You Can’t Automate What You Can’t Find: RTLS and the Data Foundation for Lights-Out | Ep. 47

[0:00] Are there any other real world applications that people should be looking at for RTLS? Yeah, one of the coolest ones I’ve seen so far, and I, for obvious reasons, I can’t mention who it is, but we’ll say an aerospace slash defense company, right? They’re capable of doing security and intruder detection using cameras, LIDAR, and tracking with RTLS as a redundancy to be able to say whether or not someone that they see in their LIDAR or their camera is actually someone that should be there. Because what they don’t want to do is necessarily try to do like, you know, facial recognition and identification and whatnot. But what they’re actually capable of doing is saying, hey, I’ve detected that a person is here.

And then they reference in, you know, whatever RTLS software they have, is there a data point for that person? Because if not, I have automation that says lock all the doors, shut everything down, lock every computer, you know, so they’re able to in real time identify that there’s an intruder there. So it’s really fascinating to see what people come up with, with using this location data. I might need that at my house when my oldest son comes home from college.

[1:21] Just hear the garage door open now and you’re like, he’s here. Talent is scarce, experience even more so, driving up costs and sleepless nights. You may even think to yourself, can I do this? But this new era brings new technology and a different perspective on your operations.

What you will hear will turn on a light bulb in your mind so you can turn out the lights in your shop. Get ready to sleep soundly while your shop never stops. Get ready for Making Chips Lights Out with your hosts, Nick Goelner, Eric Nekic and David Buick.

What’s up, everybody, and welcome back to another episode of the Lights Out Podcast. I am one of your hosts, David Buick, joined here with my co-host, Eric, the Croatian sensation, Nekic. David, how are you? Hey, Eric, how’s it going? I’m doing phenomenal, sir.

It’s the two of us because I think I missed a couple episodes which hurt Nick’s feelings, and so I think he just figured he’d let us roll with this one without him just to even the score a bit. Right, and for those of us who are actually watching this episode, they’ll be able to see the Serbian prison in which you’re recording from. Yeah, well, this is exciting for me because I’m recording from what will be something I call Smart Shop Studio.

It’s something I’m working on building and putting together. It’s also where I’ll hopefully be recording many future Lights Out podcasts from, so I thought I would kick that off by recording this week’s episodes from this empty husk of a building which we’ll be getting some work done very soon. There’s literally birds flying around in here.

It’s pretty rustic right now, but enough about me. And we’re all super excited for you. And yeah, enough about you.

Today’s guest is pretty exciting. Yeah, absolutely. We’re super lucky to be joined by Mitch Tucker from HID.

Welcome to the show, Mitch. Thanks, Dave. Thanks, Eric.

You and I met a few weeks ago at the Zoller Technology Days event. We had some mutual friends there, which is how we got introduced. But yeah, why don’t you tell us just a little bit about where you’re at right now, what you do, and what we’re going to be talking about today? Yeah, sure.

Thanks. So a little bit about what I do. I actually serve the Midwest region and then some.

So working for HID, who’s kind of a leader in the RTLS space, we try to take more of a consultative approach to customers. So being able to sit down, talk with people who are having struggles or have ideas of innovation, hearing those ideas and empowering them to do those things or working backward from those ideas and trying to solve their problem. I’m very fortunate to be able to work for a company who has such a wide variety of products and solutions and such a wide partner network that we don’t necessarily have to focus on promoting one thing or another.

We can actually just focus on the problem at hand and worry about implementing Industry 4.0 and preparing for the next generation of innovation. So it’s nice to be able to utilize the background that I have and kind of empower people with that knowledge. For the layman like me, Mitch, what is RTLS? Yeah, so RTLS stands for real-time location systems.

And all that means in general terms is you have a system that tracks the location of things. Now at face value, it sounds very simple, doesn’t seem very effective outside of where is this thing, but there’s so much more to that and I’m excited to get into that. Yeah, so I mean, high level, are we talking about like the white space that exists between our manufacturing processes that maybe a lot of shops aren’t looking at? Yeah, it’s a little bit of both.

I would say the biggest challenge that most industrial companies have is not knowing where things are in between the controlled processes. A lot of companies are going to closed loop systems, automated, you know, robotic systems, you know, maybe they have some sort of conveyor tracking on the line. But once it leaves those controlled processes, no one really knows where it goes or how long it spends in a certain time.

