Michael DeMaria with Fluke Reliability

SUMMARY KEYWORDS

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Scott. Welcome to the industrial talk podcast with Scott Mackenzie. Scott is a passionate industry professional dedicated to transferring cutting edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hard hat, grab your work boots and let's go all

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Let's do this. Yeah, let's do it.

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How you doing? I'm doing great. Was it good? This is, Are you exhausted? Because you are always up on stage. You're always Mr. Center of attention,

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yeah? But there's so much energy at this event. There is. I'll be tired next week, yeah?

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But it's such a great opportunity to collaborate people. And it's like everybody's an open book. Look at a problem

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that's subject out. That's the best thing about this event, is the collaboration. Yeah, I think one of the big things that it resonated, we heard this a couple times on the stage, is how we're all learning from each other. You know, we're all in this together. Everybody has the same types of issues and problems and things. How long have

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you been in it, just in this space, just in general

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yeah, exactly, exactly. So at this event, let me just back up. Give us a little background on who you are and what you do in fluke.

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contracts, and anazema has a gazillion years of data in a data lake. And yes, it's about eleventy billion

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terabytes, 100 trillion data points.

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It's a lot. All right, you were speaking at this event, and you were up on the stage a number of times, take us through some of the topics that you were talking about.

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I think they the, you know, the theme for this event was prepare, predict and prevail. It really, we really kind of come around a long way since we we were brought into. The company, Zema, has only been in for a year and a half now. Not amazing. It seems like it's been the amount of work that I really, you know, congratulations to the teams, yeah, teams and all what they built. And it resonated so well in through the reliability lab that's back here, the Prepare side, you know, is really kind of identifying the, you know, what's needed. How do you, how do you set up the identification of what it is that you're going to do in the plant? How do you, how well you are understanding about the machinery and how you put a plan together? We also talked a bit about the alignment systems new. We did a huge alignment refresh with the technology. Did you really? Yeah, so that came out. There was a little talk about that as well. Predict is that you know how and when you know so we've got answered the what we need to do now, it's the how and when. We grab a lot of data, and so it's about making insights out of that data. How do we create actionable understanding about what needs to be done to keep your plant risk free in a priority order so the low the things that you don't need to look at the data on machines that are healthy. Why waste time having an analyst Look at that? You know? How do we prioritize our limited skilled resources that we have in a plant?

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Yeah, but doesn't it take into consideration the criticality rating of these assets too.

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We did talk about that in this event as well. So criticality, we talked a bit about the criticality assessment and what the importance is of that it steers your course of how you get into the firm identify what's most important to solve. It doesn't really change a lot on how you analyze data, but it does, Oh, you're right about that, but it does change how you approach, how you would analyze the data, right? You're not going to put a, you know, a traffic light sensor on a machine that's the most critical machine to the plant, yeah, but you would certainly on the machines that are conveyors or redundant or, you know, your small machines that you're not going to repair. Going to repair, yeah, it's going to want to know if it's at a risk, yeah. And the like, and the last leg of it was prevail. So the where and the why, how do we, how do we find that solution and get it a work order, execution? One of the things that we were talking about here, that we've again, milestones, that we've we made over the last year is the automation. So we have data that comes in automatically, you know, sensors all over the machines, automatic data capture. So removing kind of the human, expensive element of going around and walking around, collecting data, we can now do that from the majority of machines. Automate the analysis, getting insights out of it, automating how we get repair action with a priority, a plain language, what do we need to do? And now we have the automation of building a work order. So everything is automated. The automation of the work order is a huge talking point that we had here resonated really well with especially with the email crowd, right? So I have daily activities that I need to do. And from the time that you're you know, if you thought about months ago, years ago, when we've captured data, like once a once a month, yeah, you can, you can manage that pretty well. But now that we have a stream of data coming at us every day, you know, diagnostic comes out, and if you have a work order that already exists, how do I manage that every every day when new data? So if a work order exists, I want to be able to understand if something new, something's changed, if there's machine fault is now worse, or now have another fault. So that's the automation of the work order that's going to help the help the email customer.

