Eurofins TestOil VP of Sales and Marketing Mike Barrett recently sat down with Plant Services Magazine Editor-in-Chief Thomas Wilk for a podcast filled with insights derived from decades of experience in oil analysis. Topics included what makes programs work, what trouble spots programs run into, and where listeners can improve their own oil analysis program. Here is a transcript of the conversation between Mike Barrett (MB) and Plant Services (PS)
MB: I would say that the financial cost to get involved with oil analysis is virtually nothing. You know, there's not a lot of upfront investment to buy any sort of hardware or software to get involved. It's really a matter of getting sample bottles from the lab, taking an oil sample, and sending it in. Everybody, I think, at this point realizes that the benefits of oil analysis are significant in keeping your equipment up and running and essentially extending oil changes. Those are the two main reasons why you do oil analysis. People understand that, and when they're looking at which technology should I get involved with, there's nothing upfront financially to purchase to get involved with oil analysis. Vibration has hardware/software, infrared has hardware/software, ultrasound has hardware/software, so it's more of a financial commitment. I think it's pretty easy to get a program going. But to keep an effective program alive is much more difficult.
PS: Before we started recording our conversation, you mentioned that there are a lot of complementary technologies, like those three you mentioned, to oil analysis. That isn't to say that oil analysis is superior to the others, but like you said, it's a good entry point to folks trying to get perhaps more proactive, more predictive about their maintenance scheduling.
MB: Yes, it's really all about predictive and condition-based monitoring. When I started, there was no such thing, people just would take oil samples, and if they found a problem, maybe someone would make a corrective action and fix it. As we developed reliability centered maintenance practices, the philosophy changed in that you would want to look at your individual equipment in the plant, and then do a sort of reliability assessment and say, how can this equipment fail? What are the specific faults that can cause it to fail? And then the idea is, ok now we're going to take a predictive technology that can find that fault.
You can have a lot of faults and maybe oil analysis is never going to find a specific fault on that failure, so you wouldn't want to implement it. But a lot of our customers have gone through the reliability process and understand their faults. What I see is vibration and oil analysis working together to find a lot of machine faults.
Misalignment is probably the biggest. Vibration would pick that up, oil analysis picks that up, and when you get a high wear metal count and you get a high frequency on your vibration, a corrective action is go out there and take a look at the gearbox, and ask is it out of alignment, and we fix it by putting it back in alignment. It's that kind of thinking that has developed from the early 1990s to today, so they are complementary in that fashion.
PS: Let's get to the real meat of our discussion about programs. That's something you've been specializing in for decades now, and I'm excited to hear from you some of your insights with meeting so many plant teams in developing so many oil analysis programs. In your opinion, are there one, two, or three things that you think that make a program work? We can talk about the risk points later on, but let's start with what works.
MB: I can give you four right off top my head. (1) We set up like five programs a week, and the ones that work, and what is most important, is you have an owner who's in charge. Who's the champion of the program, who's got some passion about oil analysis?
(2) Two is, do you stay in compliance with taking your samples? We get programs that start all the time, and say, these 30 machines we're going to sample monthly, these 20 quarterly, these 50 twice a year. Do you stay in compliance on that sample schedule? (3) The third is, how are you getting your samples? Do you have a good sample point so that the samples we are getting are producing good data? And is it a consistent person who takes the samples?
If we can get a good sample, and you're doing it on a set schedule, and you have someone who's passionate about it, who likes looking at the reports, then I guess the fourth would be, (4) are you taking corrective action? We find problems all the time. You send me 100 samples, and I'm going to find 30 problems. But are you actually doing anything to fix those problems? Because you're going to send me those same 100 samples next month, and I'm going to find the same 30 problems. And then I'm going to raise my hand and say, what are we doing here? Why are we taking samples if you're not going to fix anything? If you have those four things, you have a good program, when you don't have those four things, it's not as good.
PS: I'm struck by that last one, especially. We can talk about the first three points, that's all about conducting the oil analysis work. But that fourth, I've heard so often, where if there's not a way to translate the data you receive from the samples into effective corrective action, you may as well have not done the work. You may as well just burn the money. Whether it's a CMMS system, whether it's even a paper tracking system, there's got to be a way, a mechanism in place to trigger work.
MB: To trigger work someone's got to put a corrective action into the CMMS. But what I see is, people don't even know what the corrective action should be. We may find a fault on a specific sample, and maybe it's high iron, or high copper, or high water, or whatever it is. They may not have enough knowledge in oil analysis to take that report and understand it and say, hmm, this is the corrective action I need to put in.