[6:08] So I want to paint a picture for you and then you tell me if I’m onto it and then I’ll let David take over because this is a really interesting topic and I think it’s going to be really impactful for our listeners. But my colleague Kent has worked here over 30 years and it’s not uncommon to be on the manufacturing floor and see him just grabbing a tray of parts and moving it to the next point in the process, whether that’s getting it to another mill or a lathe function or maybe getting packaged to go out for heat treat or something. And the reason Kent’s doing it is because he’s worked here 30 years and he knows where those things are going to get stuck on the shop floor.

We don’t have real visibility to that. Thank God we have some tribal knowledge that is privy to that information, right? But I’d imagine for a lot of shops who maybe don’t have a Kent, those parts kind of get lost in space for a few hours, a few days, a few weeks. Yeah, it’s funny you use the term tribal knowledge because I would say at least six, seven, eight out of ten times when I’m having conversations with people that aren’t on the forefront or the cutting edge of industry 4.0 and beyond, they like to use that term where they say, you know, the majority of our people have that tribal knowledge and we don’t know how to transfer that to other people.

And so you kind of have to take a step back and dig a little bit deeper with them and ask them, like, why do you have to transfer that to other people? Why do you have to implement that into your training, right? You should have more oversight into what your facility is doing, what people are doing, and have more control over your processes. Because ultimately, having control supports that sustainability aspect of the continuous improvement journey. Love it, love it, and can’t wait to get into the weeds here.

[8:03] Yeah, but before we get into the weeds on this kind of cool technology, one that frankly I don’t know a ton about, so I’m excited for you to school me on it a little bit, Mitch. Why don’t we talk a little bit about your professional journey so far? You know, just high level, where have you been, what have you learned, and what led you to this point where you are right now? All right, thanks for asking. It’s definitely a passionate story that I like to talk about with because it kind of starts with me not knowing what I wanted to do with my career and kind of dabbling in the engineering space a bit.

When I first got introduced to an industrial environment, I was curious, right? I was always curious about where do the products come from, where does it start? Does it start with an idea and then it comes into a drawing, then how does it get manufactured? How do you control a global business at such scale? And I always kind of had a passion for figuring out how to directly impact the business in a positive way and so I was always curious to kind of go out and learn and take on new challenges and opportunities and that curiosity drove me from sitting behind a desk looking at engineering drawings to taking those drawings and going out on the floor and watching people make the product that I was, you know, ultimately responsible for. And while I was doing that, my curiosity was asking the question of, well, how can this be better, right? Can I design it better? Can they manufacture it better? Can the process be better? Can we train better? What can we do to improve this system? And that kind of led me into a continuous improvement role which more or less was pioneered at the time when I had stepped into it and that empowered me to get that direct exposure into the bottom line of the business, both top and bottom lines of the business. And once I kind of got a taste for that, I was addicted, right? I was so addicted to be able to drive change and improve not only the financial well-being of the company but the culture of the company because it’s kind of two-folds when it comes to continuous improvement.

There is a financial aspect which is usually the main driver. You work backward from financial problems but there’s also the cultural impact, right? Having a lean organization, introducing industry 4.0, it definitely changes the culture because people feel empowered. They feel like they’re being supported, like their jobs are getting easier and they’re more productive.

At the end of the day, everybody wants to be productive. So as I went through this cycle of continuous improvement, I really found that this is what I wanted to do with my career was stay focused on process improvement, continuous improvement, industry 4.0 and beyond and kind of being the evangelist for these things. So I didn’t necessarily want to stay in continuous improvement as an engineer, you know, the rest of my career.

So I tried to figure out like how can I apply this to business? How can I apply this to getting to a point in an organization where I can kind of bleed this down into the rest of the groups? And so where I transitioned into was more of a program management, project management focus where I had multiple aspects of responsibility, where I had quality people, I had production people, supply chain people, all things that are impacted by continuous improvement efforts. And also, you know, as a program manager taking responsibility of the continuous improvement initiatives themselves. So while I was doing that, I kind of got faced with an opportunity of going to a business that I did not realize even existed at the time.

Because when I was in continuous improvement, and when I was in program management, I kept telling myself when I was sitting at the computer, and when I was going back and forth between my computer and the production environment, I wish I could just see everything at once. And I wish I could just take that data and just collect it all and use it to drive change. But instead, what I found myself doing was making assumptions.

I was going out to the floor for however much time I had, right, say it was 30 to 40 minutes, I go out, I do some time studies, I come back. Well, the problem is, that’s not always consistent. It doesn’t always give you the right information.

