Replacing Unplanned Downtime with Personal Downtime: AssetWatch on Condition Monitoring
Manufacturing Happy Hour
This bonus episode of Manufacturing Happy Hour features host Chris with two guests from AssetWatch, a sponsor of the show: Dustin Moore, who comes from hands-on field maintenance work, and Patrick Carmitchel. The conversation asks what condition monitoring and predictive maintenance mean on the plant floor, and why they matter to the people who keep equipment running as well as to the business. Dustin's framing ties the episode together: the point of catching faults early is to buy time, so maintenance teams can plan repairs on their own terms instead of being called in at midnight on Christmas.
A Drink in Carlsbad and Bowling Green
In keeping with the show's format, the episode opens with each guest describing where they would go for a drink. Patrick picks a bottle shop in Carlsbad Village, California, from the time when he started drinking beer seriously, during the rise of the microbrewery scene. He describes it as mostly standing room, about two blocks from the beach, always stocked with new beers and older ones worth having, with a Pizza Port next door where you can buy a pizza and bring it over. Chris says he lived in San Francisco and knows Pizza Port well.
Dustin chooses a sports bar in Bowling Green, Kentucky. He says it has roughly 50 TVs and that he goes at least once a weekend. He recommends its "slinger burger": a hamburger patty on a bed of fries with toast underneath, topped with chili and a fried egg. Chris, who is originally from St. Louis, says the slinger is a well-known breakfast dish there. He adds that he believes it started with truck drivers who wanted something between breakfast and dinner, though he says he may have the story wrong.
What Condition Monitoring Is For: Buying Time
Asked to explain condition monitoring in plain terms, Dustin describes it as using different technologies and signals to get an early indication of faults developing in a machine. In his view the whole goal is to buy time. Once a problem is caught and reported at an early stage, the maintenance team can plan. They might order a replacement motor so it is on the shelf, or look at the calendar and find a good window for the repair. He names two aims: buying time, and finding problems early enough to minimize damage to the equipment.
Patrick takes a different approach and uses the can of beer he brought "just in case." He starts from the human senses. People can see, hear, smell, and touch, but they have only so many hands and ears. Running manufacturing at scale requires far more of them than any team has. Condition monitoring, in his description, is a set of tools that extends senses people already have. Vibration corresponds to hearing, and temperature to putting a hand on something. Touching a cold beer tells you something about its condition, and so does pouring it and looking at the head. The technology lets people see, hear, or sense things they already wanted to observe. An analyst like Dustin, who sees data across many assets and facilities, can then interpret it and say, for example, that something is a high-temperature issue or a gear mesh issue.
Preventive vs. Predictive Maintenance
Patrick describes predictive maintenance as watching for early warning signs and organizing the process so issues are caught and dealt with in advance. Whether the method is vibration, temperature, electrical, or ultrasound monitoring, he says the purpose is the same: to plan so that unplanned downtime does not happen. "You're going to have downtime," he says, "but it should be on your terms."
Dustin draws a sharper line between the two terms that are often confused. Preventive maintenance is calendar-based: lubricating bearings every three months, swapping couplings on a schedule, or checking motor-to-pump shaft alignment once or twice a year. Predictive maintenance and condition monitoring respond to actual signals. If early-stage symptoms of a lubrication problem appear, the team acts on the condition it observes rather than on the date.
What "Good" Looks Like: Start Where You Are
Asked to describe good practice, Dustin's main message is that a company has to start somewhere, beginning from where it actually stands. A plant that has never done this kind of work may take a while to reach a point where results look good. He says AssetWatch deals with this every day. Teams are at very different stages. Some are advanced and have vibration analysts on site. Others are inexperienced and need a lot of hand-holding and teaching of basic practices.
He gives a concrete example of such a practice: installing equipment properly with laser alignment instead of setting it up and checking it with a straight edge. That, he says, gives longer equipment life. For Dustin, extended component life is the real measure of success, and it eventually appears as ROI through saved money, prevented downtime, and avoided production losses.
The Gap Between Enterprise and Plant Floor
Chris asks Patrick about the disconnect between enterprise leadership and individual plants. Patrick says the two levels have different goals. Enterprise goals are often tied to shareholders and focus on consistency and repeatability across facilities. Each plant has its own culture, maturity level, and existing knowledge. Pushing a uniform program down to facilities that are starting from very different places creates friction.
In Patrick's account, success comes from making sure the facility is never left behind. The plant needs to understand the value of monitoring. That value is not a mountain of collected data but clear, trusted guidance for the maintenance team: what is wrong, what is urgent, and what to do next. If the team can plan a repair instead of being surprised by a failure, he says, condition monitoring is doing its job.
