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SUMMARY KEYWORDS

Industrial talk, asset management, predictive maintenance, condition-based monitoring, AI integration, human intelligence, data analysis, reliability partner, vibration monitoring, temperature monitoring, subscription-based service, ROI, plant floor efficiency, automation, industrial renaissance.

00:00

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 right

00:21

once again. Welcome to industrial talk. Thank you very much for joining the number one industrial related podcast in the universe that celebrates industry professionals all around the world. You're bold, brave, you dare greatly, you innovate, you collaborate. You are solving problems each and every day. You are the heroes in the story. That's why we celebrate you. You ought to just take it to the bank. I am such a cheerleader for you be successful. That's what I want to do. I'm pointing at the video, so don't, don't even worry about that. And we are broadcasting here on at SMRP. This is in Fort Worth Texas, Texas, and it's been a great conference. We're on the last day, and I've had a gazillion conversations all around. How do we manage assets? How do we do reliability? How do we maintain our operations? It's been incredible. You need to put this on your calendar because it is something that you need to attend. You need to and as you can tell, I'm sporting a cap. Acid watches on my on my noggin, right there. And we have two from acid watch and and one's name is Bill and the other one's name is Greg. I don't have their last names, but it doesn't really matter. We'll just get cracking and they'll tell us what their last name is. All right, you guys having a good conference. Yeah. See how I threw that first question out there. I didn't direct it is, all of a sudden going on, do I answer?

01:43

It's been a great conference, seeing a lot of great customers of ours, and then also, you know, having great conversations around, you know, some potential customers, and you know, areas we might be able to help them out.

01:53

Yeah, absolutely. CMS, that's what you guys are. What was that switch? What is see, yeah, I'm sorry. See how I I'm already going down the road of I'm violating everything just one second. Yeah, see, I the sad part about is I prepped them and I didn't, I didn't see I'm prepped them. Okay, Greg, no, no, no. Give us a background, okay,

02:24

the short story, yeah, Greg Raglin is my name. Very much, been all over the place. A guy once said, life's what happens when you have other plans. And that's very much the reality for me and my career started out early, right out of college. I went to school for psychology, but actually got into the logistics field as a broker for many years, learned a lot about different industries and got excited about that, and from there, got into fluid motion control, automation based products for a different company. And then, lo and behold, three years ago, I got the opportunity to work here at AssetWatch one of the solutions architects here. So hello, it fancy way of saying that I help customers solve problems in the ways that makes sense for them.

03:07

So see that. See now the cadence is right, Bill, tell us a little bit about you.

03:12

Yeah, sure. So Bill Broderick, been with ask watch a little bit over a year now, been in the predictive maintenance space for about three to four years. But my whole background has been in manufacturing automation. So I was a key ins corporation, you know, big company in automation, been walking plant floors for well over a decade, helping find optimized processes, figure out ways to automate things. Really honestly got into it when I was younger.

03:36

And what like, you're like, you're an old, Salty Dog.

03:41

For 10 years? Yeah, you like it? No, it's about like, finding inefficiencies, right? Like, I just think I've always wanted to, like, be I like in general, just general life, like, what's the easiest and the fastest way to get things done the right way? And, you know, I think manufacturing right? That's what we're always looking for and striving to do, is, how do we just as efficient as possible? And cost, you know, save costs where we can. And I'm kind of passionate about that, right? Just kind of helping companies get to that point and get to where they need to be and want to be.

04:07

But it is pretty cool to go out on manufacturing floors and see what they do. Oh, absolutely,

04:12

it's and it changes. You know, every couple years you see new equipment, new automation, new robotics, new, you know, whatever.

04:17

Just, it's cool stuff, right? I Yeah. I digress. I was helping start a sugar refinery, right? And so we built a new sugar refinery. We're commissioning it. But what I learned about sugar, it's just Yes, sure, and I would share that with my family, and they'd like, gotcha, no, you don't understand. You don't understand that sugar is, like, the

04:42

whole thing, yeah, all right,

04:45

Greg, give us a little sort of 411 on AssetWatch how I'm sort of butchered it.