Right? And it doesn’t, it definitely doesn’t lead you toward the industry 4.0 initiative. So I kind of had to make a decision, do I want to go to a company that has everything that I’ve been looking for? Or do I want to bring that technology to the company that I’m currently at? And the outcome for me was was relatively easy after I had, you know, thought about it for a few days. I have the opportunity to go be an evangelist for everything that I’ve ever wanted in an industrial environment.

So I’m glad that I took that leap. And for the last four or five years, I’ve spent all of my focus and energy into RTLS and continuous improvement and kind of, you know, being a consultant to the business consumers for innovation. Awesome.

Wow, that’s, that’s quite a story. And some parallels from my own there, you know, just kind of starting out in engineering, and then kind of learning more and more about, yeah, process and how that all fits within the context of the manufacturing workflow. I think it’s just such a cool journey, and an ongoing journey, right, in manufacturing, because there’s always new things to learn.

So now you’re with HID, RTLS is one of the technologies and things that you support. That’s a technology that I’ve always perceived is really just for large warehouses, enterprise level businesses. Help me out here.

[13:44] Is that wrong? Have I misunderstood it? Is there application for the smaller enterprise or smaller shop? I think that’s a common assumption. Okay. I think that’s a very common assumption.

You’re not wrong, but there’s so much more to it. It did start in the industrial space. There was no question about that.

The original intent behind RTLS was to replace manual actions, right? Because in many automotive environments, you have manual scans of barcodes, and RTLS was meant to replace that. So kind of bring it back to the wider picture here. We don’t just operate in the industrial space, right? We operate at airports.

We operate in hospitals. We operate in data centers, right? There’s so many things, there’s so many industries that require that knowledge, that location data to be able to drive the future of their business. Okay, awesome.

So within the context of a machine shop, let’s build a bridge for our listeners who might be wondering, okay, cool, this theme of industry 4.0 and continuous improvement and RTLS. How does that all fit together for your typical job shop or your contract manufacturer who maybe knows a little bit about this already, but never thought about it for themselves? You know, that’s an interesting segue. And I just wanted to kind of like bookend that, David, with some, you know, we here at Hennig are looking at RTLS right now.

And I think we’re looking at it under two lenses that maybe you can speak to, Mitch. I think one, we’re looking at it in a very traditional form, which would be, you know, we’ve got a million square feet of manufacturing space in Rockford. And it’s important to kind of start, you know, when we have a big push from the top down for continuous improvement, lean manufacturing.

So, you know, all of that, I think, makes sense. The other thing that we’re kind of looking at here is from more of like a sales tool, right? If you’ve listened to this podcast, you’ve heard it a bunch of times, right? Like the mistake people make is like, we’re going to install an automation system, and it’s going to solve all our problems. And I don’t think they always have crystal clear visibility to the bottlenecks being created upstream and downstream of this automated solution.

And I think that for us, RTLS is going to be a really unique tool in showing our customers, showing people that we’re trying to help kind of move into that, you know, into those advanced manufacturing techniques, that these are the other things that are going to happen around you when you install this pallet system. So with that, can’t wait to hear you weigh in on this. Yeah, definitely.

To Dave’s point, right, I want to come back to that. And then I’ll get to your question. I think the future of machine shop environments is trending more toward the closed loop automated systems where, you know, you can load your tools, you can load your material, press a button, you have your programs, it runs, right? What happens when that part leaves that tool? Where does it go? How much time does it spend in certain areas? Did someone put it in the right place? Did the right person take it out of there? Perhaps someone walked up and ran and used that machine who was not qualified to use that machine.

[17:08] There’s so many things that you can do with the location data from people, from materials, from moving equipment. So it definitely applies to machine shop environments or in certain instances, right, like we were at Solr a few weeks ago, and they have automated, you know, tool carts that move between inventory and the machines themselves. Well, to a degree, not everybody can afford that, right? So there are certain instances where people are manually getting those tools and taking them over to their equipment.

Well, what happens if a tool doesn’t make it? Or what happens if that cart doesn’t move as quickly as it should, and then all of a sudden that machine is sitting idle and your OEE is dropping, right? So there’s definitely a lot to factor in there. Not every environment is perfect. So we try to capture the imperfections.

That’s ultimately what you’re doing with RTLS. When it comes to the large warehouses, right, you say a million square feet. It’s impossible to know what’s going on there.

It’s so difficult. Trust me, we know. No.

