As part of the Power & Motion Insights video series, senior content director Bob Vavra discussed the present and the future of condition monitoring in the age of Industry 4.0 with Frank Mignano, condition monitoring manager for SCHAEFFLER Americas. They discussed how best to determine critical fluid power assets, how sensor and battery technology have evolved, and how modern systems capture and display data using machine learning and artificial intelligence. The interview has been edited for length and clarity.
Bob Vavra: From your perspective, why is condition monitoring so important?
Frank Mignano: I’ve been dealing with condition monitoring products, sales and application of portable continuous vibration systems for the past 30 years and for about all 30 of those years, there’s absolutely no reason a piece of rotating equipment should fail without notice. Every vendor has a version of that typically, and that allows us to see what’s going on with the bearings. We block out the low frequency things; we focus in on the condition of the bearings, gears and even lubrication. And there’s simply no reason why a piece of rotating equipment should fail.
If you do a criticality study of a plant, you become the maintenance manager. You’re responsible for now 5,000 assets. You go through a criticality study, and you define the criticality of the assets because the more critical it is, the more kinds of things you’re going to do to it. And typically out of that, 10-20% will be critical. You want to have some sort of online monitoring because that’s costly. Everything goes through that bottle filling machine or that extruder gearbox. And so that makes it critical.
But 60-80% of the assets would be the balance of plant. These are your process motors, pumps, fans, compressors. When you look at how to maintain balanced plant assets, the goal is to collect vibration once a month. That has provided tremendous value over the years, with great ROI (return on investment) on those systems. They’re still prevalent today, obviously.
But what Industry 4.0 does is, we amplify that. We have a much closer look as to what’s going on with that asset. Instead of getting one set of readings a month, we’re getting six sets every single day. Over a month, we’ll have a trend of 180 points. We now have a very, very good idea of the condition of that asset right up to date, right now, on your phone.
BV: You can monitor everything, but should you? How often do you do the six times a day versus one time a week versus one time a month? How do you do that deeper analysis into your system?
FM: Again, one of the things that I notice quite a bit these days is when you go out to visit facilities, there’s not a lot of people there. I mean, it used to be a department with three or four or five guys, and it’s one guy now wearing five hats, and he barely has time to have a sandwich in the middle of the day. So that’s one avenue that we address with these types of systems.
Data collects itself now and automatically analyzes itself, so this is a tremendous tool for industry. It doesn’t matter if you’re making potato chips, French fries, beer, cement, paper, whatever it is, there are process machines that need to be maintained because we all know that breakdown maintenance is the worst way to maintain your assets. It’s the most costly [method]. You have to fly parts in, you have to keep people late. And [the assets] always fail at 2 a.m. on Friday night. It’s just a rule of thumb. That’s what happens.
BV: Run to failure; I’ve never seen that as a particularly good maintenance strategy. It’s just a disaster. It increases cost and exacerbates safety problems. But there are machines on your floor that you can run to failure. So how do you section those off and what kinds of machines do you see are most likely to run to failure?
FM: To continue what I was saying before, 10- 20% [of equipment] would be critical, 60-80% would be the balance of plant and then another 10-20% would be run to failure because they have no effect on production. It’s a 10-hp motor; it’s not even worth the time to even stop and look at it. Run to failure is absolutely a good maintenance strategy for the right asset.
That’s why doing a criticality study is really important. It’s not only rotating equipment—you do it on instrumentation, you do it on tanks and vessels and piping. It takes all the opinions out of it. You say, “we have a failure that costs us over $50,000,” well, that’s critical. A refinery might be $250,000. Somebody making potato chips, it might be $10,000. So, you build a program for that site and, that’s what falls out of it. Run to failure is absolutely an acceptable strategy for those pieces of equipment that really are not having an effect on production and not very costly to replace.
BV: And you want to be able to take a look at the cost of having those replacement parts on site rather than carry that motor in your stockroom just waiting for something bad to happen.
FM: Exactly. That’s another opportunity to implement these types of technologies. Spares optimization—that is a huge opportunity to save money for a lot of sites. I know there’s a lot of good work's been done. A lot of our distribution partners can go out and work with end-users because a lot of times they have a big giant motor that has no place in the plant anymore because they’ve changed the process somehow. There’s no reason to keep this motor; sell it, write it off, get rid of it. You’re paying money to have these things in stock.
By implementing Industry 4.0-type technologies, you’re going to have the health of that asset right away on your phone; any changes, you’re going to know about it. And then we work with our distribution partners to ensure that the replacement parts—whether it’s a coupling, a shaft, a motor, pump, whatever it happens to be—are available and can get to the site by the planned outage day, and that the people who have the skill set to go do the repair are also available, typically during day shift when costs are minimized.