04:50

It's all good. It's all good. I think more than anything, AssetWatch is a reliability partner, right? I think you hit the nail on the head about human connections, people and that's the lifeblood of you know. What we do, obviously, out of the box, we're a predictive solution for all things, condition based monitoring, right? Where you think about triaxial vibration, temperature, all these things are cool. But you know, for us, we understand that companies don't need more data, right? They need the right data the right time to be able to make actionable decisions. So you know, here at AssetWatch, we use and leverage data and AI machine learning, but behind that is the human intelligence, right? People that have walked floors for several years. We have a staff of 30 plus dedicated engineers that write and see that data, write recommendations and tell you not only what's going wrong, right, but how do we fix it? So that's, that's us in a nutshell.

05:44

Bill, is it safe to say that I have these devices out on these assets, these devices are pulling all this data, and it's data, data, data, tsunami of data, and you're taking it into your platform, and you're saying, Yeah, it's good, good, good. Up there's a problem. Give it, hand it over to a human being, and then they make the determination, yeah.

06:09

07:40

You got street cred, exactly. That's exactly.

07:44

It means a lot in the world of industry.

07:46

Yeah, absolutely.

07:48

Acid watch Greg. Is it? Are there any limitations from what type of data? So you've got thermography, you've got vibration, you have ultras. Is there any sort of limitations from the platform be able to analyze specific data?

08:07

You know, a quote stands out to me that says, when you try to be everything to everybody, you become nothing to nobody, right? So what I think limitations, I think where we're at, at its core is, let's catch the low hanging fruit. So condition based monitoring. There's so many things you can monitor, right? But vibration and temperature is our core. We have an end to end lubrication program. We also do have some things that are coming. I don't know if I could speak out really about these innovations, but the goal here is, right, to be a one stop shop, right? No one wants to work in three, four or five different systems, but if we can catch things using data, using these analytics, from different sources, right? We can, you know, really try to reduce unplanned downtime. So I'm not sure what our limitations are. So far, the ceiling is hot.

08:52

Well, it's still bill it's still sort of,

08:56

how long is acid watchman around? So about 10 years now, 11 years we've been collecting data. This has

09:00

been transformed. Let's just, let's just lay it out there with the with the advent of AI, it's just sort of changed your business model in a dramatic way. Yeah, you know. And now, is it safe to say, Bill, that there, there are people that have these devices around here. It's not just a device, an IoT type of device, but other devices that that I can upload into acid watching. How did, how do you wrestle with that? Because many of these devices also have sort of this AI platform as well.

09:35

Yeah, so we hear that quite a bit, too, and to be honest, so we're more on the integration side. We would integrate with something else, like a CMS system. So you take our recommendations, push it through. You can the data is yours. You can use it however you want, with a historian. What we're really focused on is times of value and proving predictive maintenance works quickly to get the buy in with the plants right. And then we are like Gregor sanction week, we are looking at three different modalities to bring in so. Are integrating other types of thermo, whatever it may be, into our platform. So it's a one stop shop. Right now, if you were what we would basically do is we would actually take our data and send it to some other form of, you know, maybe like a one window, one pane of glass, type situation that you want to work out of. But right now, what we're looking at is triaxial vibration data, temperature data from from this sensor here. This is actually, yeah, so it's a small like salt pepper shaker, and that that's pulling data. They're dynamic. You can set schedules and things like that.

10:33

So you just opened up a can of worms. You? Are you manufacturing data? Manufacturing devices now?

10:42

Well, yeah, it's ours. I think it's another thing that kind of sets us apart,

10:47

is we only got the device.

10:48

It's ours, right? All of our technicians, all of our engineers, all of our solutions architects, are right here. So is our product. It's right, right here, stateside. So we definitely pride ourselves.

11:00

How many products do you have? Well, you got, you got that

11:05

product is the tip. It's beer, really, really two, two main core products, right? This thing right here is like Bill said, right, capturing real time data for vibration and temperature, all baked in one. Right there? Yes, sir, right there. Huh, you can take one thing that's really cool, right when we talk about human intelligence. So obviously, we're capturing data at a set schedule, depending on your process. We got, you know, some food manufacturers that are batch driven, but we're giving you live data. But as you're walking the plant floor, you know Joe that's been at the plant for 20 years, can walk past a compressor and notice something sounds off. Joe can pull up the app, hit a button on his phone, get a full spectrum reading, pick up the phone, call an engineer and say, hey, something sounds off. What are you seeing in the data? And that's the change, right? I think that that's the connective tissue between where AI and all these technologies want to be in the actual utility of people that you know walk plant floors for several years so,

