Speaker 1 00:00:07 Hello everyone and welcome to the Robot Industry Podcast. We're glad you're here. And thank you for subscribing. I'm Jim Baretta, and our guest is Scott Linderman. Scott Linderman is the c e O of Mission Design and Automation. He has 30 years of leadership in automation and robotics, formally of JR Automation, where he served for many years in various leadership roles. Scott then took the role of President of BAA Systems, a stone robotics fabrication equipment provider in southeast Michigan, a Lake Superior State University grad in robotics systems engineering. Scott has served the automation and robotics community for over three decades. He's also been active in First Robotics and has been a member and served as a director for the Robot Industries Association, the ria, now known as a three. Scott, you are a busy man. Thanks for joining me,
Speaker 2 00:00:55 <laugh>. Thanks, Jim. Thanks for having me. Look forward to a chat here. So,
Speaker 1 00:00:58 And we're gonna talk a little bit today about robotics, automation and manufacturing and how it's getting simpler, and yet it's also getting more ex more complicated.
Speaker 2 00:01:08 Uh, thinking back on my 30 plus years of automation and experience, Jim, and there was a lot of really hard problems that have been solved throughout those years, and a lot of really different technology and a lot of high technology. Maybe some easy and maybe some not so easy to use. But, uh, at the same time, we solved a lot of really hard problems over the years and it really took a passionate team and a great relationship with your customer to make those really hard projects successful with the technology y'all, through the history and, uh, it's really sets the stage nice for our chat today, I think. So I think it's a great topic to talk about.
Speaker 1 00:01:43 Yeah, I'm very interested in it as well. And we have universal robots, I think to thank and their, for their Apple approach to automation with their app store, their education, which is free, their simple interfaces and their usability, and would you kind of blame them or appraise them for some of the easy stuff?
Speaker 2 00:02:00 Yeah, no, it's a great point, Jim. The, you know, uh, we really take advantage of how industries and technology changes throughout the year and throughout, over time. And then we really do have, uh, D V T Universal Robotics, apple Incorporated, as you mentioned, a lot of different people to thank for pushing the technology and then also becoming disruptors and allowing new technology to become state-of-the-art, and then bringing the whole industry industry up around itself and then making things easier and even standardizing things to make sure that they are really user, user friendly and widely adopted, which allows for a lot of different things that we'll get into, I'm sure, as far as training and acceptance in the marketplace, and some of those things that really allow problems to be solved quicker and easier and allow us to tackle some more difficult problems as well. So I think that's part of what happens when you have these, uh, new emerging technologies and these great new platforms, uh, evolving throughout time. So
Speaker 1 00:02:56 I think we ha also look at UI and the UX of, um, like man machine interfaces, right? It's getting a lot easier. I think people are spending a lot more time and money making it easier.
Speaker 2 00:03:08 Yeah, you know what, I think the, uh, development of tools and that user experience is what is key to long-term success. And in almost anything you adapt in technology or in automation projects, I've always pushed a, a machine or an automation cell has to be user friendly. It has to be comfortable for the operators to use every day. It has to be safe, it has to be comfortable. They have to understand when it's not working, why it's not working. They also has to be approachable for a maintenance person in order to troubleshoot, upgrade, those kind of things. And those technologies have definitely been, uh, driven to it way easier to use and way more mutually acceptable platforms. And I think that again, allows more automation to be easier implemented.
Speaker 1 00:03:51 I think we shouldn't leave the sensor guys out of this either, right? They're, they've really taken a, um, a plug and play approach to using sensing and automation.
Speaker 2 00:03:59 Yeah. So the, the perception or the what a machine can understand and adapt to and how flexible it can become through advanced sensors and easier to use sensors, more reliable sensors. We're very rarely dialing in four to 20 milliamp loops with shielded cables anymore. We're plugging in ethernet jacks, downloading drivers and getting going and then expecting the results are gonna be accurate instead of having to play with, uh, calibration routines and, uh, shunt resistors, all kinds of the old stuff has been replaced with the digital revolution. So overall, you have this underlying technology of going digital and digital technology being pervasive and the sensors and the things that are available with the plug and play technology is, uh, really it does help and makes our machines better and smarter and more user friendly as well.
Speaker 1 00:04:49 But Scott, and here's the, here's the, but as easy as it is, we kind of know that it's really getting more complex.