He then warns the enterprise level. Leadership will never reach the ROI it wants, or gather the data needed for better process decisions and improved OEE, unless it manages cultural change facility by facility, one step at a time. A plant cannot be expected to adopt every form of monitoring and build predictive analytics if it has not yet covered its critical assets and done one thing well. Vibration and temperature monitoring are the accepted standard. Patrick reports that AssetWatch's engineers say about 60% of what needs to be caught will be caught by doing that one thing well. He asks why anyone would talk about other methods before that is in place. His suggested sequence is to do the basics first, prove ROI, and then add oil analysis, electrical monitoring, ultrasound, and other methods to get the most out of each asset.
When Chris asks him to state the single most important thing plainly, Patrick answers: support the individual facility through cultural change.
Winning Over Skeptical Sites
Dustin says that convincing a plant can be hard, and "the proof's in the pudding." Some sites do not believe there is a problem until they see smoke or a big temperature spike. AssetWatch's approach is to put the data in front of the team, analyze it with them, explain what the analysts are seeing in terms the team can follow, and give the reasons behind each diagnosis.
He admits that it can remain a hard sell for a while. Teams change their minds when they see results for themselves. For example, a bearing is replaced, the trend level drops from high to low, and the team notices the bearing running cooler, smoother, and quieter. Sometimes this happens quickly, and sometimes it takes more demonstrated results. The goal is to move teams from a reactive mindset to a proactive one.
"Unplanned Downtime" vs. "Personal Downtime"
Chris returns to a phrase Dustin used when they first met: replacing unplanned downtime with personal downtime. Dustin explains it from his own career. He spent years in the field, including work about a thousand feet underground in mines and outdoors in the hot sun. In that kind of service work, he says, it is "uncanny" how often equipment breaks on a weekend, at Christmas, or at the most inconvenient time. Besides saving the company production losses, early warning lets technicians plan their work "instead of being at the mercy of when it decides to fail," which he jokes always seems to be Christmas at midnight.
Patrick says this is personal for him because his father worked in manufacturing facilities. He also recalls a story that AssetWatch's CRO, Brian Ratliff, told at a company all-hands meeting about his own father and about missing an important part of his child's life because he could not get out of a facility during an unplanned event. Patrick says everything the company does is personal in this sense.
The Long-Term View: The Right Monitoring Mix
Asked about the long-term future, Patrick says AssetWatch's view has been the same since the company started under founder Will Zel. For each asset, the question is what mix of condition monitoring gets the most out of it, or how to "squeeze the most out of that orange," while accepting that returns diminish at some point. As technology improves and monitoring various conditions becomes more efficient, the goal is to reach a point where everything practical has been done. Teams could then predict what is happening and respond rather than react, maximizing planned uptime.
The Short-Term View: Multiple Modalities and Fast Change
Dustin sees a current shift in the industry toward combining multiple modalities and signals. Not every asset justifies electrical, oil analysis, and vibration monitoring together. Having all of these tools available lets a team choose the most useful combination for each asset. On a highly critical asset, combining several signals gives a holistic picture of what is going on.
He adds that with advances in AI and data science the field is changing so quickly that it is hard to think very far ahead. Developments in the short term are moving fast enough that he finds it difficult to look further down the road.
"Is This Going to Replace Me?"
Chris raises the concern that monitoring technology might threaten jobs. Dustin says he understands the worry. In earlier roles, he could imagine reacting to a company like AssetWatch arriving and wondering what would happen to him.
He then tells a story from a site he currently monitors, a very large cement plant with a Category 3 vibration analyst on staff. The two now talk daily about the equipment they both monitor and have become friends. The analyst told Dustin he felt very threatened when AssetWatch first arrived. At the time, he said, he was doing well just to finish his routes every two months. A lot was falling through the cracks, and he kept being pulled into mechanical work when he should have been doing vibration routes. He described himself as going a thousand different directions. Dustin says the analyst told him it "didn't take me long to realize that AssetWatch was the best thing that ever happened to me."
The two now work together. The analyst still uses his Emerson 2140 portable meter. Dustin tells him what is changing in the AssetWatch platform, and when deeper troubleshooting is needed, the analyst takes the portable meter out to investigate. According to Dustin, this has freed the analyst to balance fans and do laser alignments, because he knows the continuous monitoring in the background is watching the trends.
