43. Before You Buy Another Spindle, Use the Ones You Have

[0:01] Dave, everything’s yellow and black and everyone’s wearing the same yellow and black shoes. Where the heck are we? Nick, we’re at the Zoeller Technology Days and Smart Manufacturing Summit here in beautiful Ann Arbor, Michigan. And you’re right, there’s a lot of yellow going on and some pretty impressive looking tool management equipment behind us. Yeah, super exciting. This is like where you wanna tie it all together and run a smart tool room. You’re in the right place. Absolutely. Also for anyone who wants to know how to get a brand totally dialed in, they’ve nailed it. This entire building looks like it’s tied together. And Rita, who invited us to do this, is kind of leading the charge on the marketing side. She’s a brilliant woman. All you gotta do is spend a half hour with her and you’re gonna be like, wow, that’s what an elite marketing director looks like. Rita is incredible and I’m just hoping that we can figure out how to get our hands on a pair of those shoes. I talked to the photographer who was taking photos here. She says she’s been trying for six years. So if you get a pair, I’m gonna steal them. Ha ha ha. Ha ha ha. Dude, we have, speaking of elite people, we have another guest here. Would you mind introducing him? Yeah, absolutely. So we’re lucky today to have with us Walt Swetton, Senior Manager of Advanced Manufacturing at Eaton.

[1:23] Walt, thank you so much for joining us. Thank you very much. Appreciate being here. Thanks, guys. And let’s just be honest, we started this whole thing and got to about this point and then Nick realized that we turned the camera on but we didn’t turn the microphones on. So Walt, you’re gonna have to introduce yourself twice and tell us for the second time in the last five minutes. I guess it’s a good thing I like to talk. Yeah. Ha ha ha. My team would pick on me if they heard this right now. Like, yeah, he never shuts up. Not everyone gets a re-do. He tells us all the same stories twice. No, no, and you don’t get a re-do and that’s great. Yeah, tell us how you got involved in what we call the Metalworking Nation and kind of your origin story. Yeah, sure. So family background, machine shop, third generation machinist. Swetton Tool and Dye was founded by my father back in 1950. So I had a lot of opportunities machining, manufacturing growing up. Didn’t make a difference, it was milling, tarring but our specialty was actually wire electrical discharge machining. So if you have a old ad for an NTMA from 1982, you’ll probably find myself and my little sister holding parts that we manufactured on our JPEX wire EDM. It was actually for the Lawrence Livermore Green Laser. Wow. So at the time we had the biggest wire EDM in North America.

[2:38] So it was kind of a specialty. And my brothers today still have a shop north of Syracuse. They specialize in wire EDM. Yeah, but I was able to go in a much different path around opportunities, really around because of, you know, the unfortunate events in 2001. But it really opened up a lot of opportunities for me in aerospace. I immediately went to a shop and really cut my teeth on learning how to machine high temperature alloys. Yeah, EDM is like the magic. Like, how is this even real? Every time I see it, it’s like, how does that work? It’s amazing. It’s so cool what you can do with EDM. EDM is fantastic, both sinker and wire. It’s just, it’s gonna leave its own. Yeah, yeah, for sure. That’s kind of where your roots are, kind of shop floor, cutting your teeth, making parts. Talk to us a little more about kind of what came next and how you ended up, you know, where you are today in aerospace, but also industry 4.0 and smart shop technology. So obviously, you know, with manufacturing being a passion of mine, there’s, it’s a blend of finding out, you know, manufacturing process, but how to optimize it, a lot around continuous improvement. And with that is data. How do you get data available? You know, I’ve been with Eaton not quite three years now. Previously, I was with the Raytheon Technology Groups of businesses over 15 years in many different roles. And it’s just data is where it’s at, right? If you don’t have the data, you’re behind and, or you’re, you know, trying to optimize your shop floor, but you’ve already lost that time. It’s all guesswork if you’re not operating off a real hard data. Yeah.

[4:05] So when you were kind of like, you’re finding yourself on your journey to where you’re at today, was it like always whoever your boss was saying, hey, can you start capturing data? Or were you pushing that and into the organization? Because it was a belief that Walt had that, hey, we don’t have enough data. We’re not making enough insightful decisions. Yeah, I think no one really pushed that. I just, I think naturally, I guess my stint as a quality engineer and really trying to drive, you know, process capability studies and data there is, you know, very hard statistic driven. Really understanding how that data capture went to, you know, whether you’re using Minitab, you knew data was really driving process improvements. And as we see the machine tools change and evolve, there’s a wealth of data that we can tap into that just makes massive improvements to us. And it’s right there in front of you, but how do you tap into it? How do you apply it? That’s the secret sauce. You know, one of the things that struck me, Walt, and we were speaking on the phone earlier was this idea of problem first thinking, you know, really identifying that problem before we set about trying to use technology and data to come up with a solution. Would you say that kind of role in quality kind of helps you think through it from that perspective? Yeah, I think that just around the data perspective, but really the problem solving in the case of we want to tap into that data, we have to have the right problem we’re looking to solve because we also have to fund the connectivity, right? So you can’t just suddenly, I mean, sure, you can do it in maybe a single use case, but then to replicate it for another area, there is an infrastructure you have to plan and design, and especially with a bigger company like Eaton, for example, it’s, there’s all around the newer, or I should say it’s been around for a while, but the cybersecurity compliance, right? CMMC is a huge thing if you’ve got a defense or Department of War contract and it’s there.

[5:58] I mean, it’s been pushed off for years, but it’s there. And I think smaller shops will have a much easier time being compliant. Big companies like us with, you know, I think we got over 40 some odd plants now after the recent acquisition of Altair PCS, it’s, we’ve got a lot out there. So how do we structure that? How do we do that mindfully with the CAPEX we have? Yeah, isn’t there supposed to be some big update with CMMC coming like this November where everything is going to get tightened? Yeah, I think it’s tightened the contract. I think we have to be level two. I am honestly not as hands-on in that. We have a whole team at Eaton Corporation that really drives that, but we have a wonderful leads on the aerospace side that handle that. There’s a good report on that we’re progressing very well. Good. It’s, it comes to data. So when you look at infrastructure, you have multiple layers of data, right? And we can kind of get into it, but people just think data is data. And really it comes back to the original question of, you know, what’s the problem you’re trying to solve? The first and foremost problem is, are we actually getting the most out of our CNCs? You know, spindles are expensive. Yeah. Without the data, you really can’t verify the use of your equipment. So really driving into that is the, I guess, the cornerstone of funding our infrastructure, OT infrastructure investment, is really looking at that opportunity.