Speaker 2 00:04:57 Yeah, yeah, yeah. So this is the, this is the heart of the topic we're here to talk about, right? And I'm, I'm gonna tell a quick, uh, story that's gonna make a lot of people chuckle at the end, I think. But, uh, you know, originally we communicated with these people, uh, face to face and we had some snail mail and we have some different things. Then we invented telephones and we got really good at that, and we thought that was just amazing, right? Then we go to fax machines and emails and when they first came out, they were not universally accepted. You, you had to have a fax machine that matched on both ends of the wire in order to make a fax machine work. And for those of you who don't know what fax machines are, <laugh>, you had the same thing with email, right?
Speaker 2 00:05:33 When emails first came out, you had to know which email program you were using in order to send an email to someone else. And over the years that all gets adapted. And then now we have, um, texting, we have now web meetings, which we're, we're taking part in today. But I'll tell you, as easy as this technology is, and as universal as it is, there's nothing more nerve-wracking than walking into somebody else's facility with your computer and having to plug into the conference room tv, figure out how to get connected and then start up a web meeting and hope it works, let alone if your video will, that's embedded in your PowerPoint will play, right? So as easy and as evolved as all this technology is, it, it still has its challenges, but they're more accepted and we all understand it. And the first part of every web meeting is, Hey, can you hear me? Hey, can you hear me? Hey, you're on mute, right? <laugh>, it's, um, easy technology. The tools are there, it works, but it's still, uh, a very evolving process and it's still, uh, very challenging from time to time. And we all know that, right?
Speaker 1 00:06:35 When you, uh, are start considering building automation, one of the first thing that you want to do right, is identify and solve those problems.
Speaker 2 00:06:43 Yeah. So I, I'll go back to the, you know, as powerful as the tools get, right, whether it's the robots and the cobots and the simulations that are available now, and whether it's vision systems and AI algorithms and plug-in technology and even the data collection, how easy it is to get stuff to the cloud, it's really an important piece to say until we understand the right problem and the most valuable part of the problem to solve which tool and which technology should come to the table is, is the, the second piece, right? The first piece is always what's the right problem? Where's the value and why do I wanna solve this problem? How much will it cost and the value? And we could, we have a lot of podcasts about ROIs and everything in regards to how much money it will take, but in reality, the definition of the problem will drive you to which tools and which techniques you should undertake to solve that problem in the best way possible. And I think that's the part that's becoming easier, right? That e applying the tools is becoming easier and easier. Identifying the problem, setting a value to it, solving the problem correctly hasn't gotten easier. And I don't know that it will over time, but these tools that are available definitely easier. And this is the conundrum that we, uh, again, at the heart of our conversation, I think,
Speaker 1 00:08:01 So one of the other big challenges I think is, is kind of predicting and planning for unintended consequences.
Speaker 2 00:08:09 Yeah. Yeah. So if your problem statement is, I just wanna help this person out a little bit, and if it, if it doesn't work, right? If there's a hiccup, a sensor doesn't make the operator's right there and it's a nice easy cobot and they can just come over and reteach it, and that's okay. If it happens a few times a day, that's okay. Right? This other part of what you just alluded to is, I like to say the hardest problem is the one that has to work all the time for anybody anywhere, right? So you have to make a machine that can work all the time and know when it's not working and anyone can walk up to and understand the problem and, and use the machine and or troubleshoot it. And then it will do that all the time, not just on first shift.
Speaker 2 00:08:53 It's gotta work second shift, it's gotta work third shift, it's a completely different problem statement compared to, ah, do some machine tending cuz I got an operator floating around and if there's a problem, he'll come over and fix it. And that's a new problem that's more solvable now. So again, depending on your problem statement, you really do need to, uh, understand what's the, what you're trying to accomplish, right? And, and the easy to use thing is another story where you go, it's easy to use as long as your problem set can be solved with the easy solution, right? You can walk through the trade show. This is what got us talking, Jim, and I'll just salude for backtrack for a second. You know, you're walking around the automate show, you're walking around IMTS or the robot show and vision show in Boston and you're just, everybody will say, Hey, come on in my booth, I'll teach you to program a robot in five minutes.
Speaker 1 00:09:41 Yep.
Speaker 2 00:09:42 Throw your parts in front of my AI vision system and we'll teach it right away, right? And, and they, that that is real. That all exists. And if you're problem set allows that to be the solution, that's awesome, right? But, um, you wanna make sure you've defined your problem correctly. And I, uh, I think it's important, I'll, I'll add in one of my most important concepts here is to use integrators and get started with technology. It's a journey. It's not a one-time project, it's a theme I've been on for a while and you, you know, this, uh, part of the business too is just get started. But what you need to get started on is the problem definition, the value proposition, and then start applying the right tools and dragging in the experts to help you define the problem. Even. So this whole idea of how experts can help you, uh, maybe leads to another set of questions and answers that you don't have, but getting the industry experts involved as you define the problem, can be really crucial to the outcome of and feeling successful about your outcomes
Speaker 1 00:10:42 As well. When you're, uh, working with a client and maybe they're, they've got automation already, but they have to scale or they bought something from you and you have to scale that, what happens about trying to give them the best solutions in that situation?