Deciding What to Monitor: Criticality, Not Size
Chris asks which applications should be monitored but often are not, noting that something like a turbine will almost always have monitoring. Dustin does not name specific machine types. He says the answer comes from a criticality assessment at each site. A team should ask which assets would shut operations down if they failed, which would take four or five weeks to replace, and which have very high replacement costs.
He stresses that criticality is not about size or machine type. A small, football-sized motor can be essential if, for example, it supplies lubrication to a turbine. Understanding each machine's criticality is one of the first steps in building a reliability program. Continuous monitoring should start with the most important assets and expand from there.
What Excites Them: Less Paperwork, More Signal Fusion
Patrick's answer goes back to people. He acknowledges anxiety about how much disruption "AI, just two letters" is causing. He sees it as history repeating: new tools always arrive and always require adjustment. He is excited that AssetWatch gets to be present for this transition.
He points to a long-standing problem in manufacturing: it is a hard place to work, and nobody wants to fill out forms in a hot environment while managing an SOP and updating documentation so that data can flow up the chain to support better models and decisions. What excites him about the new tools is that people can use voice, video, and the natural environment to capture information in ways that make work less painful. "Filling a form out is the least human thing we could possibly do with our time," he says. He sees replacing unnatural data entry in hard physical environments as the most exciting area for AssetWatch to work in.
Dustin agrees that AI and data science have "changed the ball game." He says the company wants to keep focusing on customer needs and shape its products around them. Personally, he is most excited about combining multiple technology signals with data science and seeing how much insight that can produce.
AssetWatch's Origins: From Wireless Power to Sensors
Patrick tells the company's origin story. Founder Will Zel and a co-founder started in a different field. They were working on harvesting energy from signals so that a cell phone would not need to be charged, which was essentially a wireless power venture. They then found that industrial manufacturers were interested in wireless power so they would not have to keep changing batteries or wiring their vibration monitoring equipment.
Patrick calls that the company's first big startup pivot. Wireless power turned out to be very difficult, partly for regulatory and political reasons. He says the technology worked and the team was able to transfer wireless power to monitor assets in a manufacturing environment, but the world was not ready for it. Along the way, the founders became experts in getting as much life as possible out of a battery using Bluetooth Low Energy.
That led to a second pivot, built on several convictions Patrick lists. Route-based monitoring no longer makes sense, especially for critical assets. Multiple modalities should be combined in a single sensor. Monitoring should be wireless and work at scale. A sensor should stay in the field for years with reliable battery life while producing rich data. In Patrick's words, that is when the company found its "home," and its plan is to keep adding modalities "until we solve optimal uptime."
Adding Electrical Monitoring
The final question is about AssetWatch's move into electrical monitoring, which can catch problems vibration might miss. Dustin says there is no single origin story. It comes from the effort to evolve the products to meet customer needs and from the industry's shift toward multiple signals.
He explains it by comparing vibration and oil analysis on the P-F curve. The two are often interchangeable depending on the case. Contaminated oil will eventually damage a bearing, and the damage will show up in vibration. Oil analysis can catch the contamination earlier, so the oil can be cleaned before any bearing damage occurs. In other cases, vibration detects a problem before oil analysis does. Electrical monitoring follows the same principle. Some electrical faults eventually appear in vibration, but monitoring the electrical signal directly lets analysts see subtle changes in electrical behavior earlier. That returns to the theme Dustin opened with: catching issues early, before they cause other damage and become severe, and so buying the maintenance team time.
Doing that type of service work. It's just uncanny how often it happens on the weekend or at Christmas or the most inconvenient time is when stuff decides to break. Plan your work instead of being at the mercy of when it decides to fail.
Today's episode is all about condition monitoring and how to replace unplanned downtime with personal downtime. Our guests this week are from AssetWatch. AssetWatch eliminates unplanned downtime through end-to-end condition monitoring, AI-driven predictive maintenance, and more. And they are one of Manufacturing Happy Hour's newest sponsors. We're joined by Dustin Moore and Patrick Carmitchel as we cover vibration monitoring, predictive maintenance, and the future of condition monitoring.
Dustin, Patrick, a proper Friday afternoon podcast recording. And in the spirit of Manufacturing Happy Hour, in a time where we would typically probably be out having a beverage right now, I have to ask you each this question because you're in different parts of the country. So Patrick, let's head out to California first. If we were grabbing a drink in California, where would that be? What would we be having?
When I started drinking beer for real is when the microbrewery scene really popped. So that would have to be when I was in Carlsbad Village. We had a place called the Bottle Shop and it just always had whatever was new and whatever was old and worth having anytime. Like, for instance, Ply.
