Ankush Malhotra with Fluke Reliability

SUMMARY KEYWORDS

talk, customers, data, ai, industrial, fluke, aAAzima, work, false alarms, Xcelerate, solve, conversation, tech, assets, absolutely, world, expertise, scott, early warning signal

00:04

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 get by right

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01:11

I'm doing great, Scott. So good to see you. So

01:14

good to be seen.

01:15

I gotta tell you, thank you for being here.

01:18

Oh, absolutely. I love it, man. Everybody's so nice. Why is it because of you?

01:24

I think it's the weather outside.

01:25

If it's nice. You got it. That is nice. No doubt about it.

01:30

Nobody can see it. But I can I have a view of this sunny day outside in Florida with the golf course. Yeah. Yeah. It's great time to be here.

01:38

I have a hallway. But no, you're absolutely right. And it's great venue. I I know it's brand new. Well, I can't say brand new. I don't know. It's new, but it feels

01:50

it feels new. Yeah, I think I think he has a fun story. The Yeah, that was even though it's new. Yeah. Machines break. Yeah. There was an issue in one of the conference rooms back there. Yeah, so the tech came in. And of course, he had a bag of Fluke tools. You go, yeah.

02:07

Look, every time I talk about fluke, I say it's the gold. It's that Fluke color. You know, what if you know what the Fluke is? You know what it is? The yellow? Yeah, yes, that's right. Is it? It's not gold? It's yellow, gold? Yellow. Yeah, yeah. Correction, it's not gold. It's me bad eyes. Anyway, before we get into the conversation, let's level set. First off, are you having a good meeting. So this is awesome.

02:33

This is this is, you know, we call it the best week of the year for us, we get an opportunity to get 300 of our customers all under one roof for a few days. You know, so much to learn from them so much to to understand their workflows, see all the all the challenges they have, and in a small way, where we can help them really make that leap and the journey to being more more predictive or proactive in how they do their reliability work from reactive. And I think we've had a fantastic day and a half and another day and a half to go. See

03:07

I I'm always fascinated when I come to this event, I'm always fascinated by because of the the representation of who comes here. They're the ones that these are the individuals that work in your system, you know, they are just trying to make the operations more efficient. They're trying to use the tools that are necessary to make that happen. And then coming together here at this event, being able to share that and say, Hey, we would like to see this or this worked out, well. We used it this way. And it was great, whatever it might be, I think that that's just an absolutely wonderful thing.

03:44

And a number of our tracks are actually led by our customers. See, because we think there's so much, you know, so much great work some so many of our customers are doing, and we want them to teach or share or have others learn from what they're doing and where they are in that journey. And really, you know, create that network, right? We're all trying to solve difficult problems. It takes a village.

04:04

Yeah. And, again, I always get around collaboration, I just think that the market has changed so rapidly. And there's so much innovation going on and some technologies, that the only way that I could keep up is that you, you work with individuals, you you collaborate with individuals, and you come up with and you you Xcelerate that learning because that's the only way you're going to be able to keep up. Yeah,

04:26

that's Xcelerate.

04:31

04:49

Yeah, so maybe maybe the best way to think about this is like break it down into what's happening in the market. Yeah. And what what you know, how are we as a business trying to address that? Yeah, first To follow I mean, Scott, you and I spoke about this a year ago, you know, industry 4.0 A lot of trends around automation and things. Wow, one year, one year could well has changed. You know, I remember a year ago talking about AI with some of our customers, and they'd brushed me aside. Yeah, we're not ready for this. And here we are a year from now, everybody, everybody is trying to see how do they get a piece of the action? And when I say action, they're really trying to say, what experiments can we do? So we can get started leveraging the tech to really help us do their jobs better? At the end of the day, it's all about how do I drive more efficiency? How do I drive more safety? How do I drive more productivity, acid, acid longevity, and really using the tax, I think that's the biggest change is really the attack over the last year. And it's putting us at an inflection point, our challenges have gone up, right, all the challenges about, and we'll talk a little bit about all the challenges there more to do. But because of the tech, and it's giving us this real opportunity to leverage the tech to really solve for them and create those, turn those challenges into opportunities. I think that's probably, you know, all of a sudden, like, wow, what are we talking about 4.0 Is passe. It's 5.0, these advanced technologies and how you can