[7:20] And we’re already seeing great gains from it. And it’s now we’ve kind of, and I’ll talk about it tomorrow in my keynote, is just really looking at what that strategy was, getting a good opportunity to showcase it, look at the robustness of the infrastructure, and then looking at rolling out. So we’ll have, I think we call it OT 2.0 in Eaton. We’ve got, I think, 15 sites in aerospace now, and then we’re kind of following up with the actual dropping network cables, connectivity to the machines, where we’re connecting a fair amount of equipment, key equipment. You know, I think we’ll have over 150 by the end of the year. And you can do the math. I mean, if you’re spending, you know, 100,000, 500,000 on each CNC, you’re now monitoring that and you’re knowing, you know how well you’re getting that machine used. Yeah, yeah. I love what you were saying, Dave, about like problem first thinking, because you come to a place like this, you walk in the showroom, you see all this incredible technology and you hear what it can do. And you’re just like, yeah, I want it. I mean, it’s like a kid in a candy store. Who doesn’t? Look at that stuff. Of course we want that stuff. But, you know, anyone in, unless it’s like your family business and you own it and you get to just buy whatever you think is cool, you’re gonna have to justify why you’re making the investments that you’re making towards like a smart shop or a smart factory. And I think that’s what’s so interesting about your story is you’re utilizing a lot of this technology here, but you’re utilizing it to solve a problem.

[8:47] And I’m sure you’ve built ROI case studies. Yeah, there’s some ROI case studies that we did. And obviously we talked between cost avoidance and cost out, right? Yeah. Cost avoidance is the cost hasn’t occurred yet. So it’s a little harder there because you haven’t spent the money. Cost out is true dollars and cents that’s in your P&L. So our finance organization loves that. And we’ve really tried to prove that. So our first big implementation for a plant in Maryland was just to start connecting their CNCs and looking at base utilization. So specifically with OEE, looking at each of the components, right? You’re looking at availability, performance, and quality. People get wrapped up in each individual one or not know how they work, or you chase the wrong thing. And with that, you end up with the same OEE. The big ones I see people and cutting tools and machinery is, oh, I gotta improve my performance. What’s my cycle time? I really gotta do that. Actually, in my opinion, that is the last one you go after. I mean, the first and foremost, the first one you go after is quality, right? Because anything you have to redo or remanufacture, you’re just immediately sucking up 2X of your capacity. Totally. Oh, I love what you’re saying right now. Again, put my quality hat back on, quality engineer, quality manager, love quality. But that’s true. If you’re making any kind of scrap or rework, man, you’re sucking the shop bad.

[10:11] The other side of it then is availability. And availability is kind of a slippery slope because it really depends on your machine tool. You can’t compare a horizontal machining center with a pallet system to a regular three-axis vertical, right? Because if you try to put the same expectation that that vertical is gonna run at 90% uptime, it’s not going to because usually the doors have to open. You’re moving parts, you’re changing this. Especially with a three-axis where you’re not likely to do everything in one setup. Right, not one setup. You might have multiple fixtures. You’re rolling parts through fixtures. It’s a little old school, but some of the tolerances you have to hold or how you’re keeping some of the datums still that way is efficient. And obviously, as machines gotten better, you can’t invest in the million dollar DMG more yet for the mill turns, that’s what you got. So looking at availability is really key for us to drive because most people overestimate how much they’re actually using their machines. Right. And looking at just straight part count doesn’t tell the whole story. And where do you think, I’m just thinking of kind of the smaller shops out there that might be paying attention to this for the first time. I mean, what’s the low hanging fruit when you’re starting to look at utilization and downtime reasons and all that kind of stuff? What should the initial objectives be? I guess the initial objective is to look at doing everything you can before buying another spindle.

[11:40] Right. Usually job shops think that changeovers are costly. And yeah, if you’re an individual, one person, you’re coming out of your pole barn, whatever it may be. Sure, you can’t, that machine has to be running. You’re gonna need another spindle, right? You’re flip-flopping your changeovers. But once you start getting a team, then you’re just looking at, do I really need to add another spindle? Do I need to spend another 150K, 200K? Am I really getting the most out of the spindle? And the answer is probably not yet. Right. And that’s where you talk about the ecosystem for Zoeller, right? So I’m only talking about one component, but that’s why I’m here and that’s why we’re partnered with Zoellers. While we have had, I think we’ve got over 25 Zoellers across our various plants and different models. Okay. But it was always seen as a presetter, right? So bringing that vision of saying, there’s a full ecosystem that you can layer on top of and be a true smart factory, that is eye-opening because I think that’s a very understated area in machining. Yeah, I love where this is headed and what it takes to actually run a smart factory because so much of the smart factory stuff is like ethereal, out of reach for the average job shop or average family-owned machine shop or whatever it is. And it’s like cool to see and people talk about it at IMTS and things like that, but how often can you really achieve that? And I like that we started with the problem first approach and then, okay, what’s the core metric here with OEE? And you’re talking about the elements of OEE that are kind of maybe prioritized wrong, in your opinion, and you brought up availability. So often people think, okay, well, I’m running seven out of eight hours, my availability’s great. There’s 24 hours in a day.

[13:25] To your point about machine tools, like if you’re not anywhere near 24 hours, if you’re not running at all unattended, if you don’t have the standardization and predictability to be able to walk away and not be a doorman who opens and closes his door all day, then you’ve got way bigger fish to fry before you’re trying to buy more million-dollar equipment. So it’s really finding that path, because it’s great to see all these small shops, a lot of Gen-C folks finally getting back into the trade and, yeah, going and buying an inexpensive mini-mill from Haas or something like that, or a robo-drill from Fennec. It’s great that they’re doing that, and there’s just gonna come a point where they’re gonna have to make the next purchase, but they gotta make sure they got the money. So it’s kind of that prove-out, but then the next step is, how do I make sure that spindle is turning? It’s cutting chips and making money. So that’s where we’re really at, I think, with all of us. And now, floor space, right? Floor space is always a concern. So some of our plants have got many, many machines. We can’t add another machine. So, yet, our growth for Eaton Aerospace is really at record proportions. Our next five years are gonna be awesome. It’s gonna be a lot of work, but the growth, and if you look at our electrical side, even crazier. What do you think is driving that, primarily? Really, what’s driving that is the different platforms.