Yeah.
That place was a go-to. And it's about two blocks from the beach, so you can walk to the beach if you want. You can stand outside. It's basically standing room only. And there's a Pizza Port right next door, so you can bring a pizza over. It's a great place to just hang after work, talk, unwind, and get any beer you want to just crack one open. So, a lot of good times. Great place for somebody who likes a good beer.
I used to live in San Francisco. I think I went to that Bottle Shop. I know for a fact I have been to Pizza Port in Ocean Beach many of times for a slice and an IPA. If I go back to San Diego anytime, that's usually one of the top spots on my list I want to hit up. So, I know exactly where you're describing right now, Patrick.
Awesome.
So, Dustin, let's say we're hanging out in Bowling Green, Kentucky. And I know I pitched it before as maybe we're watching a minor league baseball Hot Rods game, but that's the main thing I'm familiar with from Bowling Green, but I don't want to give you your answer. Where might we be hanging out having a beer?
Well, my favorite place in town is a little place called Pub by Novo. It's a little sports bar. Got really, really good food. Big screens all around and it's probably 50 TVs in the place. Beer's cold and I make a trip at least once a weekend there. They call it the slinger burger. So, it's basically like a hamburger patty. It's over a bed of fries. I think there's a piece of toast at the bottom of it. It's got chili on it, a fried egg. There's a little bit of everything on there. And if you finish the whole plate, you definitely ain't hungry afterwards. So, it's pretty good food.
Dustin, you're going to get a kick out of this. I'm a St. Louis guy originally, and the slinger is a famous breakfast item out there. So, yeah. Hamburger patty, chili, an egg, some cheese. If I remember right, a slinger started because truck drivers wanted something that was a little breakfasty, a little dinnery. I might be getting the story wrong, but it's kind of this delicious conglomeration. The chili, I think, is what really sets it apart. And it's wonderful to hear that there is a burger version of that in Bowling Green, Kentucky as well.
Really good. Really good. If you come this way, you got to check it out.
Oh, I definitely will. Well, let's stay in Bowling Green for a second. I'm going to ask you both a version of this question, but Dustin, how do you talk about condition monitoring if you're having cold beer and eating a slinger burger? How do you talk about it in candid terms?
Condition monitoring to me is using different technologies and signals and trying to get an early indication of faults developing in your machine. I think the whole goal of it is to buy time. You catch stuff in an early state. You recognize that, you report it. It gives the maintenance team time to plan, whether it's maybe they need to order a motor and get it sitting on the shelf. It gives them time to play with it. It allows them to look at the calendar, see when they'd have the opportunity to do maintenance work that's required to fix it. So yeah, I think to me that's the name of the game, is one, buying time, and two, identifying things in an early stage to where you recognize that and you can get to it at an early point where you minimize the damages to the equipment.
Yeah, I'm glad you put that in a maintenance context. We'll get back to more of that here in a little bit. But Patrick, I've got two questions for you. The first one is pretty similar to what I just asked Dustin. You know the Manufacturing Happy Hour audience. We're dealing with a lot of folks that are primarily in the manufacturing space. Our audience is familiar with condition monitoring. We're talking about vibration analysis, in many ways. In candid terms, let's say we're hanging out there at Pizza Port or the Bottle Shop. What are we monitoring the vibration of when it comes to condition monitoring? Let's go there. Give us some examples of what that looks like, Patrick.
Yeah. I'm just thinking about literally being at the Bottle Shop. If I was there and assuming I'm talking to people that may not actually even know what it's talking about, I would probably use a beer.
Yeah. Yeah.
I didn't know if we were going to have something here, but I just in case was prepared. So I would look at this and I would say condition monitoring probably is associated with us as humans, right? We can only do so much. We can see, hear, smell things, and touch things and we only have so many fingers and hands. And as you are building and achieving great things within manufacturing environments, producing at scale, you need many fingers and many ears and many eyes on these things. And so condition monitoring is really about what are the tools to extend what was naturally already there.
Vibration is hearing. Are we hearing things? Our ability to put your hand on something and touch it and say this beer is pretty good. It's cold. I like it. I crack it open and I pour it and say, what's the head look like, right? But the truth is when you have it in a bottle, you shouldn't do have this beer. But it's really about those things, right? And it's really human. It's how you use technology to be able to see, hear, or smell things that we would already wanted to do. And someone like Dustin can get in there because he's seeing it at scale across all of these assets, across many facilities. He's able to look at that and say, "Okay, that's a problem. That's a high temperature issue. That's a gear mesh issue. That's whatever it is." So that's how to explain that.