12:02

and to add to that too, what's important for us is really about, it's at the end of the day, we're not trying to just provide sensors everywhere, right? Yeah, that can be overwhelming. Yeah, that's that. Yeah, absolutely. So what's we focus on is when we work with, like, a potential customer, you know, we do these trials with them, but we help build out what is the right assets to monitor with continuous but then we also have, like a route based type solution where, basically it's similar. It's like a four pack of these sensors, and these are your maybe your tier two, tier three. We don't need to be continuously monitoring, but we might want to check it once a month, once a quarter. It can all live in our platform, and you have it kind of broken out by criticality. And at that point, an operator can just take these around, put it on the machine, maybe once a month, and take a reading. And then our people, the AI, will analyze it as well as our people, but at different price points, right? So that's one of the purposes. Is really what we look to drive is like ROI, what is actually necessary to monitor continuously, what it's worth paying for, and then what is, you know, things that we can maybe just swap out pretty quickly. We just want to keep an eye on it once a month. Once a month. And what we do is we build out what is the right program for each facility, right? We're not looking to just provide a ton of sensors, because for us, we are subscription based service. So if we're not holding up to our end of the bargain, a bargain of providing constant over year over year, ROI, then you remove us, right? So if we put sensors on everything, that's when, you know, you get into a world of like, okay, this just gets very expensive now. And now you're looking at it like, it's not really cost effective. And you know, when we look to the company, it's all about focusing on, what are the things that are going to take you down, what's going to hurt your production process? What are the lead times

13:37

on these? It's the asset, criticality,

13:39

exactly. Criticality that's

13:41

more important, that pumps more important than that pump and there's there's logic behind it, there's a there's analytics behind it. It makes complete sense. Build the there are probably 12 CMS is around here on this floor, agnostic to the CMS. Can you connect

14:02

so we don't, yeah, so we can be standalone, but we obviously are. You don't

14:06

want that. You don't want somebody having to go into another system. Don't, don't, don't, don't come to me and say that

14:14

we but we were actually partners with a lot of them from the CMS, so we actually integrate the so what would happen is, like we would put out a prescriptive recommendation, type in on what we found, and then what your next steps need to be. And that would actually get pushed through the CMS. You can live in your CMS, work order gets created, and then they close it out through the CMS. That would then update our system, letting us know that the work bi directionally, exactly, so we have both, yeah, exactly, and we that's the goal, right? Is what we typically do is prove that the technology works First, like even during a trial period, make sure the plant is bought in, that they're seeing their their life is changing now, because now they're not chasing tires, right? They're actually being more efficient with their time, yeah. And then we do these integrations, and that's really where we start maximizing, really maximizing the use of predictive maintenance alongside of C. On this.

15:00

Craig, do you? Do you take your clients, hold them by the hand, and then deploy these devices and say, this is the right way to do it. I look at this pump. It's not just slapping it someplace. There's some there's some thought process behind it. Absolutely. If it was me, it would be slapping it anyway.

15:19

Yeah, we actually made it. We have a full blown, what we call a RT team, right? S that reliability technicians, that their sole job is to walk plant floors and lead the charge in terms of install, all we need is an escort, right? Typical installation for us is about six hours, and I keep saying the word partner, right? And I think that again, the less that you have to do in terms of managing a program or some data or some sensors, the easier, more effective it'll be. So when I say that, we come in, we do the installation, we're on site two to three times a year, making sure that not only does the hardware work, but do we need some new training?

15:55

So training, well, I haven't even touched on that. What do you guys get?

16:01

Too far ahead of ourselves, basically trading within our platform, right? Okay, leveraging what we're using. Can it effectively make change? Right? Change management is everything.

16:11

So it is. My spider senses went off. I was like, because it's especially in this, in this world that we live in today, I just find that being able to be well, competent, yeah, and being able to have that training and and and be current, it's everything from my perspective,

16:36

for sure. Yeah, we try. One thing that's super important for us when we're looking at, you know, customers is like, when we try we track engagement, right? How quickly are they responding to these alerts? What are they doing with them? Because at the end of the day, we don't want to put a project on your plate. We'll do that. We'll manage that. We'll make sure so if they don't respond to an alert, or whatever it may be, we're going to reach out via phone call, via text, via email. There's multiple different methods. We're making sure that you're taking action on this, and that's where we kind of come in from that change management portion and really help drive the success. Because again, being it's a subscription, it's like, if you're not using it, you're not going to use it next year, right? So the whole purpose of what we're driving with that human element behind the AI is the support is critical to the success of the program. And the goal for you to have a successful predictive maintenance program, you need support. And every company is different. You have mature companies. You have companies who are not mature. And everyone needs, needs are different at the plant level. So we partner you with the right engineer on our side to make sure that they, most of them, come from that industry of some sort. So again, it's really that, like, driving the engagement. It's not something where it's dropped off to you guys, and hopefully you can figure this out. We know that what it requires is a huge team on our side to support you