[14:48] It’s great to see the, I guess, finally recovered from COVID, right? So I would say, last year, most companies into this year have crested over where they were in 2019. So really coming out of the, we’re hanging on for dear life to be profitable, all of the disruptions in supply chain, or raw materials, whatever it may be, and then, obviously, people are traveling, and it’s good to see that. So as that wheel keeps turning, we’re now going to see more platforms. We have, I mean, on the military, we have the new MV75 platform that’s come out. It’s replacing the V22 for vertical lift. And then we’re gonna see some next-gen single aisles come from Airbus and Boeing, right? So in 2030s, it’s gonna just keep going. And it’s both defense-type aerospace and commercial aerospace. Both commercial, yeah. I mean, look at the, you just look at the run rates that Airbus is getting, and Boeing’s recovering on their output, and we’ve got content everywhere. So very fortunate as a company that our content is on all these different platforms. And then with people flying, you’ve got the aftermarket as well. Yeah, I thought you were gonna say, oh, of course it’s defense, and that’s what we hear is booming all the time, but it’s cool to see that commercial’s strong, too. Yeah, it’s a blend. Commercial is strong, at least in my opinion. Commercial is stronger, and it’s driving our business, and it’s driving our aftermarket, whether you’re getting the repairs for Delta or United, whoever it may be that’s using these planes, that all feeds into machining components.

[16:17] You can’t spell high-end without DN. If you’re serious about taking your shop to the next level, it might be time to stop thinking in terms of good enough and start thinking in terms of capability, flexibility, and my favorite, automation. DN Solutions is helping manufacturers move into true high-end machining with their SMX multitasking series, the DVF 5-axis machines, and advanced automation solutions designed for shops that wanna run smarter, faster, and more competitively. The SMX platform gives you the ability to combine multiple operations into one setup, reducing handling, improving accuracy, and helping you get complex parts out the door faster. Their DVF 5-axis lineup delivers the precision, rigidity, and confidence manufacturers need for today’s demanding aerospace, medical, and high-performance applications. And when you pair those machines with automation, you’re not just buying equipment, you’re building a more scalable business. High-end parts, high-end capability, high-end thinking. Because you can’t spell high-end without DN. Learn more at dnsolutions.com. Were there any particular moves you made at Eaton kind of in this mission to kind of find unrealized capacity that kind of surprised you in terms of what it was able to unlock, just in terms of maybe certain data points you started to measure that were really revealing or anything along those lines? Or was it more of a snowball effect of just kind of incremental improvements? Really, I knew that was there, and I’ll step back to my experience.

[17:59] Collins Aerospace was the last company within the Raytheon Technologies after acquisitions. I did a lot with Digital Factory in my role there and kind of knew and tapping into all this factory analytics that we could get in data tags. Worked with a great IT team there and really could see that come forward. But the problem was, this is five, six years ago now, the understanding of how to record that information, because obviously storage is a big problem. So there was a lot of design work there and understanding that. Yeah, and you could see that data come forward. So when I knew, and with my machining experience, when you walk a shop floor, you’re like, there’s a lot of red lights out there. I mean, just by looking at the red lights, but did you have the data to really make the case? Why were they red? What was the reason? And that’s where the first question, and I’ve been pushing really what I call three levels of OE, and level one is, is it running or not running? And any small shop out there can get all sorts of the tools that are out there that are very inexpensive to just look at and answer the question, is it running or not running? And I have straight data, 24 seven, and saying, yep, this is how much I’m utilizing my spindle. And that’s just the first part of availability. Availability has other components that make it complex, that truly calculate in real time and constantly. But just taking a snapshot and just say, utilization, 24 hours, hey, I’m only cutting eight hours of the day. Then it really starts, you can do the five why analysis, right? Why? And then you start looking, oh, it’s because I didn’t have this tool, or I didn’t have this material.

[19:36] So then you can start tracking on how you can do your root cause and corrective actions for that to eliminate those issues. So you said level one is just kind of on or not on. You know, what percentage of the 24 hour day is my machine running? Take us into level two. Level two is actually where the operator gets involved. So we’re really starting to expand and use Ignition, an ignition based platform. And we have partnered with Flexware and we use their Spark MES, specifically their OEE application. So that now the operator is able to give feedback. So the machine stopped and now the operator within the way we have the interface, within about 15 seconds, they can give a reason for that. You know, it could be, oh, yep, I’m going to break or I’m changing tools, doing a setup, right? So now you have more data, contexts of why the machine is down. So then you get your Pareto charts, again, all about providing data to continuous improvement and really having that tie in to our continuous improvement team. So really take that and go to the next step. So first step is just percentage of time the machine is running.

[20:51] Second step is starting to give reasons and context to why it’s not running, where the operator is not participating in it. Is there a third step? Ah, third step, that’s all of the advanced data tags in the machine. And that’s where it gets complex because of the OT infrastructure is required. But as you probably, if you’re familiar, you know, MT Connect has been around for quite some time. Fanuc Focus has been around for quite some time. And if you look at the iterations of those, look at the data that’s starting to be available. It’s been quite some time now, but MT Connect, you could pull the tags and completely reverse engineering what’s happening in the machine tool. And actually have a full virtual setup right next to the machine of what’s happening. And that’s just scratching the surface because now you’ve got all of your load meters, what are your axes seeing, you know, your spindle load, obviously, is they’re all around, you know, cutting tool performance. You’re starting to tap into all of these other use cases that just can go so many different ways, but solve the bigger fish first. And because if you get really one track mind to try to just solve that one problem, you’re gonna spend a lot of money and you might not get the absolute return that you were thinking it was going to. I mean, if you’re a high volume automotive shop, yeah, maybe, right? Because you’re doing such high volume, but in aerospace, we’re ultra low volume, ultra high mix.