And it's interesting, because we have a services group that goes out to the field and takes samples. They're around the equipment all the time, and this is a huge benefit of oil analysis, it forces you to go out into the plant and be around your equipment. There's so much knowledge you could pick up just by smelling and listening and touching. These guys in the field can get a lot of knowledge around the equipment, but then when they come back, and the analysis is done, some of these customers have these guys actually enter work orders into the system, because all the customer wants is to fix problems we find. Once the work order is in their system, somebody's got to fix it, so they eliminate that sort of paralysis of looking at a report and not knowing what to do, because our guys around the equipment, they get a report back that says, “hey, you know, you had high iron” and because they're around it, they'll say, “well, yeah, when I was around it, the thing was shaking like a tree, so it's misaligned.” That's what the work order should be. If you have someone like that in a plant, who's got the knowledge of what a report means, who's been around the equipment and can understand it, then it's easy to get a work order into the system. But that's a big problem.
PS: Would you say in terms of your recipe for program's success, that the responsibility for that part of success lies with the project champion? Is it the champion who is supposed to look ahead and forecast these potential pain points, especially the last one and say, okay, we do have to have a system in place to get work scheduled as needed, not just sampling?
MB: In our industry, there's MLA certification – Machinery Lubrication Analyst, MLA – so that is someone who can understand a report. Someone on the team should have an MLA certification, because they're the ones who are going to be looking at these reports, and being able to translate it into a work order. It may not be the champion. The champion just has to be passionate about a program and keep it running, and keep the sample compliance on track. Because eventually, what happens, and I see it all the time, is we have a great champion, and then he switches jobs, either within the company, or leaves the company and goes somewhere else. And all of a sudden, you lose a champion, and then you start to see the sample fruit frequency diminish, because someone's not as interested as the champion who started it.
PS: That was a smooth transition into what are some of the challenges? Are there other common challenge points that you see? Do people have trouble taking the same sample from the same location? Is it even before the sampling process takes place? It is issues with making sure the oil is clean before it goes into machines? What are some of the more common ones?
MB: Yeah, a lot of it is from start, setting up the equipment database. We need an equipment roster to get set up before we can do anything. Sometimes it's as simple as they send us the roster, and we don't even have lubricant, we don't even know what oil is in there to start analyzing. And they don't even know, which is even worse. That's a big problem to start.
And then it's really, where do you get a sample from? Has anyone been trained on how to take a proper sample? The good programs typically have sent their team to training for MLT training (Machinery Lubrication Technician), and those are the guys out in the field around the equipment taking the samples. Getting a consistent sample is a big challenge. And, you know, it's not a fun job for people. People aren't raising their hand to say, “I want to go out and pull 100 samples every month, that sounds like fun.” So, it's a challenge, and what happens is, you get different people taking the samples, who do not take it the same way, who do not take it in the same spot. So, then you get variance in the data that we're sending back to them. We have a couple of customers who have dedicated people who take samples, and they may have to take 400 samples a month, and there'll be two or three of them, their team, and they're paid on sample compliance. They get bonus based on hitting 98% sample compliance. Now, our analysts look at these reports all the time from them, and when someone goes on vacation, they fill somebody else in to take the samples, and the analysts all of a sudden are looking at the reports and saying, wait a minute, why is all the data out of whack? Either someone's not putting the right labels on the bottles, or someone's taking samples in a different spot. It's so crucial to get consistent sample taking, and even sample takers. That's a problem because you just don't get consistency in the program. I would say Tom, it comes down to training. When we started this back in the 1990s, there was no training and there weren't really trade shows. It was a lot of education we were doing. And then in 2000, you start to see training programs develop, and conferences. Today, there's a heck of a lot more training and there's all sorts of people certified MLA / MLT. It's really nice to see, I guess, but there's still so many plants who are starting programs, and they don't even know what MLA and MLT are.
PS: You’re framing that perspective for me, because I joined Plant Services in 2014, not even 10 years ago. And I look at say the Reliable Plant conference, which has been around for 25, 26 years?
MB: 1999 is when it started, I believe.
PS: It feels to me like the show has been around forever, and it's all I know, but clearly 30 years is not forever. It's still a relatively new science in a lot of ways, or discipline I should say,
MB: It is, and that show has exploded from when it started back in 2000 to where it is today. It’s international, you know, and when it started, it was a little show out in Tulsa, OK, and you'd get 100, 150 people there, and now you get 1,500. It's nice to see, there's a lot of awareness around lubrication, keeping your oil clean, lube rooms. People don't understand the importance of having a dedicated room to keep your new oil, and having processes in place to filter it. I walk into plants all the time, and one of the things I ask is, let's go look at your lube room. And they'll say, well, we’ve got a barrel sitting over there, and there's a barrel in that corner. And whenever they need oil, they just come and get it out of the barrels. It's hardly a lube room. That's just part of the whole lubrication processes, are you putting clean, dry oil into your machines.