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This is sort of in the in the weeds, a little bit typical companies that I've worked with in the past, not very mature when it comes to these work orders. So there was a big push to create work orders, sure, but then there's this backlog of, well, work orders, yeah, and and they you just, you don't get through them, because there's no way of you know what's what's a priority, what's not a priority?

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It becomes noise. It's just Yeah,

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along with all the other stuff that you're dealing with, right? Yes. How does this automation of being able to create a work order eliminate or prevent that? Or, how do you prevent it from becoming noise? Another work order, another, another thing, spin. It just tells us we're falling apart.

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Well, now, now you know, right? So if you don't, if you haven't, if you don't capture anything, you don't have any faults in the mission, in your plan. So you now have, you know what you have up against you. But you're right. We are in this world where you have to create a ticket for everything, and then, how do you manage that? Yeah, so you just put more people on, on managing. And that's not a sustainable

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solution. It's not no, yeah. So I've been there. The whole

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goal here is to be able to help plants keep organized. How do we identify you know, this is the thing that you. Really need to do this is the most important thing, and bring all that data together to be able to prove

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that out. Can Can you do that? Can you create that work order creation workflow to where it does have a tendency to say, Okay, I have my work orders here. This is my work for today. But then then a work order comes in, and it has a higher priority, and it sort of Trumps the other work orders or whatever. There's a way of being able to do that, right?

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Well, he made is super powerful in that regard. Yeah, it's the knowing that something else comes in. So it's, again, it's that daily, that daily management. What we're really kind of building currently is that ability to be able to take this, the diagnostic system, out of one automated program, and being able to do something with that in another program. Yeah, so it'll certainly help customers keep organized and knowing what what to do and when to do it. And if you, if you do it right, it's about having the right dashboards be able to present that kind of information.

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Yeah, that's that. That was a big gap in the in the work order create. All they did was just see the is a gazillion work order. Yeah, here's another piece of paper. There's another piece of paper. Yeah, exactly. And, no, that's good. I'm glad that that's the

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case. It's about though, just to kind of close that up, yeah, is we one of the I thought it was a really great presentation about justification, you know, the how do you justify the ROI? Yes, what you do? Yes, you know, so being able to have that data that you that you have, you don't necessarily approve it by how many work orders you have, how many fires you're trying to put out, but you can close the loop on it that I did solve a problem, and I can say there's a metric on there, something that would resonate up at the executive level. So taking that maintenance, you know, the activities, you know, off the plant floor, and then making it in a way that can resonate upward, you know, if you're doing a case study or the like, you know there's there's certainly work that needs to be done there. But what we're trying to do is make that in a way present, that in a way that can be done really quickly, simply and visually.

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How do we prevail? You know, there's, there's a need to be able to communicate. Well, yes, in this huge communication is the going to be the huge problem that we're going to have? I speak especially when we think about the retiring workforce that's leaving that could answer that question, because they've done that forever. Yeah, you know, I know I can prevail, because I've done this right. I can keep you remember, like an old military movies for the on the submarines, they would have one, the one non Navy person who managed the diesels, right? He could just wake up in the morning and he smells the air. Is like, I need to grease that very right, right, right? Yeah. He didn't worry about prevailing. He just did it. Yeah, yeah. Well, now we have new generation coming in. So we have a huge retiring workforce that's that's coming, yeah, a couple million coming. Yeah, we've known it's been coming for five years, but we just keep ignoring it. Yeah, I know we will fix it.

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Hopefully somebody will have a silver bullet to be able to sort of deal with

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so there's 1.9 million consultants coming in.