Yeah. Excellent answer. And I'm actually going to go a step further because Dustin, you were giving a great example of this at the start. You were talking about condition monitoring in the context of predictive maintenance. So, one more question for you, Patrick, and then Dustin, I'm going to kick it back to you. How does predictive maintenance work? I know a lot of folks listening are familiar with it. It's a topic that has come up on the show more than a few times, but I'd love to hear your take on painting the picture of what this looks like.
For me predictive maintenance means that you're looking at early warning signs. And so a lot of this is around how you plan it so that you can catch things because you know that your process should dictate whether there's an issue and in advance take care of that. And other times you're looking at whether or not you want to address issues proactively in order to be able to know as you're continuing to develop. So if you're looking at vibration, temperature, electric, ultrasound, all these monitoring methods, it's about your ability to be able to plan so that you do not have unplanned downtime. And all of these tools and process really are designed specifically to mitigate that. You're going to have downtime, but it should be on your terms.
Yeah. Now, Dustin, I'd love to hear your thoughts. Can you tell us what predictive maintenance looks like in the context of a manufacturing facility? Let's go a little deeper, maybe paint a picture from your end.
Yeah. So, you hear the term preventative maintenance and then you hear the term predictive maintenance. So, preventative maintenance is more a calendar-based technique where you're lubricating your bearings every three months. You're changing your couplings out every so often. You're checking the alignment once or twice a year on the motor-to-pump shaft alignment. Where predictive maintenance and condition monitoring are more so looking at actual signals and maybe you see early stage symptoms of lubrication and you're working more towards the conditions you're actually seeing. That's kind of the way I think of it.
Yeah. What does good look like in the context of condition monitoring? If I'm a manufacturer listening to this, I'd love to get your take, Dustin, as to what pretty good looks like. Maybe it's not perfect, but what do good best practices look like in the context of manufacturing?
Well, there's a lot of different aspects to that. But the moral to the story is you've got to start somewhere. You got to start where you're at, and you take a company that hasn't been doing this sort of stuff, sometimes it takes a while to get to a point where it does look good to you. And we experience that on a daily basis. You kind of meet maintenance teams where they're at. They're all in different parts of their journey. You get some that are pretty advanced. They may have vibration analysts on staff that are boots on the ground on site. And then you get some maintenance teams that are really inexperienced and we do a whole lot of hand-holding and teaching of best practices.
So, a lot of aspects to that, but overall I think just starting somewhere, establishing good practices, learning the benefits of properly installing stuff, using laser alignment instead of just setting something up and straight-edging it. You're going to get longer life out of your equipment. And to me, that's the measure of success. When you're starting to extend the life of your components and ultimately you see that ROI at the end of the day, you've saved money, you've prevented downtime, losses, things like that.
Yeah. I think those are some great summaries, right? You're extending the life of equipment, you're preventing the downtime inside of a facility. Let's go a layer deeper. Patrick, I'm going to send this one to you because I think for some of the audience, we've captured some things. They're nodding along with us, right? They're like, "Yep, this all makes sense." One thing I'd like to ask you, Patrick, is, let's say, what is the disconnect between enterprise level and what's going on on the plant floor and how does condition monitoring play into that?
Yeah. For me, we see a lot of this. It's challenging because everyone has their goals and the enterprise goal is frequently associated with their shareholders, not necessarily how does a plant feel, what is the culture of that one facility and how are they operating effectively. And for condition monitoring, at a facility level versus what it means at scale for the enterprise to get what they want to grow a business, these can be very different things.
And so, from an enterprise level, we're looking at the consistency across and repeatability across facilities. And if you're trying to shove that down the pipeline to facilities that, to Dustin's point here, are related to different kinds of maturity, they are all starting in different ways and they all have their own cultures and they're all going to approach and leverage whatever knowledge or experience they have to start to take steps. And so the challenge is really that disconnect. And where we've seen a lot of success really is around making sure the facility is never left behind.
The facility is not the one that is understanding the value of what it means to be monitoring, not just collecting a mountain of data, but giving the maintenance team clear and trusted action. They know what's wrong, what's urgent, and they know what to do next. And I think if you can plan repair instead of getting a surprise or a failure, condition monitoring is doing a pretty good job using some of the methods that Dustin was referring to.