[22:14] Yeah, yeah. And I think that’s like, you know, you could tell which companies have the big marketing budgets and at the trade shows and stuff, you got like your cutting tool companies and it’s all about cycle time improvement and everything like that. And then I think about what really kills the availability or the utilization is like setups and not running like, oh, I only have enough staff for one shift. Like that’s where all your gains are gonna come from. I would say the vast majority of shops out there, not that you don’t wanna try to push the pace and, you know, improve cycle times. And that gets into some of the stuff that you’re doing a lot, Dave, is like where we get the load monitoring with slide tech and, you know, pushing the pace and optimizing how the program is executed based on, you know, some of the cutting loads and things like that. But let’s move in to the second level of OEE and talk a little bit about the, you know, performance and that kind of middle variable. So we’ll start with you, Walt. How detailed are you guys? I think it’s fun for the average shop to listen to what like elite, you know, Eaton level companies are doing. What kind of data are you looking at when it comes to the actual performance and the cycle time and the cut? You know, for the cut, a lot of the cases is pretty manual right now, right? So we’re trying to optimize tools or testing tools and seeing where that, we have to have very repetitive performance and we have to be very careful of how much stress we’re putting into the material. So if you’re machining Inco 718, for example, your tool starts to wear, sure, it could keep cutting, but you’re inducing stress. And when you go later to stress relieve it or do some sort of cycles prior to assembly, it can spring back and then therefore cause a lot of non-conformances.

[24:02] So you gotta be very mindful of that narrow space to make sure that, yeah, you’re changing your process. It might have impact that you might not see down the line. Yeah. So it’s not just about running faster or harder. Correct. And then some materials are very stable and you can go, I mean, you can run aluminum and everyone likes to run machine 6160-T6, right? It’s like, oh yeah, no problem. It’s a lot different. It’s like, how fast can my spindle go? Is it balanced properly? But for us, I think with our stainlesses and our Incos, it’s pretty hard. Aluminum’s like the straightaway of the race course where you’re just flooring it. But the big thing is not just the performance and we try to match performance. Yeah, if you can get a couple more cycles, those tools are expensive. So that’s really where coming back to cost out, like, yeah, we spent this much on this cutting tool. I go to this one, it’s the same price. I can get X amount more cycles. There you go. There’s my savings. So therefore using the data to provide that and validating say off a spindle load, for example, we’re not heavily into, and I know there are a lot of aerospace companies that do, and we will explore that more in some cases at some of our shops, but real-time adjustment of speeds and feeds, again, just because it’s variable and we don’t know the outcomes of that. So we try to be very careful with some of our more sensitive parts.

[25:21] Sure. That’s actually super good feedback for, you know, something that does make real-time adjustments with speeds and feeds, because usually it’s like, oh, if you can optimize what’s in the cut, like let’s push it, but- Well, you got to define what optimizing really means and it doesn’t automatically mean faster. Yeah. Right? And you really have to be thinking about the entire process to your point, Walt. It might have an unintended consequence like just inducing stress into the part in a way that you weren’t before. And now all of a sudden, you’ve got a host of quality problems that are, yeah, costing you production and you’re causing all kinds of scrap and rework. And anyone who’s machined didn’t know where, you know, you measure in a constrained state or in a free state, you know, it’s why is it measuring different on the CMM that it did inside my machine tool? Yeah. Well, you unclamped it, right? Yeah. That’s why, you know, and you have to say, is that really, is that part of the quality? Is that really the issue? And in a lot of conversations with the design engineers is like, oh yeah, that will flex and that’s fine, you know, or yeah, we need to specifically call out this needs to be measured in a constrained state. So, Walt, you know, I want to kind of take this conversation to a place where maybe, you know, a lot of our audience might be thinking about, you know, they’ve got some budget, they got some CapEx. They want to make some investments in their own business to just improve the performance of their business, improve their throughput, improve their machine utilization. There’s tons of ways that you can spend money in this industry.

[26:48] I mean, we’ve got a whole showroom behind us here of really, really beautiful technology, but how would you advise a smaller shop to start thinking about that? Because I really feel like, you know, having good data is really just this foundational piece to process improvement that needs to be there. Is that where you would start with investing in a business or are there other things people should be looking at doing? I realize it’s a bit of a loaded question. It’s a little bit, again, depends on the equipment you have. Sure. You know, I’ll use the vertical machining center example. You know, yeah, setups are one thing, but the one product that Zoeller has is pre-setters, right? And their infrastructure with the tool management system, TMS, how do you actually manage your tooling? How can you eliminate downtime, bringing the tools already built for the operator so that they’re actually changing them back? Because most verticals now have changers in the back that you can load in. You can use their Z code, right? And be able to pass over all your offsets directly. Like this is all stuff that normally the machine is stopped, the doors are open, someone’s typing in the offset, the decomp, right? And unfortunately people make mistakes. Machine crashes happen.

[28:04] That’s just more downtime. So- They put in a positive offset instead of a negative offset. Or, you know, you purposely set your Z plane down minus one and suddenly someone put in 10 inches and you just ran it right into the table. And it’s like, okay, can I have 25 grand to fix my spindle? Yeah. That’s really where it is. And then, you know, CapEx conversation is, what’s the next step? You know, try to get there. If you’ve got the work, try to find it how you can move to the next step to get a spindle that can run. Like I said, for a horizontal go 90% or greater, right? So that way you have that ability to load it and that spindle just keeps going. And now it’s just all a matter of maintaining how you load your pallets or your tombstones. And then obviously having the infrastructure for your tooling support. Everyone thinks about material flow. Do I have my raw material? Can I make the part? Do I have the steel? Very often they skip the cutting tools. And it’s almost shocking when it goes, oh yeah, we don’t have that cutter. It’s like, what do you mean you don’t have that cutter? You knew you were gonna cut this part for three months now. And it’s like, oh yeah, well, we lost track of it. But not having the right tool management strategy, it can just cripple you. So, and I even see it in some of the shops that I’ve been around for many years. It’s just like, they lose track or they lose count.