Speaker 2 00:10:55 Yeah, so I think it's again, uh, the scaling issue and how to get started first, but then with the end in mind, right? Quite often you get started, but you wanna start with the end in mind. And if the end is we're gonna have a lot of different automation projects and we want to get engaged, you want to pick a good integrator, you want to pick the right technology, you want to start with a problem that's gonna be it. Um, an example of what you're gonna try to do so you can work out the hard parts of the process, figure out what are the variables in play that you didn't know existed right now in your process. But as soon as you start to automate it or apply some of these easy tools, you'll find out, oh, here's another variable we didn't even know. And then you're gonna have to try to solve this.
Speaker 2 00:11:37 So you again, wanna work with your problem definition, get with some industry experts, systems integrators, et cetera, that can help you define the problem, define the variables, and then when it's time to scale, you'll be on a really strong platform and you'll be very confident that you've used the proper tools. And then you gotta, you wanna staff up and get your, uh, people trained and do the right things to have your people ready and able to operate and use that equipment as well. Uh, it's key to long-term success and, and that overall feeling that automation works for us, right? It's an important piece.
Speaker 1 00:12:10 Scott, what are the other things that are making it harder?
Speaker 2 00:12:13 Oh yeah. So just, I think it's a <laugh> it's a loaded question, right? We, we were here to talk how easy the tools are and that technology's really come a long ways. But what the, what that also does is let you go after some harder problems. So it used to be as long as you had one part over and over the same part, you could get your ROI to meet a justification and it would be cost effective, but with a higher flexibility of different parts and different luck models and turnover and changes. And I want to be able to run a lot of different parts through my machine. That's one that used to be fairly expensive to accommodate, but now the technology's become available where you can offer a more flexible solution at a similar cost to an, an old, uh, fixed automation perhaps, right? So that's one piece is flexibility, um, and the requirements to be able to run multiple different parts and be able to adapt to a changing environment.
Speaker 2 00:13:09 The second thing, and I don't know that there's a list of these, it's a very long list probably, but, uh, just the expectation that, again, as I said, that it can be able to run with anybody at any time and I'm gonna be able to get the data in, in my iPhone app in my pocket to my boss. There's another expectation on the data collection and how the data is available and who it's available to, uh, which used to be very, very difficult to do. And then now again, that's another one of those technologies, it's become easier and easier, but along with that comes an expectation that that data is understood, what's the definition of the meaning of the data? So it gets all the way back to that original comment about even though you can get data in your pocket very easily and quickly, what does the data mean and the definition of that problem originally, and what's the definition of the data that's gonna come with the solution? And, uh, it's, uh, it does still start with that foundational thing, but, uh, it makes it harder because it people have higher expectations in general would be one answer to your question. So,
Speaker 1 00:14:07 And there's less engineers and less engineering in the factory today, would you agree? Yep,
Speaker 2 00:14:13 Yep. For sure. I think the, um, oh yeah, it's, it's an ongoing trend that the, the technology itself is, uh, is becoming easier, more widely accepted. So I don't need to have as many engineers perhaps and the machine should just run and it will recover when it doesn't run. So this is allowing less and less trained professional engineers required even to be, to support different kinds of equipment. So I don't know that it's a downside, but at the same time, you want to be sure you're solving the problem again correctly. So you gotta understand your manufacturing practice. If you don't have a strong staff internally, you need to lean on some kind of systems integrator or your local technology distributor who's somebody who's gonna bring this technology to you and make sure it's applied properly. But then again, the technology's nice and easy. Um, you know, training training's, one of the things that, um, over the years you used to have to go one week of training was required at your vendor's site if you wanted to use this climate of equipment, whether it's robots, vision systems, anything you had to go for training cuz they were fairly steep learning curve to them.
Speaker 2 00:15:22 Where now the learning curve has definitely come down. So training has is a double-edged sword to me, right? Do you have fully trained engineers and staff in your facility? Like used to be required maybe we would say is not the double edged sword. Part of that is, um, you know, an expert makes things look easy and quite often they're not. Right? So I'm gonna switch into my Canadian mode for a second, Jim, because right, if you're a, if you're a sports athlete and hockey hockey's one of the hardest sports to do if you don't put in a lot of effort, right? So, you know, you, you, uh, can make something that looks really easy, but it's actually very, very hard to do. And I like that analogy. If those professional athletes and, and I will refer to them as systems integrators in this business. Yep.