But at an enterprise level, if they lose sight of the fact that they're never going to get that ultimate enterprise ROI or the data required to create greater decisions to improve total process and manufacturing, to improve OEE, all of these things that people desire to have, unless you actually, facility by facility, manage cultural change one step at a time. And you can't expect that someone's going to go and apply all the various forms of condition monitoring to be effective and to develop all the analytics to be predictive if they haven't just looked at critical assets and just done one thing really well.
And I think that's really the challenge, is have they done that first one thing? And I think the expertise that Dustin has here in looking at vibration, temperature, this is an accepted reality. That's the standard. If you do that, a lot of our condition monitoring engineers say 60% of the things that you're going to need to do, you're probably going to catch just by doing that one thing well. And if you haven't done that for critical assets, why are you talking about all these other things? Let's go do that first. Let's prove ROI and let's keep adding on more oil analysis, electrical, ultrasound, all of these great methods of monitoring to get maximum ROI of an asset.
And I want to just have you repeat that, Patrick, just so the audience gets it. What is the one thing that they need to do really well, just very clearly?
They need to support the individual facility for cultural change.
Dustin, I'm going to kick it over to you now. So, what's a best practice you would offer on supporting a facility with the type of cultural change that's needed? Maybe from some of your experiences out in the field.
Well, the proof's in the pudding. Sometimes it's a hard case to sell, and we've experienced that. You get some of these sites and they don't think there's a problem until they start seeing smoke or big temperature spikes, something like that. So, one way we do it is we present the data in front of them and we'll analyze data right in front of them and kind of try to talk to where they can understand exactly what we're seeing. Give them the reasons why we think it's
This or that, and then it's still a hard sell for a while. But once they start seeing that, you look at those trends and, hey, you changed the bearing here, and this level went from up here to down here, and they see the results on their end too. That bearing is running a lot cooler, a lot smoother. Don't sound like it should. So it's a process. Sometimes it happens pretty quickly, and sometimes it takes a little more showing results before you get them to come around. But like I said, we definitely meet all different types, and we meet them where they're at. We work with them and try to get them to come around to a more proactive than reactive state of mind.
Yeah. I'm curious, Dustin, one thing that you had mentioned, I believe when we first met a couple weeks ago, you had said you're working to replace unplanned downtime with personal downtime. And I think that quote really resonated with me in terms of what the whole point of predictive maintenance, condition monitoring ultimately is. So Dustin, if you could explain that in a little more detail, I'd love to hear what you mean by replacing unplanned downtime with personal downtime. I'd love to hear it in your words.
Absolutely. I spent a lot of my career hands-on, in the field, boots on the ground, underground, a thousand foot in the mines, or outside in the hot sun working on something. Doing that type of service work, it's just uncanny how often it happens on the weekend or at Christmas, or the most inconvenient time is when stuff decides to break. So part of the benefit of doing this, in addition to saving the company money for their production losses and giving the maintenance team more time to react, is you get that early warning. You can plan your work instead of being at the mercy of when it decides to fail, which, like I said, is always on Christmas at midnight.
Yeah. Patrick, do you have anything to add to that?
Yeah. I think for us, this is a personal thing. I grew up, my father was in manufacturing facilities, and you just see these are people. I think it's a great story that our CRO, Brian Ratliff, shared with the whole company a while back, one of our all-hands, around his own personal experience with his own father and missing out an incredible part of his child's life, had he not been able to get out of that facility during an unplanned event. And it's just very personal. Everything we do here is really personal.
Patrick, I'm going to lead off with you for this question. I want to talk about what kind of the future of condition monitoring looks like. I want to do this from a long-term and a short-term perspective. So, Patrick, what does the long-term future of condition monitoring look like?
I mean, the long-term future, in our view, has really been there since the beginning. I think about our founder, Will Zel, and from the outset it's always been, hey, this is an asset, and it's operating as effectively as it possibly can. What's the right mix of condition monitoring to get the most? How do you squeeze the most out of that orange? And then there's diminishing returns at some point. And the goal here, as technology evolves, as our ability to monitor various conditions efficiently and have an appropriate monitoring mix evolves, we're able to say we've fully maximized what's possible so that we can predict what's happening, respond rather than react in a way that makes sense to ultimately maximize our planned uptime.
Yeah, Dustin, I've got a couple questions for you. I'd actually like to ask you about the future of condition monitoring in the short term. I think we've talked about modalities before. I'd love to get your take.