[29:25] They don’t have right there. But, you know, we think about parts that we’re shipping to customers. We have ERP systems there, but on the flip side, we don’t do the same thing for our cutting tools, inserts and mills, whatever it may be. And you suddenly don’t have that form cutter you need to put that profile in and you’re dead in the water. And you have to call up a customer and say, yeah, we’re gonna be two months late cause I gotta wait eight weeks to get a cutting tool. Yeah, I was gonna say, you find out there’s only one of those form tools left and it’s in Japan and needs to be shipped over. In some cases, you know, when you get into aerospace, there’s so many different specialty cutters that, you know, the lead time on that is extensive or you’re going to a special grindhouse that makes that for you. All right, shop owners, listen up here. I think all of us know we are in one of the most in capital intensive businesses there is and margins are tight and we’re always fighting issues. And then when we make money, what do we do with it? Stock market’s up and down all over the place. Well, I get asked a lot about where can I invest my money? I’m a firm believer as business owners, you’ve gotta invest in yourself first. You need to reinvest capital into yourself. So the number one thing that I’ve done in this industry investing was ProShop ERP. We’ve been using ProShop since 2018 and my payback literally was within weeks. With their per user based pricing, I knew when I made the decision, I only needed to save my workers roughly one hour per month.

[30:54] We saw within the first week, we were saving multiple hours per day. That type of ROI just doesn’t come along very often. Outside of that, the real value has been able to quickly implement best practices across my entire shop from the time we get an order to the time we ship it. Scaling my business with confidence, being able to go out and know that I can deliver on my promise to deliver quality parts to my customer and then gaining insights into every job, employee, machine and every process in our business to really drive efficiency and look for opportunities for improvement. That’s where the real value in your business drives. So visit ProShopERP.com, book a demo and start realizing ROI today. That’s ProShopERP.com. I like what you said earlier, Dave, when you were like, well, where do you start? And you almost implied like we’ll start with getting real data. And I think that is one of the more foundational steps is like if you wanna do CapEx planning and you have no idea where you’re at with OEE or utilization or whatever, data is important. But I think often the way most shops invest is because they got a job that required more than what they had before they took the PO.

[32:12] So like, that’s what I see is, oh gosh, we got this huge job coming in and I wanna be able to deliver it all from my shop and not have to outsource some of the PO or whatever. So I’m gonna buy more equipment. And then you just keep accumulating equipment. But what happens is you forget sometimes to like go and get the data and get real truth or your metrics. You’re just layering more equipment on top of bad processes. Yeah. Yes, right. Because you keep getting work. So you’re like, oh, I need more equipment. I need more equipment. But you never solve these. You’re just not nearly as efficient or profitable as you could be. It’s like, you know, there’s the saying you can’t teach an old dog new tricks. Well, if you have a shop that’s like gotten bigger and bigger and bigger, it’s hard to teach an old shop new tricks and good insight and good. But even the new shops, right? They’re, like I said, the Gen Zs that’s coming out and learning machining for the first time and they know there’s a market out there. Yeah, they’re really focusing on learning machining, the process, right? And they’re very fortunate today. There are so many options to get low cost solutions that can provide that data for you. Yeah. And there’s a whole slew. And sometimes it’s baked into, you know, you know, your DNC system, right? You wanna start instead of using a thumb drive or back in the day, floppy disks to transfer your programs to your machine from your cam system, you need a DNC system. So, you know, we are very heavily invested in Simcoe, for example.

[33:32] Well, Simcoe has a very basic product. It’s basically included. So if you connected it for your DNC, away you go, you can get that same data and it’s very inexpensive. And any small shop that is just looking at like, this is way too much. I’m like, no, it’s not. It literally is a flip of a switch and you have a whole shop layout and you can tell if a machine’s running or not running. Yeah, base level machine monitoring. We talk about it. It’s something we offer. So yeah. It’s a dime a dozen. You can find it anywhere. It’s what you do with that and how it gets more advanced. That’s where like the rubber meets the road and you can do some really cool stuff. But you can do so much with just basic monitoring. Yeah. That, like I said, I’m paying for our infrastructure based off of just that. Yeah, it’s so good. And it’s so great that, and what the biggest portion is, is now we can not lose the hours in the day. So we know that, yeah, now after 10 minutes, notifications are sent out, right? We don’t expect this machine to be down. Someone’s there helping the operator and say, what do you need? Is there something wrong? And then just when you, oh yeah, we don’t have this tool or these wrenches aren’t here. That’s where you get all that problem solving and you try to really address it. And sometimes the operator is just struggling trying to make parts, inspect parts, whatever it may be, that asking for help directly is delayed. And you might not find out until tomorrow and the operator is like, yeah, it a rough day, blah, blah, blah.

[34:53] But that was eight hours or, you know, maybe it’s only four hours of their shift that they lost because they were struggling. One thing my older brother taught, he’s like our lean guy, you know, he’s our president and CEO. And he always talks about, you know, you set a target and then you define your current state. And a lot of people want to skip over the define the current state. Like we’re here right now. We know where we’re at. But it’s like, do you really know where you’re at? Do you really know exactly where you’re at? And you reminded me of that, Walt, when you were talking about like, well, we don’t have the tools. And Al Whatmull, our buddy, who’s the CEO of Toolpath, he always says, he calls it the clean your garage problem. Because if you want to do any sort of like AI cam automation that we know is coming and you don’t know like your own tool library and you’ve got like some tool recommendation features that are getting more and more popular and that technology is evolving, but you don’t even know what you have in your shop. None of that works. And so much of this technology that you see and kind of the future focus smart shop technology doesn’t really work unless you have a really solid foundation and understanding of your current state and where you’re at right now. And back to like the whole, one of the foundational steps is get the data. But let’s go back to Zoeller for a second because you made the point where you were talking about like, hey, they’re not just presetters. You know, it’s this whole ecosystem. And I imagine your experience with them started at more of a foundational level and kept evolving.

[36:20] Do you want to kind of walk us through that evolution a little bit? Yeah, sure. I mean, obviously, presetter is big. Anyone who’s in machining, instead of touching your tools off, I mean, you used to, you know, do it to the table to a part and piece of paper and go old school, right? Or then they finally got Renishaws. But anything that was in the machine, that was lost time, right? So with presetters and there was many different options or solutions out there, Zoeller was always very consistent and probably one of the most accurate out there and still are. I think they’ve constantly led the industry on that. Really where it partnered with me is more as I got into a side business, you know, 20 years ago of doing tool cutter grinding and really seeing where they were the absolute leader in that space. So as I had a few anchors and doing regrinding for small shops in upstate New York, it was kind of, you know, really great to see how they led the industry for that. So that’s where I really became familiar with Zoeller and then just seeing how they have grown. I know Alexander kind of presented, you know, all of the lines of code they developed. Like you wouldn’t think of a tool presetter company would be generating millions and millions of line of code. Right, so it’s great. Yeah, and they have 60 different products and the wealth in which they’re seeing their ecosystem grow and how that will transform shops is unbelievable.