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20% of manufacturing jobs lost in the UK, like next year. No way retirement. Something like that. 20% there's new talent that's going to come, Gen Z will arrive, yeah. What is it the

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millennium? I have no clue. The math is too hard

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for me. You have to so they will have to learn how to prevail, because. They will be coming into roles that are going to be with a huge generational gap between the two. And so I think that's but what's what we have to think about is, how do we build technology that allows them to understand how to answer that question?

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How do you see now you bring up a great point. This was an aha moment. And I, you know, everybody talks about and specifically around, how do we backfill? What do we? What do we do? Do we, you know, upskill people, whatever, whatever the strategies and the words that are coming out of at that time. The reality is, is that I think that if you do not, if you do not invest in the innovation and in the technology and the latest and greatest, you're not going, you're not going to attract anybody that has any ability to be able to sustain you. Oh, absolutely, yeah. I just think it's critical whether you fight it or not. I think you just need to do it.

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Oh, absolutely. You can't, you can't, not. It's going to come whether you like it or not, exactly right. So the AI is here, how do you how do you embrace it? Yeah, that's, that's exactly correct. I think what's important there is that the new generation of workers are the ones that have been born with technology in their hand. Yep. So you have to cater to that group, and they think that way. There's a they will tell you that way, very directly,

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exactly.

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It's not a bad thing. But I was talking, there was a lot of conversations I'd had about this over lunches and coffees and beers. Is there is a wall between those two generations, the there's a pain point that the workers have gone like I've said this SKF guy that came on mocking me in a nice way. I really appreciated it. 37 years in a plant and losing a screwdriver, but he had a lot of and same have had a lot of pain points that we've learned from. Well, the new generation doesn't have that. They're, I think they're, they're more we had Nolan here, who is talking on behalf of the new generation coming in. And they don't have the same level of understanding. They don't have this mindset of working in the same plant for years and years and years and growing and learning from it. Yeah, they'll have to trust the new the older generation to teach them. When I got into this, I had that luxury of the older generation at that time would take you as a protege. They would teach you. They had the time, oh yeah, and they were encouraged to do so, yeah. Hey, look, I've been doing this for 30 years. Let me show you how I do it with a lot of pride. Think about how stretched thin your workers are in the plant today. They don't have the time, the luxury to be able to say, Come here, come here, young, come

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here, old. Let me. Let me, yes, take you under my wing.

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And then there was, um, there's a kind of a same aha moment about the question of why every everything came to the why? Why? Why do you do it this way? Why do I need to do it this way? Why can't we do it a different way? And there's a, there's a disconnect between the retiring workforce and the new workforce, yeah, and there's a fear of the AI displacing the retiring workforce earlier than they want to retire. So I want to hold on to my knowledge. I don't want to, yeah, yeah, yeah. But the newer generation that comes in, as I said, you know, has this need to have more technology, more capabilities, so I think the responsibility is back onto the manufacturing plant, just to embrace that. How can I build smart manufacturer in a way that allows you to trust the data that you have understand the reason why we do things to begin with in a technological way that the new generation would say, Hey, I love this.

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I think, I think we're missing out. And I think, to your point, I think you brought it up, we do a horrible job at communicating. We just do, yes, we need to do a better job of communicating and being able to communicate that that that bright future that leverages technology for the, you know, the betterment of the business and the community and whatever might be. And I think we need to do that. I think

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that's where industrial 5.0 really comes back into place, yeah, where we bring the humans back into it. For was all about digitalization. Now we have this data now we've and we've kind of figuring out what to do all with this data. But now that's good point 5.0 now brings in the humans to say, Great. Now, how do we use this in a way that bridges that generational gap?

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Yeah, I, I that's a whole nother conversation, because I can't believe we're talking about industry 5.0 but we are, because we we. We've recognized the necessity for all of us to get together as some humans, to be able to sort of take it to the next level. Let's do it. Michael, how do they get a hold

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of you? Are you Fluke liability?

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That's where I'm at. Are you out on LinkedIn?

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I am certainly on LinkedIn, somewhere on LinkedIn.

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