Speaker 2 00:16:07 We work at this every day and our engineers are trained and they're experts at this and sometimes they make things look really easy that are actually really hard to do. Uh, and it's again, just because they're experts and they're professionals and I think you can use as an end user looking for automation projects, sometimes it will look really easy, but it actually is because the person coming in and making it happen is a is a trained professional and they've practiced for hours and hours and they've shot a a thousand puck a night in their basement for years, right? This is, um, is not as easy as it may look sometimes. So
Speaker 1 00:16:42 The, um, one of the things that's making it kind of hard or easy or is, is that vendors are getting into the supply chain and what are some of your thoughts on that?
Speaker 2 00:16:52 Yeah, you know, if you go back, um, to the tools and the, and the fact that vendors bring hardware used to be, and you just, you needed a part numbers and they were the support and they were the stock area of, of hardware for other people to use, where the value stream, as you mentioned, as moved up and down and moved around for the different technologies. And as you go through, where is my support structure for training, for where's my support structure for proper implementation and then stocking and delivery and support spare parts, that, that's all moved around, right? So as, as a, as a value added provider, distributors and vendors of tooling tools, whether it's hardware, vision systems, robots, they wanna bring more value to the end users, more direct end value as they can. And I think it's again, a double-edged sword I would say.
Speaker 2 00:17:45 But, uh, the quicker and easier we can solve more problems for people, our whole industry will get better as long as, again, I just keep beating on this drum as long as we're solving the right problem. Because the risk is someone says, Hey, this is easy, just go ahead and plug this in and and it'll solve your problem for you. And you'll say, sweet, and you'll give them a PO and a check and the stuff will come and it will do the simple part, but it's not what your problem was. But there was never this next level of conversation about the details. So I think the vendors going up and down their value proposition and bringing more to the end users, it's powerful, it's flexible, it's direct to the end users. We just can't miss out and have a misapplied. If we misapply 'em and it doesn't work, the uh, and the attitude will become, ah, we tried it once, it didn't work. And that's a risk to our whole industry. So we wanna make sure we match the problem and the solution really well.
Speaker 1 00:18:41 Art, do you feel that parts and part families and part feeding, do you think it's getting harder?
Speaker 2 00:18:47 Well, I think the, yeah, we mentioned earlier a little bit about the flexibility and then requirements that are put on different, uh, types of machinery and how that continues to go up. But I also would say that, that the ability to solve those problems is getting more and more powerful. So I don't know if I have a clear answer, but yeah, the requirements for more flexibility in part makes, is continues to go up. Um, but our ability to solve those problems continue to get stronger and stronger. So, you know, the, the paneas have been picking of any part, any time just shove a bin in, uh, the robots will pick 'em up automatically is still quite a long ways away. But at the same time, there's a lot of tools that allow subsets of that to be very easily and very successfully accomplished. Again, as long as you can define the problem into some subset, get the right tools applied, some of those problems are becoming easier, easier to solve and very robustly solved even. But define anything anywhere, problem will always be a hard one. So
Speaker 1 00:19:46 Is budgeting, and we, you've kind of touched on this earlier, is budgeting for automation or maintenance, is it getting more complex?
Speaker 2 00:19:53 Yeah, for sure. You know how much, um, how much money is available to solve what kind of problems is where you start, right? First you say, I'm a manufacturer, I'm an end user of some kind and I want to use automation. My boss said go get one of those cobots, we need to have one, right? Or I want data, so go get me industry 4.0 data, right? So these are, these are things that are real and their demands placed on a top level. And then you have the, the bottom up level as far as, hey, we got this quality problem and it's not working and we're shipping bad parts. And so the, the, the drive for what's motivating people to implement different technologies, this is very real and it's always been there, right? But what is getting more sophisticated is how they're interacting with each other.
Speaker 2 00:20:40 It's not simply put a quality check in place, leave it, sit there, it's put the right quality check in, tell me good and bad, give me measurement data, write trends to a file somewhere. Use AI to improve as the day goes on, right? So the, the solution that comes to this simple problem becomes a, a more detailed and a more valuable solution at the same time. So how much money is there? Are you just solving a problem or are you gonna solve the problem, gather data and make your whole process better? Well, that's more valuable. So the, the equation for the ROI changes, and I'm just using one quick example, but, uh, yeah, the ROI and the calculation much more complex, way more variables because the tools allow you to maybe instead of a simple solution, spend a little more money and get a really more valuable solution. And this is what should be considered in your ROIs is how can I get even more value out of a simpler solution perhaps.