Yeah, I’ve worked in, you know, single shop environments before where, you know, a tool is missing and you spend 30 minutes looking for it and it’s 30 feet away, but it’s small and you can’t find it, right? So it’s difficult even in those environments, let alone a million square feet where anybody can be anywhere with anything at any time. So being able to have that oversight, seeing things in real time is one aspect, but being able to collect the historical data and use that as evidence to make changes is definitely the most important aspect, I think. Yeah, yeah.

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We’ll see you there. To Eric’s point, a lot of conversations that we have are actually around both what is the value of the internal team and what is the value to the customer? Because actually, we not only solve problems internally, but we actually provide, let’s say a digital twin, like HID doesn’t provide the digital twin, but our partners actually provide digital twins on top of the RTLS data that actually can function primarily as they want as a marketing tool. So like what you were saying earlier, some customers might want to see that.

What is your control of your process? How can I ensure that you actually know what’s going on in your facility? If I call you up and say, hey, where is this order? How do you tell me that? Where is it in the process? If I ask you to expedite something, how are you going to do that? And it’s very simple with a digital twin and RTLS data. I love that you bring that up because that’s 100% the application in which we’re looking at it right now, both for our own internal use, but also being able to show a manufacturing facility, like what a digital process simulation, a digital twin that involves RTLS, that involves the productivity gains. We had actually heard from a partner of ours that there were quite a few larger manufacturers that were moving into an area where any capital purchases, any capital expenditures had to be tied to this sort of digital process prove out.

So they wanted to see the digital twin. They wanted to see that full throughput cycle. And I have to assume that for a lot of those companies, that’s going to include technology like RTLS.

Yeah, that’s a trend that we’ve seen for decades as far as having capital allocated to infrastructure. What has not been the trend up until the last five, maybe five to 10 years, is that that infrastructure focus was on RTLS. The infrastructure was more on how can we get more, you know, Wi-Fi inside? Can we get better coverage? Can we get better, you know, connectivity at each station? Can we get more Wi-Fi outdoors so people don’t lose connectivity when they go out there? And then you kind of started to see this shift of, well, okay, well, we have as good of a Wi-Fi infrastructure as we can have.

What else, right? How can we take this a step further? And the trend that we’re seeing now, thankfully, is that when we get on conversations with people and we start talking about, hey, why did you approach us, right? If it’s not, I have a burning hole and I need to fill it and I need to get out of this mess, it’s actually, I would say eight out of 10 times, it’s actually, hey, we have capital allocated to, you know, improve our infrastructure. And one of the things that we’ve identified is RTLS. So, it’s really cool to see that coming.

And actually, one of the things that we see is that the RTLS infrastructure is becoming a commodity as opposed to a nice to have. I would say, yeah, 10 years ago and beyond, it was very, hey, that’s cool, but how do we justify this, right? There wasn’t a ton of knowledge, right? And over the last five years, been so many educational campaigns to try to teach people what RTLS is and how it’s valuable to the industry. And I think it’s a combination of that as well as the transition to what we’re calling industry 5.0, which is AI, right? And I think without the foundation of the data, you can’t really make that transition very well.

I agree. So, industry 5.0, what we’re calling, you know, the AI revolution, AI is only as good as the data you give it. If you don’t have the infrastructure and the data collection, what’s the point of moving to industry 5.0? What’s the point of implementing these robust AI systems? So, what we’re seeing is that by like 2030, 2030 to 2035, we’ll say, everybody is going to be rushing to get RTLS because they’re either going to go to industry 5.0 and say, hey, this isn’t doing everything that we want it to.

[24:17] And they’re going to realize the hole that they have with the data that they’re missing, which is the location data, or you’re going to see them say, okay, I see this coming. Let’s put in RTLS, then let’s move to an AI-based system. I mean, even your evangelists on the closed loop, lights out, you know, factory thinkers, like, even they know, you can’t do that without RTLS because not everything can be closed loop.

Absolutely. So, I want to talk about like what an adoption trajectory looks like. But first, you know, we’ve talked about search time costs, obviously, like bottlenecks, location-based automation.

Are there any other real-world applications that people should be looking at for RTLS? Yeah, one of the coolest ones I’ve seen so far, and I, for obvious reasons, I can’t mention who it is, but we’ll say an aerospace slash defense company, right? Okay. They’re capable of doing security and intruder detection using cameras, LIDAR, and tracking with RTLS as a redundancy to be able to say whether or not someone that they see in their LIDAR or their camera is actually someone that should be there. Because what they don’t want to do is necessarily try to do like, you know, facial recognition and identification and whatnot.

