Podcast: How ultrasound enables safer, more efficient plant operations

Key takeaways

Ultrasound adoption is growing fast, often outpacing vibration as the go-to condition monitoring technology.
AI-driven tools are improving maintenance decisions by aligning data collection with specific actions.
Autonomous lubrication systems save time, reduce risk, and enhance machine reliability through precise, condition-based action.
Small gains in bearing efficiency can scale to major energy savings and improved sustainability plant-wide.

In this episode of Great Question: A Manufacturing Podcast, Thomas Wilk, chief editor of Plant Services, sits down with Blair Fraser, VP of technology at UE Systems, to explore the evolving role of ultrasound technology in industrial maintenance. The conversation highlights how advancements in AI, battery life, and processing power are enabling smarter, faster decision-making for equipment monitoring and lubrication. Blair shares insights into how UE Systems is integrating automation and partnerships to reduce downtime, improve safety, and boost energy efficiency. The discussion also looks ahead to how future-proofed tools will empower workers and extend the value of condition-based maintenance strategies.

Below is an edited excerpt from the podcast:

PS: I just got out of a great session [at Leading Reliability 2025] with Blair where we talked about future technologies and future applications for ultrasound – how that technology is evolving and changing to meet the needs of customers out in the field and beyond. That's we're going to talk about today, Blair, is some of what you're seeing in the markets and some of how technology evolution is changing.

BF: Yeah, looking forward to it, and look at a high level what we're seeing is that the adoption of ultrasound is going at a pace we haven't seen before. More people are adopting ultrasound, finding different use cases for it, and we’re really excited.

PS: You mentioned the market for ultrasound is actually starting to emerge past the market for vibration, not that they're slowing down, right. But I was surprised to hear in the previous conversation that market share for ultrasound has grown to exceed that.

BF: Right, and I would or wouldn’t? say that the growth rate of ultrasound is set to outpace the adoption of vibration. When we look at conditional monitoring technologies, I think vibration is kind of the standard, it's what most people go to. But now I think more people are open and see the value in combining not just having a single technology, but combining multiple technologies together and often ultrasound is that first other technology that's being used.

PS: In your presentation called Next Generation Ultrasound, you had broken down the way that a lot of people approach using this technology into: detect, diagnose and decide. And in many ways, some people can stay at detect and diagnose, but that technology is evolving to address the decided part of this, correct?

BF: Correct, and that's really where I see artificial intelligence (and things being smarter) really helping us to make better decisions, but better decisions faster, right? And I always link it back to an action – so what action are you going to take from the decision? Everything we do is usually helping us to gain some knowledge to make a decision, and the analogy I gave in the presentation today was, if you are starting out in condition-based maintenance or condition monitoring, whatever you want to call it, and you're still reactive, you still don't have a lot of time to go into root cause analysis and things like that, but your objective is to keep the plant running, that's where you can just stay in the “detect” mode. I detect the bearing is wrong or bad, and my action is replace it, so you can miss the diagnose piece, you don't need all the data, you just want to keep the plant running and you can mature over time. I think what happens is technology has to align with the decisions we're going to make because the more sophisticated, the more data we need is going to drive up the price, it's going to drive up how hard it is to adopt this technology and everything. So I think if we start to link the technology to the actions we're going to take now and in the future, we can get more aligned on technology adoption.

PS: And you profiled the results of some research you had done, especially to understand better how to take ultrasound readings to determine whether the readings indicated a mechanical fault, or a fault with the level of lubrication needed (i.e., too much or too little).

BF: Exactly, and we're trying to use technology and it really is driven by two things in our world. One is the advent of battery technology and how long we can run wireless sensors and portable instruments, in couple with processing power. I think where AI is going to help us – call it AI, neural networks, whatever you want – and some basic algorithms is to make us better decisions. So what we're working on is an algorithm that's going to help us make a decision whether we need to lubricate this bearing, or do we need to start planning to replace it, right, and give that quantitative measurement, some guidance to some people out there that have to look at hundreds if not thousands of bearings on a weekly, monthly, daily basis and help them make better informed decisions right at the asset itself?

PS: Right, and this is the promise of AI. AI is not going to fold your clothes, it's not going to drive … well, it might drive your car. But in terms of machine health, it's going to help you decide better what to do about what is happening in the field. And as you observed, when it comes to bearing lubrication, most lubrication is done with the machines operating. You know, you're not going to shut down the entire machine to take care of this. To better understand what action to take – do we have to shut the machine down or not? –is critical towards helping companies save money and be efficient in this area.

What we're working on is an algorithm that's going to help us make a decision whether we need to lubricate this bearing, or do we need to start planning to replace it.
- Blair Fraser

BF: Absolutely, if you look at the recommended guidelines on how to lubricate a bearing in a motor, it’s quite extensive. And if you look at it subjectively, if you follow each step to a tee, it's going to take you 10, 15, 20 minutes to lubricate just a single bearing. If you look at the number of bearings in the facility that need lubrication, there's a lot. So the math doesn’t math – there's not enough time in this world, and I think that's fundamentally what technology is bringing us, is time.