[37:36] It’s amazing. Yeah, it’s so exciting. Dave, we talked to, I’m blanking on the guy’s name, but we talked to one of the leaders of service earlier. Oh, Felix. Felix, yeah. Yeah, Felix, good guy. I think I asked him like, so would you say you’re 50% software, 50% hardware and actual, you know, physical equipment? And he’s like, yeah, that’s probably fair. And to your point, like that’s where everybody’s headed. It seems like most of the kind of tech driven brands, the innovative brands that you would see at an IMTS are adding more of a digital element to their value proposition and what they’re offering to their customers. Yeah, and if you look exactly what Zoeller did with TMS and setting out how their tool management system is set up, DMR, right, these kind of presented and the order of things there, that’s the lifeblood of your cutting tools. The presetter just becomes something that provides the information now to the overall system. Obviously it needs to be extremely accurate and repeatable and they have different products depending on your price point or what you’re trying to drive. So like a Smile 420 that’s in here, right? That’s probably what most, you know, most small shops could use, right? But it’s a big step up to go to the Venturon over there where it’s got the auto clamping. So this is where some of the conversations that I’m working with my plants was we’ve got lots of those smiles, right? But it’s, again, treating it all as a presetter. It’s like, no, I want this now, the Venturon to be our mainstay.

[39:02] Why? You saw it. They’re showing on how that platform is going to be the basis for all of the automation going forward. So it’s got the full auto measure cycles in it. It’s got the mechanical replaceable clamping, right? It’s not manual clamping and everything they’re doing in their core lines, whether it’s the Fanuc robots delivering in is all off of that platform. So a little bit more of an investment upfront. Now we’re a bigger company, but we know if I’ve got a shop that’s got 50, 60 machines, guess what? It’s going to pay for itself. It might not be tomorrow, but I’ve now have this and I have to come back and re-justify another tool presetter. I have that as the basis along with we’re building out TMS, right? So it’s really great to see that, but no, am I going to have their automated systems yet? No, but that’s where I want to go. That’s awesome. And kudos to Zoeller for building not just the equipment, but the software that allows you to scale without having to manage all these different integrations because you have a patchwork of equipment and software solutions trying to get you, guys like you who do that advanced OE analysis, what you need. Imagine like your IT team’s headache of trying to patchwork all this stuff together if it was a little bit from this brand, but this software, but then this software, and then this brand, and then forget it. You know, and obviously we talk a lot about machine time.

[40:26] I mean, you got to think about all your manufacturing engineers time, right? So TMS is huge as you link it to Mastercam, for example, if Mastercam is your cam choice, they got a great integration with that. Now you’re running off of one catalog of tools. You just go into shops, every ME had their own catalog of tools. And then when they do their tooling sheets and things, it’s all a different process. With TMS linked directly to also VeriCut for verification, it’s just makes it all streamlined. And now your ME’s utilization goes up significantly. Yeah, it’s interesting like how impactful like standardized tool data is to the whole process. I used to work in the AI cam business, and that was one of the biggest hurdles to adoption is that ultimately, if you have an AI powered cam programming solution, it needs to know what it has for inputs, what tools are available to use. And the reality is most shops do not have their tools standardized and digitized. They just don’t. And so ultimately, they can’t make good use of that technology then. So it’s this whole idea of getting your house in order to take advantage of some of the automation and process improvement is such an important aspect.

[41:43] And I think that kind of brings us into kind of part of the conversation. We talked about data capture being super important, getting operator feedback from the floor into your monitoring and your data collection. Can you speak to kind of the human element in terms of managing this change? You know, technology is just, it’s changing how work it’s done on the shop floor. Have you at Eaton or your past experience run into just a resistance to that from operators and how is that managed? I’ve seen resistance at all levels, to be quite honest. I get it, it’s new, the change management’s real. The biggest thing is demonstrating that you’re there to make someone’s day better, right? That it’s truly there to make their job easier, right? It’s not to take away or to punish and those things where, yes, unfortunately, people use that information in a negative manner and that’s where you get that. But ultimately, if you can make an operator’s job that much easier, like suddenly, yeah, they don’t have the tools and you come back in and here’s a new tool cart, full shadow board, all of your things there. Wow, I don’t have to go roaming around for an hour looking for some wrench, right? I don’t have this T6 to change my inserts. It’s that type of stuff where they’re very appreciative and that’s where you get the buy-in.

[42:59] But on the flip side, other levels, you get managers that, oh, I know how to run my shop, I don’t need that telling me that. And it’s just, I get it, yes, there is a secret sauce of knowing a shop floor and monitor it, but you can only be better if you have the data and only optimize your time. Now you’re not chasing problems that you thought you had, you now have concrete information to say, yeah, we’re gonna do the root cause analysis over here and see what that true problem is and I don’t have to chase this, this, and this. So it’s also a training thing because I think we’re so, the skill set that most people have is all around, like I said, the machining process. The MEs, manufacturing engineers of years past, they’re all worried about how I make chips, what’s my speeds and feeds, what’s my tool path. The MEs of the future, it’s gonna be data. You gotta know the process, you gotta have that core, but now it’s how do I use the data to optimize my process? So it’s a very blend of an industrial engineer is part of that and it’s just, I mean, you gotta know your machine tool. That machine tool has all that data in there, you’ve gotta know that machine inside and out. I like that you brought it back to people, Dave, and you talked about root cause analysis a minute ago, Walt, like you’ll start to get root cause analysis of what kind of people you have by who embraces and is part of those that are championing this data collection and I’ve always noticed, even I lead a sales and marketing team, but the people who care about what’s in the CRM and want to know what’s in the CRM and want to log their calls and take notes and they want to tell you how much they accomplished that week and tell you what’s in their deal pipeline and everything like that, that’s our data, right? And those that are chasing after the data are always the best people on my team.