Yeah, I think we're seeing a shift right now in the market where companies and the industry as a whole are seeing the value in using multiple modalities and signals. Every asset may not make sense to have electrical, oil analysis, and vibration all on it. Some may, but having those different technologies at your fingertips to use as tools, you can make the best decision per asset to what's going to give you the most beneficial information. And you take an asset that's really critical, you use multiple signals on it, you can really get a holistic view of what's going on with that asset when you combine those multiple signals.
So this condition monitoring realm, reliability realm, with the advances of AI and data science, it's rapidly evolving. So that's kind of a short-term solution, but beyond that, it's evolving so quickly, it's hard to think very long term. It's advancing so quickly in the short term that it's hard to look that far down the road.
Well, one thing I also want to ask you about is, and our audience is definitely an audience that understands these are tools that are helping us, empowering us. They're not replacing jobs. But Dustin, I feel like you've been in the position before where you've seen folks wonder, is this going to threaten my job? For example, I think you've had this conversation pretty recently, actually. I'd love to hear where maybe that's the thought, but why you have been able to articulate that that's not actually the case.
Yeah. And I've been in roles to where I could see myself in those shoes, where if somebody like AssetWatch came along, I'd be like, "Oh man, what are they going to do with me?" But one of the sites that I monitor now has a Category III analyst on staff, and me and him have become really good friends. Talk every day. On a daily basis, we'll touch base around the equipment that we're both monitoring and collaborate around that, but also we've become friends.
And he told me, he said, "When you guys first come in here, I felt really threatened." But he said at the time—this is a really, really big plant, big cement plant—he said, "At the time, I was doing good to finish my routes every two months. And there was a lot of stuff falling through the cracks. I was being pulled to do mechanical work when I should have been doing my vibration routes and stuff like that. I was just going a thousand different directions." And he said, "It didn't take me long to realize that AssetWatch was the best thing that ever happened to me."
So he's still got his Emerson 2140 portable meter on hand, and we work in conjunction. So with the AssetWatch software and platform, I let him know what is changing, and then if there's deeper troubleshooting required, he can take his portable meter out and look into it. But it's freed his time up to where he's able to balance fans, do laser alignments, because he knows that he's got the safety net of AssetWatch in the background kind of monitoring the trends for him.
Yeah. Dustin, another question just popped into my mind, especially for groups that are listening to this out there thinking, I know I need to be doing a better job with my condition monitoring. What is the number one thing, or maybe a few applications that you see out there, that should be monitored that aren't being monitored on a frequent basis? Because we're there, and by the way, there are people across a variety of verticals and industries listening to this, but there are only so many different things that rotate in the space. I'm very curious. I feel like something super critical, like a turbine, for example, that's always going to have condition monitoring on it. But I'm curious what some of the other things that should have it but don't might be.
Well, it's just a matter of doing a criticality assessment at your site. Every site's got certain assets that's detrimental to operation. So that's the biggest thing, is understanding what are my big players that, if this goes down, it shuts operations down? Or what are the assets that I have that's going to take me four or five weeks lead time to get a spare? What is the assets that are really, really high-end replacement cost? So it's not necessarily a size thing or a machine-specific thing. There's some situations where a little small football-sized motor may be very, very detrimental to—it may be sending lubrication to that turbine. So understanding the criticality of each machine is one of the first steps that a company should take when they start to kind of build their reliability program out. Understand where our big players are, and that's where you really need to start with continuous monitoring, and you can expand out from there as you see fit.
Awesome advice. Patrick, I'm going to ask you this question first, but Dustin, I'll pass it to you as well as we get towards the end of our conversation. What are you most excited about right now when it comes to the future, near future, long-term future of condition monitoring and predictive maintenance?
I think I take it back to the people. I talk about those that are concerned about all the change happening right now, the concern of AI, just two letters creating so much disruption, and the reality that this is nothing new. It's history repeating. There's always going to be new things, new ways to do things. It's always an adjustment. And for me, I'm excited about the fact that we get to be there during this transition.
There's been some really, really challenging things that have never been able to happen in manufacturing because it's a hard space to work. And who wants to fill out forms when you're sitting there in a hot place trying to manage an SOP, and you're going to update your documentation so that you get the right data so that you can serve that up the chain and everybody gets new models to make better decisions? That's really nice, but the cool thing about these tools and where we're going is that you can use your voice, you can use video, you can use the natural environment, things that are already happening, to capture things in ways that make work less painful.
And we're excited about figuring out how do we do that so that you can do the work you want to do well, and just take these painful things that were never really human. Filling a form out is the least human thing we could possibly do with our time. So filling out things that produce data unnaturally, I feel like that is the most exciting thing in a hard physical environment that we get to partner in, and that's exciting to me.