17:46

see, this is interesting, because I've been having these conversations over the years about and then there was that big drive for IoT. So IoT and these are devices, and I remember having these companies, they sit on the asset and they pull data you don't have. That's amazing. And then, and then, and then the conversation sort of evolved in and then we collect the data, we send it to the cloud. No way you're sending it to the cloud, and now it's just ubiquitous. It doesn't make any sense. We got a device. We stick it out there. It just does it. And now we're, we're at a point where, if you're not doing something like this, well, you're, you're at a competitive disadvantage. Absolutely not a doubt. Yeah, okay, future hat. Future hat. This goes to you, Greg, and to you really will. But what? Sorry Greg, say I'm not just throwing it out there. Yeah, I was getting ready. I was getting ready. I said, catch yourself, Scott, don't do that. Future hat. What do you see? It going future hat. Your future like, what do you see the future captain in here,

18:54

the future is wide open, right? Yeah, talking about AI, right? You can't even open an app for Uber without seeing a suggestion from Ai. But I think what's happening it is right? So I think for us, it's like the ceiling is very high in terms of new technology change and working with partners, integrators, yeah, but I think what's, what's coming for us is a big explosion, right? With, you know, new industries that we're serving every single day. We actually doubled in size right over the last two years. So it's phenomenal.

19:26

I think it's a renaissance. It is. It is industrial Renaissance, for sure. Bill, what do you think?

19:32

I couldn't agree anymore, and really for us, what we're looking at is being like we're what we are taking is our, you know, our customers are guiding us right, like they're they also have needs. They have other technology that's a good one. All we're doing is listening to them at this point and seeing, you know, if they're having this issue that maybe we can't solve today, but let's talk about how we want to solve it. They're not the only ones. These other ones, other customers are probably having similar ones. So what we're looking as we're listening to, like you mentioned, some different types of technologies, ultrasonic. There's a lot of different ways out there. There's a ton. Yeah, and is to really start bringing those technologies into our platform as well and become a one stop shop for reliability, not just, you know, IoT or predictive maintenance.

20:10

Love it, yeah. Okay, Greg, how do people get a hold of you? If they're saying, I want to talk to

20:15

you, give me a ring. Give me my cell phone. No no, no no. Give me. Give me a LinkedIn.

20:20

LinkedIn, first name, last name, Greg Raglin, R, A, G, l, I N. Check us out on asset. Watch, asset, watch comm.

20:27

Season Five. Bill, how do people get a hold of same way? Bill Broderick on LinkedIn, calm. And then also ask the watch, reach out. I'm one of the directors there, so please reach

20:36

out here, here, here's the lazy part of me. I get to go into LinkedIn, find you connect. I want to connect with you. Grab the URL, stick it in my website. That's the lazy part of me, and that's appreciate that. And then anybody can go out there and look at your stack card, because that's what they do. You know, they're gonna find you on LinkedIn. You know, it's just what it is. All right, you guys were absolutely wonderful. Thank you very much for joining industrial talk. Thank talk. Thank you for your continued support. We are broadcasting on site. SMRP is the event, and you get people like Bill and Greg that are just absolutely fantastic, and you get to connect with them, and you get to have conversations. That means something. We're going to wrap it up on the other side. Stay tuned. We will be right back.

21:22

You're listening to the industrial talk Podcast Network.

21:31

Yeah, that was SMRP. As you can tell you were listening to it. It is a must attend event. You're in asset management, reliability maintenance and everything else. Yeah, you need to be there. It is a great event. Great people. They're all focused on your success, just like Bill and Greg AssetWatch and you know, the right there at the fundamentals, data, collecting that data, making it real, understanding what that data means to your operations, and just continue to just strive for greater insights you need to, because you need to be more efficient, and it's, it resides in data. All right. Again, industrial talk is here for you. You need to tell your story. You industrial professionals, reach out to me. Industrial talk.com. Let's tell your story. It's so important. We've got a couple of new podcasts out there. Be looking for it. All right. Be bold, be brave. Derek, greatly hang out with Craig and Bill. Change the world. We have another great conversation shortly. So stay tuned.