06:15

leave it's five Dotto. I can't I can't believe in four, four dot odas is not, it's not done, you know, what I was always concerned about with IoT, or IoT, or whatever, that term, it was also just evolving into sort of this miscellaneous file. And it was just, you know, yeah, let's throw this technology in. And let's do this, let's though that whatever it might be, and then it sort of lost its clarity. But then a year, you have that switch of chat, GPT. And then all of a sudden, it just blew everything up. And then they recognize that. So you had a couple of you've had an acquisition in the world of Yeah, so So talk to us. Yeah.

06:56

09:00

It what's an interesting sort of twist to it, I know that there are a lot of companies that are out there saying I want AI I want AI to do certain things. And I want I want to just sort of throw data into it, and it spits out results. But this is still sort of vibration centric. There's still a human it's a it's a way of taking that tsunami of data and saying, No, we don't need that we need this and be able to sort of narrow it down, but it's still a human.

09:31

Absolutely human component. Yeah, thank you for bringing that up. It's a human. It's an ad. It's an expert, which is what the and that expertise is absolutely need. Right. Your AI helps us get to a certain point. And that's when the human and that expertise in the knowledge comes in. So the way we offer the service is we've got a group of analysts over 40 analysts globally. So they remotely looking at the data using the AI to do 90% of the work for them. And then using that expertise to kind of do that remaining 10 person and we keep improving the algorithms and everything and then provide value to our customers. So that's huge from an efficiency point of view. Absolutely. I think the other thing here is, when we think about AI, sometimes it's often looked at like, well, first of all, it's changing everything we do, it is right. Our jobs aren't going to be the same no matter what, what part of my organization, their jobs wouldn't be the same a year from exactly right. I think for us, it's really more of, we have the big problems, our customers saying they can't hire our customers saying they don't have the expertise. That's where AI can come in and take some of these mundane tasks away, and automate that, and really leave our experts to really focus on the things that they're not able to get their time to us. So I think I look at AI as really an amplifier and seeing how do you solve for some of the challenges and work work work working to try and address some of those? That's an

10:59

interesting avenue, where you can let's say, I'm on vibration tech, whatever your category I am. So I'm able to be more efficient in my because because the the AI is just sending me information that is specific to that, that that device, does the does AAzima the solution, normalize the data, meaning, it might be different, this asset down here in Texas is different than that same asset in Norway, or whatever it is. Yeah, does it? Does it bring about that sort of normalization too?

11:38

Absolutely. And I think the strength of the solution is the richness of the database. So this is the algorithms are built over lots and lots of data in different applications. So it's really trying to address that and adjust for that. I think one of the biggest challenges even when even when customers are using some sort of predictive maintenance, kind of engine and such, there's a lot of, you know, there's a lot of false alarms, right? What what is EMA has strength is it's reducing some of that, because you don't want to go do that extra work, you don't want to go and address an issue when there isn't an issue. And a lot of that leads from bad data, or so if you don't have enough data, if you have bad data, it may trigger some of those false alarms. I think in the case of his email, they've been able to reduce some of that they've been able to really get the data and the engine to work so well, that it really reduces to almost no no false alarms and really have the techs in the limited time focus on the things that are most important. Does

12:39

it continue to learn and assess? Absolutely sure. You have these these devices that exist today on on assets that are being managed by fluke reliability, and you're constantly feeding it with data, so it constantly evolves?

12:56

Absolutely. It's better. Yeah, there's, there's, as more assets get monitored, as more data gets collected, the algorithm gets stronger and stronger. And it's really that it's that feedback loop that keeps it and the analysts play a key role here. Yeah, because they are, they are assessing this and really filtering that and adding that back into the, into the into into our expert system

13:21

phenomenon. I know that you get a run, I can have this conversation, but we're already well above 10 minutes. So how do people get a hold of you on cush?

13:33

Scott, you know, I'm on LinkedIn, I'm on you know, my my email my telephone is there. I love to hear from our customers and see how we can help them solve for some of the difficult problems they're facing.

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You're listening to the Industrial Talk Podcast Network.

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