Yeah. Dustin, what are your thoughts?
Yeah, I thought Patrick had a really good answer there. But yeah, AI and data science has really, really changed the ball game. So I think that above all else, we want to continue to look at the customer's needs and improvise and form our products in a way that it's meeting those needs. And one thing that's really exciting to me is my brain is just constantly churning at combining multiple signals of technology and intertwining that in data science, how insightful that can be. So very excited with where we're going in the future with those sort of things.
Well, I have one question that, Patrick, I'll ask you this one because this is actually more of a brand question. It's an AssetWatch question. I just feel like you guys are making waves in this industry recently. And I'm imagining there are some folks listening to this that are learning about AssetWatch for the first time. So can you give us a quick background on the story of how AssetWatch got started and how quickly you've kind of risen in the industry? I think that would be helpful for a lot of people that have spent the past 30 minutes getting to know you guys for the first time, Patrick.
Yeah, it's actually a really interesting story because Will Zel and the co-founder of this company were in a totally different kind of space. They were looking at how do we disrupt harvesting energy through lat signals on a cell phone, right? It was a completely different world so that you didn't have to charge your battery. So this is about wireless power originally, before we ended up discovering, okay, somebody's really interested in industrial manufacturing to leverage wireless power so they didn't have to continuously change batteries or wire their monitoring when it comes to vibration analysis.
And so that was kind of that moment of shift in a typical startup where you have a big pivot. It's like, oh wow, this is interesting. And then it's just so hard, right, through the changes required, even just politically, to go into wireless power is a massive deal. So it's like, okay, the world isn't necessarily ready for that. It worked. It was very cool, and they were able to transfer wireless power in order to monitor assets in a manufacturing environment. But they became experts also in getting the most you can possibly get out of a battery in order to do that with BLE, which is low-energy Bluetooth.
So it's really cool how they then pivoted again into, okay, the world's not ready for that, but we know we love this space. These are real hard problems that the people are facing. Route-based monitoring when you don't have to do a route, especially for critical assets, doesn't make sense anymore. Combining multiple modalities within a single sensor makes sense. Doing it wirelessly makes sense. And being able to do it at scale and be able to leverage a model that allows that sensor to exist for years at a time in field with a trusted battery life, consistently operating effectively and getting you rich data, not just poorer, but really rich data, is something that really kind of brought everything forward into, all right, this is our home now. We know who we are, and this is what we're going to go do, and we're going to keep stacking new modalities against this space until we solve optimal uptime.
Well, I appreciate the backstory, and I have one more bonus question because we've learned a lot about vibration analysis today talking through condition monitoring. But now AssetWatch is getting into electrical monitoring, things vibration couldn't catch before. How did this latest evolution of the company come about? How did this electrical project come about? Dustin, I believe you have a story for this that you can share.
Yeah, it's not necessarily a story, but we're constantly looking to evolve the products that we have to meet customer needs. And the industry is going to multiple signals, and I think we see the value in that. So you can kind of relate the electrical to thinking about vibration and oil analysis, the relationship between those two. So if you look at the P-F curve, vibration and oil are a lot of times interchangeable depending on a case-by-case basis. So let's say you've got contaminated oil. It will eventually end up to a point where you've got a damaged bearing, and you're going to see it in vibration. But if you're doing oil analysis, you can
Get it in an early stage and clean that oil up before it ever ends up in bearing damage. And you'll run into cases where vibration would detect something earlier than oil.
So electrical, by getting into electrical, it's sort of the same principle. There's electrical faults that'll eventually show its head in vibration, but if you're monitoring the electrical signal directly, you can notice little subtle changes in the behavior of that electrical. And again, goes back to that time. You're able to catch stuff in a very timely manner, very early stage before it creates any other damages and advances to something that's a severe problem.
Yeah. Well, I'm excited to see the evolution of AssetWatch, you guys getting into electrical monitoring. It's been awesome getting to know you guys over the course of this conversation today. So with that, Dustin, Patrick, cheers. I just want to thank you both for taking the time to be on Manufacturing Happy Hour today.
Yes, sir. We appreciate your time.
Cheers, folks. Hey, everyone. Thanks for listening and thank you to Dustin and Patrick for jumping on today's show. And thank you to AssetWatch for sponsoring this podcast. If you want to connect with Patrick, Dustin, and AssetWatch, head to the show notes page at manufacturinghappyhour.com and make sure you're subscribed to Manufacturing Happy Hour wherever you get your podcasts. Stay innovative, stay thirsty. We'll catch you again next time.
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