But what they’re actually capable of doing is saying, hey, I’ve detected that a person is here. And then they reference in, you know, whatever RTLS software they have, is there a data point for that person? Because if not, I have automation that says lock all the doors, shut everything down, lock every computer, you know, so they’re able to, in real time, identify that there’s an intruder there. So, it’s really fascinating to see what people come up with, with using this location data.

Yeah, I might need that at my house when my oldest son comes home from college. You know, just hear the garage door open now and you’re like, he’s here! If you run a job shop, manage a job shop, or spend your day trying to squeeze more output out of the same people, machines, and hours, this one’s for you. During IMTS week, the job shops, workshop, and networking reception takes place on Tuesday, September 15th.

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If you’re going to IMTS to find ideas that can move the needle in your shop, don’t just walk the aisles, get in the room. Learn more and register at IMTS.com. Walk us through the adoption trajectory for, you know, a manufacturing facility. I have to believe that every single manufacturing facility on earth deals with some sort of search time cost, with some sort of, you know, automation-based, location-based bottlenecks.

[27:32] I believe, personally, they are extremely common and probably costing millions, if not billions, every year. How do people get started? Yeah, it’s a great question. It’s one that we face every day, right? It’s basically, you get someone who’s intrigued by the technology, they get intrigued by hearing success stories, but they don’t know where to start and they don’t necessarily want to just come in and say, hey, I’m going to spend a million dollars on my facility and make it entirely, you know, RTLS-based.

I don’t think that’s the right approach. Now, from a sales perspective, someone might try to push that on you. And I don’t appreciate that and that’s not where I come from when I talk to people.

I’ve actually had instances over the past, you know, several years where I’ve been in calls where I’ve said, hey, you know, I’m very happy to support you in bringing an RTLS system into your facility. I think there’s a few things that we should talk about and do first before we do that. And that’s why I put so much emphasis on being a consultant first, because at the end of the day, you’re not going to implement an RTLS system in a chaotic environment where you have no idea what’s going on and you don’t know what should be going on, right? It’s one thing to not understand what’s going on, but it’s another to not know what the benchmark is.

And I think the first step to anybody that’s looking at RTLS is to actually think about what the processes should be. So when you have that data, you have a benchmark to go off of, right? Because you’re going to not only use that to watch the process and say, did it follow the process or not, but you’re also going to look at it and be able to create automations using that location data. And if you don’t know what those processes are, it’s not as valuable to you.

[29:20] So what I like to do is kind of sit down with people and ask about their current processes. What does that look like? Run me, you know, from raw material to finished goods and where do the finished goods get stored? How does it get picked up by the third party logistics to understand where they’re at in the continuous improvement journey? Because at the end of the day, I have to come back to being in our continuous improvement consultant first. I have to.

That’s where my passion lies. And I’m happy to bring RTLS in and help implement that, but you got to know what your processes are. So from that trajectory, when we get people who understand their processes, we can then build upon that.

And I think the first most important thing is how much money do you spend? How much or how expensive are the products you produce? And what is the size of your business? A million-dollar project for a company that makes a million dollars a year is not a good investment. It’s not, right? So I would never promote, you know, any kind of project that would be like that, but a million-dollar project for a 500 million-dollar business, they might not even bat an eye at it, right? So there’s different scales that you can kind of look at when you’re speaking with a customer. If a small machine shop came and said, hey, I really want to know where these tools are.

We waste, you know, 15 minutes a day trying to find this one tool or, you know, however many tools. Well, you could start with something that’s simple, right? Let’s say maybe you go with an RFID system. You know, a simple RFID system costs a couple thousand dollars.

[30:54] And then say you want to get a little bit more particular and you want to know where it’s moving throughout the facility and, you know, pinch points aren’t working anymore. So then you would scale up to maybe like a Bluetooth technology where you can actually get more of a real-time tracking as opposed to identification of, hey, this is here, you know, within this zone and yada yada. Even though that’s kind of how Bluetooth works, there’s so much more to Bluetooth that can get you a little bit higher accuracy and more real-time information.

Now, when you really scale up and you’re at what I was just saying was like more of like a $500 million a year business, right? You’re getting more into flexibility and precision accuracy and trying to squeak out every single ounce of ROI that I can get out of this system. And that’s where something like an ultra-wideband would come into play. Definitely a more expensive system, but it’s significantly more robust and flexible, which allows a company to, let’s say, install one time, if properly done, right? And never change it again, right? So they don’t have to, let’s say the CEO comes in and says, hey, this isn’t working.