[44:51] And those that are kind of like, ah, we don’t need that, I’ve never had to do any of that, I was able to sell just fine without it and they kind of avoid that, that’s always where you start to wonder like what’s really behind the curtain here? Are you giving it your full effort? And I think you see that in the shop too. People who are like, yeah, I want to know how we keep score on our business performance. I want to know what great looks like. And when you keep score, you’re more inclined to pursue excellence and you’re more inclined to want to improve what the data is showing. And I think you see that in people too as we talk about so much of the science and the nuts and bolts and the machines themselves, but you see that in the people. The people who love data and the people who try to capture data and improve data are the people who are going to make a big difference. Yeah, and I think a lot of those people with the data and solving those problems, it frees them up to use their minds on more complex problems. Like they can start to think beyond instead of chasing a wrench, hey, I noticed that we could do this and this better because we’re getting this waste here and someone didn’t see it, right? So they start becoming the problem solvers. We want to give them every tool possible to solve their own problems.

[46:09] And that’s really, I mean, you look at how from a CI perspective, you hear probably about tier meetings, right? We don’t want to escalate problems. We want it to be solved at the level and give them the information and the tools to do that. Now, finding the right size of information, they’re not going to really care about what we’re shipping that week. They want to know about what’s happening with the machine, right? So there’s finding that flight level to give them information to fix their own problems and really enable that. Yeah, I think that’s such a good point. You’re creating a theme we continually bring up on this podcast, you know, technology lifts people up ultimately. And I don’t think any of us have been replaced because of industry 4.0 clearly, right? It’s just helped us do a better job. It’s interesting, you know, there’s a lot of talk around AI as well. You know, we’re putting people out of work and there’s a lot of resistance and fear. And reality is, if you look at even just the, you know, the machine shop business over the last 30 years and all the technological changes, no one’s out of a job. You know, the job has changed, sure. But- It’s still scary though. It’s still scary for people because that’s what they know, right? The status quo, they’re not understanding. And AI is a very interesting conversation. It’s obviously so talked about everywhere now.

[47:27] And obviously my electrical side of the business in Eaton, right? We’re massively invested in that in data centers, right? So AI is creeping in and should be used on the shop floor. But again, AI will only return the data that you have. So if you don’t understand your data that’s going in, what kind of information is AI gonna give you back? It’s not gonna be actionable information, but can you actually leverage that to really use AI to be that much more effective? Most definitely. And when I talk about level three for OEE, right, connectivity is all the events data tags that you get from MT Connect or Fanuc Focus and now plumbing it. So we’ve partnered with Palantir and now have two sites that are using Palantir’s product and we’ve customized a little bit for our frontline leads that it’s giving them real-time AI analysis from the machines. And if we have operator contacts as well, that provides it in. So it gives them a whole dialogue where everyone’s just like, oh yeah, chat, GPD, no problem. Yeah, well that’s pulling everything out of the internet. On the shop floor, it’s what data do you actually have, right, and it’s in many, many factors less, right? Infinitely less.

[48:46] So that way you start building that catalog of data tags for it to pull from. And that’s what I’m excited about and really see as we progress. And then again, coming back to Zoeller’s product, it’s more data that you’re gonna feed into all that. When you’re getting that from the machine tool, it’s gonna feed to your tool usage, how you’re actually controlling that, identifying problems before they happen. So being predictive. And there’s so much you can go from asset monitoring, of course, but it’s just, it’s exciting. It’s a very exciting time. Yeah. Yeah, for sure. Again, back to the clean your garage problem that Al talks about, and you talked about, hey, no one gets replaced. Well, the people who get replaced are those that don’t do the foundational stuff to get good data. They just refuse to evolve. They refuse to do what it takes to have a shop that’s future ready, at least within our organization. If there were people who were resistant to like, okay, let’s get everything digitized. Let’s get everything set up. Let’s build the kind of like basis understanding so that, because otherwise you’re putting a ceiling on what’s possible as you scale. Because if you don’t have it organized, if you don’t have a dependable like kind of structure underneath you, then you can forget about doing any of the higher tech stuff. It’s the same conversation many years ago when automation really came in, right? People like automation, it’s gonna replace everybody.

[50:07] No, it just changed your job, right? It changed that your core competency was still the same. It’s just trying to help you be more effective. Yeah. Again, it’s really on the company that’s doing this, right? Where you say people lose their jobs or whatever, but it’s really on, as leadership positions, it’s on us to help transform the workforce because that’s what we need, absolute. Like no matter what it’s gonna be, the workforce is gonna be key to everything. So be a leader and transform your workforce to be able to embrace that change and not be terrified of it because everyone’s, you know, will come through and say, oh, there’s gonna be a layoff because of automation or AI. No, there shouldn’t be that. And if you’re driving that type of mentality, you’re gonna run out of talent. And when you run out of talent, your competitors are gonna fly by you. Mm-hmm. That’s so good. 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. This half-day program is built specifically for shop professionals like us who want practical ideas that they can actually take back to the floor. You’ll hear how other shops are reducing operational costs, improving output, applying AI in shop-ready ways, and implementing automation where it makes sense.

[51:37] Plus, you’ll get a detailed industry outlook and the chance to connect with other job shop leaders who are solving the same problems you are. 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. So with that, Walt, you know, I’d be curious, based on your role right now with Eaton, when you look into the future, what are the things that are on your mind right now as you’re kind of planning and strategizing for the next few years? I know you were talking on the phone about, you know, there’s a lot of forecasted growth, which is really exciting. So talk us through that, what’s on your mind today? I guess, you know, like I said, I’m really trying to embrace the opportunity, this growth potential that we have, and it’s really seeing in bookings and it’s just going further. And Eaton’s a great company and seeing where we go with our product lines and making very key acquisitions. So it’s great to be part of the leadership team and really shape that. So what I’m most excited about is really transforming our manufacturing engineering organization and really bringing that sense of community. Obviously, getting into larger companies can be, as I said, you know, come from the Raytheon technology world, there’s a lot of acquisitions and changes there. So you have some disjointed plants out there that might feel out there on island.