It's actually the fact why we keep on developing and enhancing what we call the OnTrak Wireless System. It's our way of giving our customers back their time. It's an autonomous condition-based monitoring system, which means it's lubricating based on the condition of the bearing, but it takes that decision in action and automates it. So what it's doing instead of telling you hey, this bearing needs lubrication is it’s going to go out there, and it’s going to lubricate your bearing on your behalf, very precisely. Now it's got some guidelines in place and humans always have oversight, right? We're not just setting it loose and these gremlins go out there and do their thing. You have human oversight, and I think that's what people understand is, it isn't just a set and forget; if you change your bearing, you need to reset some parameters, so there's always some expertise required to manage these types of autonomous systems, but that's really where UE Systems is going. We're trying to use technology to make better decisions and automate our actions.

PS: And you started bringing partners on in the process of research and development to understand better how to get results from these ultrasound tools. Your first partnership that I was aware of was with Flir recently, and there's another partnership that was just announced, correct?

BF: That's correct. At UE Systems, we firmly believe that our customers need ecosystems, they need partners from different aspects, bringing different expertise to the table. And Flir is a great example of very successful partnership, just like the partnership we announced with this company called perma-tec. They're a German company, the market leader in single point lubricators to complement our OnTrak Wireless System. Just like with Flir, we formed a business partnership with the technology we have now, but it's also a technology partnership and that's what excites me the most, because now we can get some of the smartest people in the room from both aspects of this technology and figure out how we can combine them, make them more efficient, make them more effective.

So with perma-tec, we have integrated and designed with them to engineer a lubricator to work with our OnTrak Wireless System, and we use their network of grease supplies to put any type of grease in these lubricators for mounting kits. What is exciting, and hopefully we'll do a podcast next year, is build the technology that we're working on together. If you integrate ultrasound as close as you possibly can to the lubricator, the better it's going to be for our customers.

PS: One last question before we wrap up. You observed there were some follow-on benefits of this kind of technology in your presentation today including energy savings and safety. Could you talk a little bit about that?

BF: Yeah, absolutely, and this was a fundamental learning. We knew it existed and there was some qualitative advantages of it. So essentially, when we're looking at lubrication or bearing health, we're monitoring the friction in the bearing. While very, very subtle, with a change in the decibel level that indicates it needs lubrication, there is a very small, quantifiable energy use that's happening. It is so, so very small, but if you can measure it, you can quantify it and you can save it. And what excites me the most is what we found is when you're operating above the needs lubrication level is about a 3-8% loss of energy efficiency in an electric motor.

So 3-8%, and that's just one bearing. So while one bearing alone isn't going to change the world, it's not going to negate air conditioning and things like that, but what it's going to do is compound, because most people have hundreds if not thousands of bearings. And how long do they operate in that unideal state of increased friction? What we're seeing is no longer just “save my bearings” or “save my time.” Now it's, “can we make this world a little bit of a better place for the people that we're going to leave it to?”

And then when we get back to the safety aspect, and this is a kudos to our customer that drove it is, what we find is using autonomous condition-based lubrication system is you save about 99% of the time needed to lubricate a bearing. But what we didn't realize, and this is where good partners come together, is there's a safety aspect. Ideally with the lubricated bearing that asset is running, any time there's a safety instance is because you're doing something to a machine, and it's typically in in transient states – when it's shutting down, when you're doing maintenance, shut downs, some things like that. So anytime we can take a technician, a maintenance person out of harm's way, there is a safety component to that.

PS: One more before we wrap up Blair. We talked about where UE has come from and the way technology has evolved currently. What's next on the horizon for UE and its partners?

BF: We've been around, I think 51 years, maybe 52 now, and I think because UE Systems is seen as the leader in ultrasound, it's our job, our responsibility to make sure we're evolving the technology. One thing that's very clear in the way UE Systems operates is we are continuing to do research and development. We are always going to work with universities, research companies to keep on making sure that we're evolving this technology when it comes, and not everything we do research on is actually commercialized. We can learn things that prove what we thought was still true, and there's certain things where technology just hasn't caught up to affect ultrasound yet.

So what we're doing is we're trying to enable the worker, we're trying to make them more efficient and more effective. I'll give you an example: in our new Ultraprobe 15000, we believe that people don't need to be constrained by time anymore, or “I need to do this every month.” People are going to start taking data when they need it, based on some signals to, say, collect data. What we built in the 15000 is a very advanced processor and memory storage that allows us to transfer data wirelessly and go up to any point anytime and take that data, enabling that worker to make more efficient and effective calls.

So we're going to start to see the advent of technology that's going to push wireless, and I think is going to push processing power, to a new level. Every one of our new technologies has processing power that we're likely not using and I'll give you an example. Our latest wireless sensor that's coming out, we're going to be using from the get-go about 5% of its processing power. So what are we doing with the other 95%? I don't know! I can’t say that with certainty, but what I can say is from a future proofing point of view, we see artificial intelligence, we see neural networks, we see the need for processing power. And what we want to do is work with our customers saying, “you don't need to replace your technology, you just need to upgrade the firmware” and that's what we fully believe. We want to work with the customer for 10 years on that piece of equipment and make sure the decisions we make now from a technology point of view stand the test of time from what we can see in the in the near term future. Obviously I can't see 15 years out, I would love to, but I can definitely see some trends, and I believe battery power and processing power are going to be the two drivers that are going to enhance ultrasound technology.

About the Podcast
Great Question: A Manufacturing Podcast offers news and information for the people who make, store and move things and those who manage and maintain the facilities where that work gets done. Manufacturers from chemical producers to automakers to machine shops can listen for critical insights into the technologies, economic conditions and best practices that can influence how to best run facilities to reach operational excellence.