I want to see a new layout of the facility, you know, completed in two years. If you’ve done your RTLS properly, when you rearrange the whole plan, you shouldn’t have to go and rearrange the whole RTLS infrastructure. It’s just there.

It knows where everything is. So scanners become redundant, pinch points become redundant, all these things that required something to go to a certain place and then get identified, completely redundant. And then scale is pretty, pretty, pretty simple.

I mean, once you have like kind of like that core infrastructure for RTLS built, like how well does it scale with your company? Yeah, I find that once we put in infrastructure that people understand, right? You don’t want to put in an infrastructure and then have nobody, you know, have proper training and understanding how to use it. But once you understand how to use the system and what to use the data for, you create more of people like myself where they become continuous improvement evangelists. They see the opportunities within the data and that scales itself, right? You get people who want to get to the next level.

They want to save a certain amount of money. They want to hit a certain throughput number and they start saying, okay, you know, this group, you need to work on this. This is the data we have.

Let’s start working on this. I’ll give you more information in a couple of weeks. I’ll watch it over the next couple of weeks.

So there’s definitely a scale factor there. And the other thing to understand too is that let’s say you’ve pretty much squeezed out every bit of ROI you can get from one facility and you want to go to the next building or you want to go from this state to that state. It’s the same software, right? So all you’re doing is you’re taking the infrastructure and putting it into the next facility with all the lessons learned of the first facility.

[33:45] You already know the ROIs. You just have to plug in maybe a few different regional-based numbers and then you implement it. And then the person maybe at the top level who oversees both of those locations is still using the same software.

They’re just switching between the sites. So now they can see oversight between all of them and you can compare the data from the two and you can say, hey, this is working better here. Why isn’t it happening here? That’s awesome.

So Mitch, I want to go back to something you were talking about a little earlier with your kind of consulting approach to this technology. When a potential customer reaches out, I doubt people wake up in the morning and think, oh my goodness, I need RTLS. What are the symptoms? What are the problems that customers are coming to you with? What are those conversations like that might ultimately lead to RTLS being the solution for them? Yeah, I think the biggest, most common challenge that people are coming to us with is, and it sounds simple, but it’s very expensive, is why do I spend so much time looking for something? Right.

And when you factor in, you know, like, let’s say we had a customer come to us who, let’s say has 200 employees across the facility, right? And everybody has agreed they roughly spend about 12 minutes per shift or per day, right? Looking for things. I don’t know if you guys, you know, did the quick math on that. That’s like $400,000 a year in wasted labor.

And a 200 person facility is not that uncommon. Sure. So it’s, it’s, it’s mainly the, the search and find challenges that people are coming to us with.

And when people start looking into that, when they start reaching out, they get more information, then that kind of transitions from, okay, I’m not just searching for things anymore. We’ve solved the process control issues or the, we’ll say the search time reduction issues. Now let’s look at what else we can do with that.

And you start kind of leading people into these ideas where, you know, you have location-based events that are driving further automation within a factory, right? So material replenishment is a big one, making sure that when material gets to the line, something is triggered in the system that says, hey, it’s been delivered, right? And we don’t have to have a scanner at that location. There’s just infrastructure to know where it is. And even with going to the fully autonomous material delivery with AMRs, you’re still required to have the location data for whatever it’s moving.

[36:30] So at the end of the day, like these, these companies, the successful companies, I should say are, are starting with this, hey, I don’t know where anything is and quickly realizing, hey, this is much more than a search and find this, this, we have so many challenges around automation that this could help, help fix. Wow. Yeah.

And you know what, I love that you talked about that through the lens of like a 200 person shop, but I know for a fact that that’s a challenge in a 10 person shop, you know, just not understanding where it could be, you know, a piece of custom tooling. It could be, you know, a lot of material for, for unique job that you’re just not sure. Maybe the material came in two months ago and who knows where the heck it ended up.

[37:12] There’s all kinds of situations where there’s just wasted motion of people going around looking for things that just contributes to this overall reduction in, in throughput for the shop, because we need to take extra time to find it. So I think it, you know, maybe not something I’ve traditionally thought about for a machine shop context and yet like super applicable from, from that perspective. It’s very applicable to a machine shop environment in the sense that when, when you’re at a large scale, right, they’re, they’re looking at big, big picture, right.

[37:45] Maybe a little bit of waste here and there is not as important, but you know, I have, I have friends that have machine shops, right. There might be four or five machines in there in the facility. It’s very small.

The biggest thing that they figure out at the beginning of every year is what is the number that I have to hit at what point in the year to break even and make sure that I’m making money. Right. And they have to stay afloat.