PS: One of the first eye openers for me was understanding how quickly oil can get contaminants in there. And contaminants don't even have to be that large, of course, it's just a matter of, if they're not kept in a clean, dedicated lube room, it's going to be a challenge to keep even filtered oil clean.
MB: It is. I mean, you have a system and you have a filter on it, you could have pretty clean oil in that machine. And now all of a sudden, you're taking new oil that you think is clean, and you haven't filtered it, and you're putting it into the machine, you're putting dirty oil in on top of clean oil. That was a big problem, but part of these conferences in the early 2000s really stressed this whole cleanliness issue of oil. And that is very big, I mean particle count is a test we run that looks at the overall cleanliness of the oil. In the past that was done on turbine oil or hydraulic oil only. Now we have customers who have big gearboxes, and they want to know how clean their oil is, because they will filter it to improve the cleanliness, and they'll give us a target cleanliness code to say, “we want to keep the oil below that; if it goes above it, you need to flag it, because then we'll bring in a filter cart and filter the oil, because it's so important to us to keep it clean.” But that mentality wasn't always there. And it's the training and the conferences that has helped that.
PS: It's good to see that plus people like yourself and the programs you’re developing that have driven this to where we are today, which where we can talk about some of the some of the pinch points and some of the ingredients that go into making a good program.
MB: It's cool, some of the things we do with customers now. A big thing is data ingestion; some of these bigger corporate accounts have that we do multiple plants for, they have people corporate guys who don't want to sit there and look at oil analysis reports. They could look at 400-500 in a month, (but instead) they want to take the data, and they have some sort of AI / Power BI type of platform that they can bring the data into, and maybe integrate it with vibration data or infrared data, and do some sort of analysis to really pinpoint the machines across the fleet that are having problems. It’s not just looking at an oil analysis report from a gearbox at a power plant. It's much, much bigger thinking.
PS: Let me close our interview with a cost question. You mentioned that this is one of the more cost effective or the most cost-effective predictive maintenance approaches. If a champion wants to start a program or even approve the program, and they get challenged by their superiors to estimate the ROI, is this is the kind of thing where the average technician or champion can identify an ROI pretty quickly via oil analysis?
MB: It's not that easy. It's easy to look at eliminating oil changes. Most people have time-based oil changes, we change our oil every year. If you implement an oil program, you should eliminate that immediately, and say we're only going to change the oil when the reports tell us to change your oil. So, you could look at that cost savings. Now, the other big savings is increased equipment reliability, which means less maintenance costs and more productivity. That is harder to determine an ROI. You could say, we're going to have more equipment uptime. Well, how much more? Can you translate 5% more uptime into 5% more productivity output? That's part of the ROI. It's been difficult to do because it's a cost savings based on a piece of machine not failing, if you're doing oil analysis. You could look at it, all of a sudden, we get a report back and you have high iron, and you say, “you better go out and check that gearbox.” So, you go check the gearbox and say, “oh, if we didn't come out here, check it and do this, it would have failed in two months and cost us $100,000.” So doing oil analysis just saved you $100,000. People understand it, but it's hard to put it on paper.
PS: You almost have to look at something like mean time between failure, and look at that time stretch first before the dollar figures come back, when it comes to uptime and downtime. I hear you loud and clear that the most immediate cost savings that can be calculated on paper would be freeing up resources from doing regular time-based sampling and saying, ok, we reduce these routes, now these folks can go work on other jobs.
We want to thank Thomas Wilk and Plant Services for giving us this opportunity! Link to podcast: https://thetoolbelt.podbean.com/e/tips-and-tricks-to-improve-your-plant-s-oil-analysis-program/.
About Eurofins TestOil
With more than 30 years of experience in the oil analysis industry, Eurofins TestOil focuses exclusively on assisting industrial facilities with reducing maintenance costs and avoiding unexpected downtime through oil and fuel analysis program implementation. As industry experts in diagnosing oil-related issues in equipment such as turbines, hydraulics, gearboxes, pumps, compressors and diesel generators, Eurofins TestOil provides customers with same-day turnaround on routine oil analysis testing. For more information on partnering with Eurofins TestOil on oil analysis programs or training opportunities visit https://testoil.com. Contact: Michael Barrett 216-251-2510; email@example.com.
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