[52:57] So how do you connect that? How do you leverage that workforce, that knowledge that could ultimately bring a major improvement for another site? How do you connect them? How do you upskill, right? How do you really look at what you have for talent and bring it forward? So, and yes, there’s opportunities from a cutting tool perspective and saying, oh, we could really, really transform this shop. They’re running older pieces of equipment. If we could do this, this, and this, wow, and we put this type of mill turn machine in and wow, we could truly go lights out, right? And what does that look like? And that is exciting in a different way. So as I, myself growing up in manufacturing, I can get overly excited about it and my team picks on me because I just will go with things and I’m just like, guys, we can go so far with it. And I have to remember, we have to take small bites. And that’s where, you know, coming back to is making sure you know what that next bite’s gonna be. Are you gonna choke on the whole thing? Yeah, no, that’s so good. And I think that’s kind of the theme, you know, do the stuff now so that when you’re nerding out and dreaming about the future and you’re so excited about it, that’s actually possible. But if you make mistakes early on and you don’t kind of do some of the foundational stuff, then you’ll have to go back and refix it. And it’s a lot harder to do than just kind of like, like if you’re a five-person shop right now, there’s a lot of things that you can do to set you up for success. So you can take advantage of some of this smart factory stuff. Trying to do it, like kind of break bad habits is a nightmare compared to just like, oh, we’ve scaled strategically from the beginning.

[54:29] Yeah, and I love going to every plant, listening to every manufacturing engineering manager, ME, quality engineer, listen to their stories and what they’ve experienced over the years. Because with companies like ours, people are around 15, 20, 30, and there are people even 40 years of tremendous amount of experience and knowledge. And being able to incorporate that into the next improvement is really great. One plant I’m working with a one ME manager, he’s probably been around 30 years, I think. And he’s just like, he’s like, this is invigorating. I can’t wait. And it’s like, and we can see where we want to completely transform this whole plant. That’s very heavily into machining. And it’s just like, we can see it. Now, how are we going to figure out to get there the next five years? And it’s just like, and it starts with, yep, we’re going to bring in the next thing for technology, train the workforce and understand how the process will work with that, make sure verify and then build from there. But that’s all, that’s one thing, but it’s going to stem off 30 different things we need to actually go off and improve our workforce. Yeah, I always say to myself and like anyone who’s like me, who’s kind of a future focused thinker, you got to be where your feet are. And like, just take that next step. Mine are in the clouds, but yeah. Exactly.

[55:45] So speaking of where our feet are here at the Zoller event, the Technology Days event, you said you’re giving a talk tomorrow as we kind of close. Do you want to like foreshadow what you’re going to be talking about a little bit? Yeah, sure. I’ll be talking about, you know, some of the connectivity strategy that we’ve kind of really built off, you know, fortunately leading the I4O team now, it’s kind of been able to execute my strategy of saying, hey, we need to show value with connectivity. We talk about Industry 4.0 at Eaton, it has many different variables to it, where they might talk about specific technologies, but for me, it’s data. And that’s where I’ve kind of made it the, like I said, the cornerstone for what we’re going to do, because you can’t do computer vision systems or anything like that past data if you don’t have the right infrastructure. So at least getting that in place is there. And that’s what I’ll be talking about is like, yep, this is where our strategy is, where we’re going through, worrying about compliance, partnering with the IT team to really make sure you got your T’s crossed, your I’s dotted and have the right things to build out where you want to go the next five, even 10 years, right? Obviously things will change, but if you start the right way, you’ll be able to transition that. But, you know, even finding in our shops where we have to update our network switches or getting network cables dropped to machine tools, it’s just not thought of. So it’s like, okay, well, there’s a cost incurred with that.

[57:06] Okay, this is the problem we’re trying to solve and this is where we’re going. But once you have that, we did one plant, now they’re like, oh, wait, we can connect all of our quality equipment now. We have the right OT infrastructure where for years, the answer was no, because it’s a cyber concern, right? So it’s now it’s like, oh, great. Now SPC is totally going to be transformed in that plant because now all their air gauging, for example, can get connected. It just opens up with that. But from that initial investment, it just spawns off to so many different things that you can’t keep track of the amount of value. It’s really, I guess, it’s always about the highway, right? If you can pay the highway, it’s not about, you gotta pay for the highway, but everything that the traffic goes through it is going to be tenfold. And it’s just trying to get to that point, that critical mass. And it’s really excited to see that really starting to come fruition in the aerospace. Yeah. It’s such an optimistic outlook for the future. I really love it. Yeah, same here. And it’s fun. I mean, a lot of our guests are smaller shops and not quite as mature in their industry 4.0 journey as what you guys are doing. So it’s always really cool to kind of plant the seeds in the heads of our audience, like what’s possible in the future and what a big company like Eaton’s doing. And every small company could do it. I know it’s being there in a small machine shop, it’s hard as you’re trying to just meet customer commitments.

[58:29] If you’re a job shop, you’re worried about your changeovers, in some cases you’re birding the midnight oil, right? You’re working all hours to make that delivery. There’s plenty of inexpensive tools out there that can at least start giving you that information. So as you look at your CapEx, just maybe, hey, maybe I can just do something like this and just monitor uptime, downtime. Yeah. And just see what that gets. Does it show you something that you didn’t know? Yeah. And then, like I said, even if it’s more effective in how you spend on your next machine, I think it probably more than paid for itself. That’s awesome. So Walt, are you active on LinkedIn or anything like that? How can people reach you? Yeah, I’m active on LinkedIn. Now you can find me pretty easily there. Becoming more and more of a presence as my leadership role has changed within Eaton, which is great. I got to do a post. Like I said, I was in one plant last week with the Palantir team and my team, as well as our IT organization, kind of getting them set up. So I still have to do a post and looking forward to sharing all of this with everyone as well. Well, thank you so much for sharing all of this with me. And Dave, you’re always so good at closing us up. So why don’t you wrap this up with us? Yeah, sure. Well, a big thanks, Walt, for being on the show. I can really just tell you have such a heart for the industry and for the people in it. So thanks for being here with us today. And thank you so much to our listeners for also tuning into this episode.

[59:45] Don’t forget to subscribe, share, comment, and listen to Lights Out. And make sure you follow Walt on LinkedIn. And be sure to check out Zoller as well. And if you didn’t make it out to this year’s event, maybe put it on the calendar for next year. All right. Thanks very much, everybody. Let’s turn the lights out on this episode. ♪ You can get a taste of what it is ♪ ♪ Oh, oh, oh, oh, oh, oh, oh, oh, oh, oh, oh, oh, oh ♪