Any minor inconvenience puts them underwater. Right. And, and especially as a small machine shop, you don’t have super high margins and you don’t have super high volumes.

Right. So, so you really have to be careful about how much wasted time you have. It’s not necessarily, Hey, you know, Joe spent X amount of minutes per day over the last six months, you know, wasting time here.

So I’ve wasted, you know, a couple thousand dollars in labor. That’s not as important to them. What they’re looking at is, okay, well, how much time did that equate to? And what was my throughput because of that? Right.

Because at the end of the day, if their throughput is not as consistent as they want it to be, that’s a huge problem. And people will go under if they’re not meeting the numbers that they plan their entire business around. It’s not as impactful, I should say, as you know, the, the multi-million dollar or billion dollar companies, they can suffer those losses.

They can, they can handle those and react to them quickly. But sometimes at a small scale like that, if you don’t know where something is and your machine is down because you’re looking for a tool or a material, it could hurt you in a big way. Absolutely.

Yeah. And it’s like, you almost see the snowball effect, right. Of like that missing tool, three people searching for it, the whole period where you have to get everything back online.

It’s just, it gets ugly. And, uh, I remember like my first foray into lean manufacturing. And that was like one of the first questions that asks you is like, imagine how much time in any given day is spent just searching for like a screwdriver, you know, or, you know, you’re looking for the boss and you just can’t find them anywhere.

[39:44] Maybe you can just throw them onto that system and just get a GPS location. There he is. Boom.

Yeah. It’s funny because you, you, you bring up people tracking, right. And it’s, it’s, it’s a controversial topic, uh, even globally.

Right. I would say that Europe and Asia are a little bit more progressive when it comes to, you know, being able to track people. And I think that you’re going to start to see it a little bit more in the U S um, there’s definitely a lot of laws around tracking people for, for different reasons.

But one thing that I would, I want to talk about is that when we think about the potential of knowing where people are, no one at the end of the day really cares if their employee, you know, where they don’t care about the location data necessarily. If their employee leaves the station and goes to the bathroom for 20 minutes, right? Like that, that’s not why they want to track people. When we talk about tracking people, the biggest thing that we’re emphasizing is what we would call connected worker, right? Being connected to the rest of the system, because when you go to your station, we know when you got there and you can get compensated accordingly, right? If you got there 15 minutes early, you don’t have to prove it to anybody.

We know you got there. If you have a close interaction with a forklift and you need evidence that someone was driving erratically, we know where you were and where that forklift was. So it’s, it’s more of a safety, uh, concern that we try to promote.

And I think one of the bigger things too, that we’re seeing is we have customers coming to us asking for evacuation assistance and emergency response systems. You know, 5, 10 years ago, we didn’t really think like this, right? It was more, hey, let’s have, you know, these mustering stations around the facility. And if we have to evacuate, this is where your mustering station is.

And then we’ll take roll call when we get out there. Well, we actually have pretty innovative customers coming to us nowadays saying, hey, I want everybody’s badges to be Bluetooth enabled. So that way I know where they’re at in the facility.

And if we have to evacuate, they know which mustering station to go to. And we do automatic roll call. And we have a dashboard that says, hey, this number of people or this specific person is still in the facility.

We need to go get them or we need to tell first responders that they’re still in there. So it’s, it’s really cool to see how people are adapting to this more on a worker level, not even necessarily on a throughput level. That’s fascinating applications.

And honestly, I think gives you a true census to like, just how, how wide this technology can expand. That’s, I would have never thought, you know. Yeah.

I mean, this is why it goes back to me saying that it’s becoming a commodity. It’s not, it’s no longer a nice to have with all the ideas that people are generating that were on the forefront of RTLS. There’s so many use cases that it’s kind of, it’s, it’s inevitably, you know, I don’t want to say not much of an ROI discussion, but it’s becoming more of a commodity, right? So you don’t have to have as much emphasis on the ROI because you know, that a couple of use cases are going to pay for itself.

[42:42] Yeah. Yeah. And I mean, I agree with you on the people monitoring thing, that it is a controversial topic and frankly, not something I’m, I’m crazy about at all, but I love kind of the point you made is that it’s not necessarily about babysitting or being big brother, but you know, it would be useful to know, let’s say you’ve got, um, you’ve got people on your shop floor.

You might want to know when and how often they’re interfacing with machines. You might want to know that for job costing reasons. So you understand the labor component of your job costing.