Speaker 1 00:21:37 Scott, do you find the conversation between OT and it becoming simpler or harder? Or is it even happening? Uh,
Speaker 2 00:21:44 Yeah, the, so the, the technology, the data, the connections and how things are intertwined, it's a trend everywhere in our lives, in our personal lives. It's a trend in our factories, it's a trend whether we're traveling everywhere, our data and and connections are, are everywhere. So yes, the conversation is continually how are these things intertwined? We don't want standalone anything anymore, right? We don't, as people, we don't in our factories, we don't in our machinery. So how to connect them and what are the risks and the security concerns, uh, it's a conversation. As soon as someone wants to say, let's get these things connected, let's make 'em talk to each other, uh, sure we can do that. It's just like, connect into the conference room TV again, right? Yeah, we can do that <laugh>. Okay, now let's figure out the details. And it's always messier in the details, right?
Speaker 2 00:22:34 So the conversations take place. Yes, the desire is there for sure, and the desire is there because there's a perceived value to having things connected and making them easily talk to each other. It's back to the, that plug and play. All I do is plug it in and it works. Yep. Okay, sure. But what's the definition of works and is that what I really need? And it's a much harder problem than will it plug in? Sure. Will it do what I want it to? And will it be the right value proposition? It, it's a much more difficult question.
Speaker 1 00:23:03 Uh, this is my last question for you, Scott. Are you dealing with clients around cybersecurity or is this one just more complexity?
Speaker 2 00:23:10 Yeah, that just, uh, popped into your head cuz I mentioned security and connecting this stuff. I hear every it guy around the country right now, a little puckered up, but, um, it's very real. Um, again, in our personal lives it's very real and in the factory floor, yeah, as soon as someone wants the data, they want to be plugged in. They want to be on ethernet. The next question is, who do I have to talk to to figure out what the rules and regulations are gonna be? There are technology solutions to solve almost every concern out there. Um, but it's a conversation you have to have and you need to be coming again with the tools are there and the technology is there. The, the downside of the cybersecurity and the I t OT thing is that it changes so fast of what's acceptable in, in a security environment and what's available in hardware and industrial platforms. They're, they're not quite on par with each other, even though they're chasing each other rapidly all the time. Uh, it's definitely an ongoing conversation, always. Right. So
Speaker 1 00:24:11 Scott, thanks for coming onto the podcast. Um, what do you like to do when you're not building automation?
Speaker 2 00:24:16 Uh, yeah, it's a good question. Uh, no, we had, you know, friends and family. We live in West Michigan, so on the lake or, uh, with your friends and family doing some sports, hanging out, uh, hunting, fishing and those kind of things. Uh, it's just what we do here and we, I definitely enjoy those activities.
Speaker 1 00:24:33 It's, uh, good to hear your voice again and how can people get ahold of you?
Speaker 2 00:24:36 Yeah. You know, I'm sure there'll be a link in the podcast notes somewhere, but, uh, absolutely. Uh, I'm on LinkedIn. Feel free to reach out personally if you want to connect that way or professionally, I guess. And then, uh, my company is mission design auto.com and then go there and check it out.
Speaker 1 00:24:52 Scott. Thanks very much. You have a good rest of your day. Bye now. Our sponsor for this episode is Earhart Automation Systems. Earhart builds and commissions turnkey solutions for their worldwide clients. With over 80 years of precision manufacturing, they understand the complex world of robotics, automated manufacturing and project management, delivering world class custom automation on time and on budget. Contact one of their sales engineers to see what Earhart can build for you. Their
[email protected] and Earhart is spelled E H R H A R D T. I'd like to thank an all J three, the Association for Advancing Automation. They're the leading trade association for robotics, vision and imaging motion control and motors, and the industrial artificial intelligence technologies. Visit automate.org to learn more. I'd like to recognize our friends at Painted Robot. Painted robot builds and integrates digital solutions. They're a web development firm that offers seo, digital social marketing, and can set up and connect c r m and other e r p tools to unify marketing, sales, and operations. And you'll find
[email protected]. And if you'd like to get in touch with us at the Robot Industry Podcast, you can find me, Jim Beretta on LinkedIn. We'll see you next time. Thanks for listening. Be safe out there. Today's podcast was produced by Customer Traction Industrial Marketing. I'd like to recognize my nephew, Chris Gray, for music, Jeffrey Bremner for audio production. My business partner Janet, and our sponsor, Erhardt Automation Systems.
