platforms over a single protocol or maybe a small number of protocols. To me, that sounds like more of a software problem.

Phil Voglewede:

Yeah, but it has to do with the hardware. Why isn't hardware a lot?

Zach Peterson:

I agree. I mean-

Phil Voglewede:

I think the majority is software. I agree. I agree. But I want to look this as a system. I can't point fingers, I got to remember, I got to point it back to myself. I'm a mechanical engineer. I can't say, "Hey, it's a software issue." Because that's what's happened in the past. We keep saying that, "Oh, it's a software issue, it's an IT issue," and IT says, "It's a hardware issue," and hardware says, "Oh, it's the mechanical's portion issue." We just have all this finger pointing. We need to sit down and get together and say, "No, it's a systems problem."

And now, who's going to take the lead? Maybe software, but we need to be able to say, "Hey, we're going to have to give something up, there's going to be a trade-off." I can't say that, "Hey, I got to use that, this is the only way that you're going to interact with this machine." Because then all of a sudden you have all these translators and things that have to make it all work together. I want it to be like Starbucks, I just bring in my laptop. I don't care who made it, it just works, I'm on the internet.

Zach Peterson:

So, it sounds like there's some level of standardization that's needed in order to get to this level where you have hardware and software and networks that all play nice together and allow this seamless communication across production assets from multiple vendors.

Phil Voglewede:

Yeah. And that's what it's going to take. It's going to take someone to make the standard to make that work, and realizing there's going to be other kind of things that are going on, but we've done it before, we just need to do it again. And then unfortunately, I think there's a lot of automation manufacturers out there that are not willing to give that up just yet. Because if you can take somebody in and say, "Hey, if you buy our stuff, we know it'll work." And so then you're kind of stuck with that.

And that may work for large companies, but really get automation into places that it hasn't been before, we got to have to bend a little bit, that I'm not going to buy an entire system that it might be just part of automation and it might be some legacy environment and legacy stuff because I don't want to have to get rid of that stuff yet. It's working, it just needs to talk in a better way. So we're going to have to come up and we have to compromise, and we're going to have to standardize. And I don't know how that's going to happen, and who's going to lead that, and that's the hard part is because there's no central organization that when you're talking about things this big that can define that. And unfortunately, it's not a consumer thing, it's an industrial thing. So unless these, I think, industrial people get together and start to demand that, it's going to be hard to do.

Zach Peterson:

Do you see any potential for some of the biggest manufacturers getting together and just forming their own consortium and basically just throwing down the gauntlet and saying, "You know what? We've all decided it's in our best interest to work together, and to have these production assets that are actually able to communicate with each other." Not in the IoT pipe dream kind of way, but really at the technical level in the way you're describing. Do you think there's any chance for the big manufacturers to do that?

Phil Voglewede:

Do I think?

Zach Peterson:

Yeah, the guys that actually build the production assets, those people.

Phil Voglewede:

Yeah. Yeah. There's always hope, there's always. I guess I'm hopeful. I don't think in the near term it's going to happen, but I've been surprised before. I think as this Industry 4.0 continues to go and we start to realize the vision of AI and how that comes in, that's going to force a lot of these hands. Right now I don't see the manufacturers, the systems integrators demanding it because it's just not in their best interest yet. But we'll see, we'll see. I'm hopeful. I can't give a timeframe on that, but I'm hopeful, and it's something I'll continue to push for, it's something that I don't know if I'll see it in my career, but I do believe will come. And back to Omron lab, when you start to see it, when you start to see how much easier it is to do, these are the people that will be coming into manufacturing, coming into there and they'll say, "Well, wait a second, we did it like that here. Why can't I do it there? Why? Why not? Why not? That'll make my job easier. Why can't we do it?"

Zach Peterson:

Yeah. And I'm sure at some point, someone from a company that is interested in what you're doing might come in and have that eureka moment when they see it and they say, "Oh, we can suddenly revolutionize our entire line and we can have our mechanical assets talk to our electrical assets, we can have everything that worked together."

Phil Voglewede:

Yeah. And maybe that's that exponential thing, maybe it'll all of a sudden enough people will start to see it, it'll just grow. I think right now we're stuck into this, we're still living from the sins from the '80s, we're still living from the sins of hardware. How long has it taken us to USB, and plug and play, and PC software, and how the consumer is just like, "Look, I don't want to have to go to an IT professional when I buy a computer to set it up to work with my different things." And I think that's coming, it's just a matter of time.

Zach Peterson:

Okay. Well, as this evolves, of course, we'd love to have you come back on and talk to us some more to see how the manufacturing environment really has changed.

Phil Voglewede:

Yeah, absolutely. Anytime. It's been a pleasure.

Zach Peterson:

Great. Thank you so much for joining us. To everyone that's out there watching and listening, we've been talking to Phil Voglewede, professor and associate chair of the Department of Mechanical Engineering at Marquette University, he's also director of the Omron Advanced Automation Lab. If you are watching on YouTube, make sure to hit the subscribe button, you'll be able to keep up with all of our podcast episodes and tutorials as they come out. And last but not the least, don't stop learning, stay on track, and we'll see you next time.