You might want to understand that because you’re in pursuit of lights out. And if people are having to intervene in automated processes to make them run smoothly, then you’ve clearly got some problems you have to solve on the automation front. So it’s, it is useful data, but definitely a tricky topic to do that in a way that is, is ethically sound, uh, I guess to quote, uh, also, I think, you know, for just morale, right.

[43:42] I’ll quote you, David, when we, when we have conversations about like flight tech and, uh, you know, shop, shop flow, uh, intelligence and things like that. There’s a fine line between, uh, data and surveillance. And I think more importantly, like how that’s conveyed and received by the people involved, you know, absolutely. Hey, it’s Paul from making chips. If you’ve been burned by recruiters who don’t understand manufacturing, you are not alone. That’s exactly why we created hire MFG leaders. We’re not just recruiters. We’re current and former shop owners, and we know what it takes to lead in this industry. Whether you’re hiring your next operations leader, sales manager, or production supervisor, we’ll help you find someone who actually fits.

[44:31] Learn more at makingchips.com slash hire. Okay, Mitch. Well, let’s, let’s start to wrap this up and bring it home.

You know, I think it’s, uh, I’m so glad you were on the show today and, and starting, you know, to shed some light on this topic, especially for folks who may not know a ton about it. One of the things that we always want to do when we’re wrapping up an episode of Lights Out is we want to summarize some of the low-hanging fruit, some of the actions that our listeners can take based on the content of the episode. And maybe you can help me out kind of summarizing a few of those, but one that stood out to me was gaining an understanding of how much time you or people on your shop floor are spending looking for stuff, you know, quantify what that waste is, um, and then start to think about what’s realistic in terms of a way to solve that problem.

Is it, you know, something like RTLS? It certainly could be, maybe it’s something else, but I think just understanding that amount of time spent leaving the machine, leaving the process to go find a gauge or a piece of tooling or a print or to ask a question of a supervisor, I think that’s really valuable to know. So sticking to the same theme here, being continuous improvement forward, there’s a few things that I would say. First and foremost, know your processes.

[45:53] You have to know your processes. If you don’t know your processes and you don’t have them standardized, you’re not ready for anything else. It doesn’t matter what kind of technology you put in there, you have to know your processes.

The second thing, go to what we would call GEMBA, right? That’s a lean manufacturing term, basically means go there and see it, right? So go there, watch things for yourself, understand what’s actually going on. Lastly, once you’ve seen what’s going on, and I know this is kind of basic, but do your 5S. Do your 5S so you know what good standardization looks like.

Once you’ve done those things, then you’re at a point where you want oversight across the whole facility and you can actually have a benchmark to what good looks like. So you can bring the RTLS in and you can start to scale your business and squeeze out those inefficiencies in ways you’ve never ever imagined. Yeah, I think the real low-hanging fruit there to the 5S point is when you set in order, when everything has a place, then there should be no mystery about where something is located, at least for things that are kind of permanent fixtures of the shop floor.

And so, I mean, that’s something that anyone can do and it is not a costly endeavor to do it. I know when we did it at our shop, it was a pretty big transformation. So that’s great and great points made all around there, Mitch.

Yeah, and definitely don’t underestimate when you reach out to RTLS companies that they are also consultants forward, right? Like it’s not just me and I’m happy to say that, right? It’s not just me in the industry who is a consultant forward. Make sure that even if you’re not ready for RTLS, maybe you know that you will be ready for RTLS. Don’t be afraid to talk to these companies, right? Because they’ve seen it.

They know what bad looks like. They know what bad has done to go from, you know, poorly performing to highly efficient. So use all the resources that you have to prepare yourself for RTLS.

The other thing too is don’t forget that the next best thing is still built on what we have to accomplish now, right? So everybody has been talking about Industry 4.0 for the last 15 years and now everybody’s talking about the AI transformation, which is what we’re calling Industry 5.0. You can’t go to Industry 5.0 unless you have done the requirements for Industry 4.0. That’s right. Figure out 4.0. Keep your eyes set on the foundation. RTLS provides the foundation for the data that is required to go to Industry 5.0. Awesome.

Well, on that bombshell then, Mitch, we’ll wrap up this episode. Thank you to our listeners for watching and listening. Be sure to share, like, and subscribe.

Share this episode with a colleague, with your boss, with anyone who could benefit from it. Leave us a comment. Let us know what you think about the show and how we can make it better.

Otherwise, we will turn the lights out on this episode and we’ll catch you on the next one. Mitch, thanks so much again for being on the show today. Thanks, Dave.