"That’s why doing a criticality study is really important. It’s not only rotating equipment—you do it on instrumentation, you do it on tanks and vessels and piping. It takes all the opinions out of it."
BV: Let’s talk about some of the new technology that’s out there. I know Schaeffler has OPTIME, your own wireless condition monitoring platform, but the idea of condition monitoring wireless battery-powered systems: What does that give the plant operations team, the maintenance team today, that they haven’t been able to have before?
FM: Constant, consistent coverage of the healthy asset. With the portable system, it’s manpower dependent and, unfortunately with COVID, people are out for a week or two weeks. It’s a critical time. You lose that monthly collection: It slips to six weeks, eight weeks. Then you’re moving into territory where these are just spot checks. There’s not a condition monitoring program anymore. We’re just walking around and seeing what’s going on today.
Then there’s hard-to-reach things—pumps, fans that are up three flights in cement mills. I don’t know if you’ve ever walked around those, but you got to climb a lot of stairs and there’s motors and fans on every deck. You just put a sensor in, you put a gateway nearby and, boom, the whole process is automated.
The other advantage of implementing these types of technologies is, it’s not to replace the people that are collecting the data. Now, we have an opportunity to take those people and have them work on more important tasks, such as why are we only getting two years out of this pump? You should get five to seven to eight years out of a motor pump.
It comes down to things like root cause failure analysis and doing precision maintenance. When you look at reliability as a whole, there’s so many components that all need to come together. And it’s really difficult to have a good reliability program because there are so many components. You go through the strategy, you define the work that you’re going to do…who’s going to do it? Is it electrical, is it mechanical, is it instrumentation? You get all that lined out and you have people that can go out and do the work. You have to train those people.
"Precision maintenance is a fantastic way to improve the skill set so that when they align something, we know that it’s aligned properly. We’ve just given that asset a better chance to live a long life."
BV: We’re talking about breaking down silos from between design and operations, between operations and maintenance, and really from the C-suite down to the plant floor. There’s always been disconnects and it’s been based on the lack of information that is available to everybody, so that everybody understands everything about what’s happening in the facility. And that’s one of the things that we’ve seen with concepts like machine learning and AI. They're now giving the right information to the right person in the right context so that they’re individually able to understand all the things they need to understand without having to worry about things that don’t really directly affect them.
FM: You know, that’s the beauty of these technologies. If I could put my Schaeffler shirt on here, with the OPTIME system, one of the unique things that we do is we provide actionable information. So, we’re not just providing a bunch of trends and time waveforms for the end-user to try and figure out what’s going on. Schaeffler has been developing and deploying condition monitoring for a long time.
And of course, we’re backed by a gigantic global bearing company. We’ve been making bearings for over 100 years, so we know a lot about rotating equipment and that knowledge has been put into the algorithms of OPTIME. We’ll take all this data and we’ll come back and say we think there’s a lubrication issue or we see bearing damage on this machine.
There’s a finite set of things that can happen out there. And once you know how to define those and the problems to look for, you put that into the algorithms and then these systems become a lot smarter. They’re available every day and up to date. Then you have actionable information.
Precision maintenance is a fantastic way to improve the skill set so that when they align something, we know that it’s aligned properly. We’ve just given that asset a better chance to live a long life.
BV: What’s the next thing that you see coming down the line, or are we just getting to trying to get better and better at this? Or is there something else that you see as the next generation of all this?
FM: That’s a good question. Some places only run Monday to Thursday. So, designing the sensors to adapt to specific applications—I think we’ll see that as we move forward; sensors that can determine that the machines are running, let’s collect data now rather than just on a schedule.
One of the things we’ve already added to our platform is a smart lubricator. There are a lot of single-point lubricators out in industry. One of the things that we're coming out with is a base unit for that which will automate that process as well. In addition to the condition monitoring of that asset, we’ll be able to tell what the status of that lubricator is. Is it full? Is it empty? Does it need to be changed? Is it clogged? What’s the temperature near that lubricator?
Then we’re going to go out from there as we listen to the voice of the customer. What needs are next? Do we want to integrate oil analysis systems? There are permanently installed analysis systems. Do we want to take that data and import that, put a chip on that, make it part of the family, make it part of the platform?
So, the sky’s the limit. It’s going to be based on what the customer need is, and then we’re going to go ahead and validate that and develop and add to the portfolio.
