Aaron Merkin is Chief Technology Officer at Fluke Reliability, and he is responsible for the development and execution of industrial IoT strategies. Aaron is an experienced technology executive with a deep understanding of technology and product strategy, solution architecture, M&A, and organizational transformation. Plant Services Editor in Chief Thomas Wilk recently spoke with Aaron about the changing landscape of industrial maintenance, including remote condition monitoring, supply chain disruptions, and industrial cybersecurity.
PS: Could you tell us a little bit about yourself and some of the projects that you're working on at Fluke Reliability that relates specifically to the maintenance sector?
AM: Certainly. I'm the CTO for Fluke Reliability, and have been with the business about 11 months. I'm responsible for all of our hardware and software engineering and product development, with about two decades experience developing enterprise software and solutions across a variety of industries in the last decade or so, specifically serving asset-intensive industries developing MRO solutions. Here at Fluke Reliability, we're focused on two major areas. We have a large CMMS offering called eMaint, to help out with daily maintenance activities and predictive maintenance activities. On the other portion of the portfolio, we're very much focused on condition monitoring, and that's a combination of remote condition monitoring services offerings as well as route-based and continuous vibration monitoring solutions.
PS: That (twin) offering covers so many bases when it comes to a full-blown reliability system that can pull the data in, help analyze it, spit out reports, send alerts. That's part of the reason I appreciate you being on today's podcast because you and the team sort of cover so many areas of what's coming, but you have to be ready in all areas for the innovations.
AM: Indeed. Historically, this has been an industry particularly in the use of vibration for condition monitoring that's been heavily targeted at experts, requiring many, many years of training and hands-on practical experience. And we're looking forward to applying advanced technologies such as AI and ML, to make that same type of vibration-based condition monitoring available to non-experts.
PS: Oh, cool. Well, let's hang on to AI and ML, we'll get to that later in the podcast. I wanted to start with a topic that our readers tell us is important, especially during the pandemic right now. Suddenly, there's been a strong interest in remote condition monitoring for obvious reasons: if you can't get somebody on-site, how do you set up a system? So given that we saw a strong interest emerge in the past 18 months, what do you see driving remote condition monitoring in 2022? How do you see it evolving in the coming year?
AM: I think we'll see that because of the inability of people to be on-site, I think there's sort of a secular trend which is the graying of the workforce, and a lot of people heading towards retirement. That was accelerated quite a bit with COVID in terms of people really rethinking just, in general, their life choices, and how much they want to continue working, or if they want to ease into retirement. As well as with health concerns, people not being comfortable going on-premise, and going into facilities and performing maintenance activities. I think we've seen a sort of an acceleration and an interest at looking into alternatives rather than using their own staff to do maintenance inspections on-premise.
And as we've sort of been through the peaks and troughs of COVID, particularly when we were going through the large area of uncertainty, there was a lot of interest in RCM, in remote condition monitoring services, but not necessarily an ability to actually take advantage of them because of the travel issues and access issues. Now the vaccination rate's coming up, and people are getting more comfortable with reopening their facilities, I think is when we're going to see in 2022 a significant adoption of those services. The end of 2021 was really learning what it's all about, and what are alternatives for how we can perform these maintenance activities and monitoring. In 2022, we'll see now people taking advantage of that, as I said, and maybe starting to see a sharp uptake in services.
PS: Interesting. One of Plant Services' missions is to help provide our readers and industry in general as much information about these sorts of new topics. And it sounds like that education effort industry-wide is well underway, people have been looking at it for a while. Do you think that the average plant is probably poised in '22 to take stronger action?
AM: It's a great question. I think that there's a broader understanding of the availability of these services in both the RCM aspects as well as a bit more of the transition to continuous monitoring versus route-based. I think there's certainly room for more education and more awareness to be raised about the breadth of the assets that can be covered, as well as the affordability of the services themselves.
PS: Yes, that's an issue too, costs can be variable for these kinds of situations. A lot of times when we survey our readers, Aaron, what we find out is that they're not really sure how to quantify the benefits of solutions like this. And so, costs can be an obstacle, especially if they're not sure what will the return be? How are we going to get it back?
AM: I think what we have is, we have an understanding that planned downtime is better than unplanned downtime. And it's the ability to perform preventative maintenance, particularly less maintenance activity, less engineering resource effort, as well as potentially with lower-cost parts, that is inherently better for a business than having an unplanned outage and having to perform major repairs to the system. There's a concurrent trend which is supply chain limitations, and one of the areas that we're seeing is that, if we're able to provide you through RCM (or a customer or a plant supervisor) to have an earlier lead time of a fault, then they're much more likely to be able to order the parts that they need and have them in-house and be ready to be able to schedule the repair before that fault actually occurs and takes down the plant, and they have a significant line down while they're trying to deal with supply chain issues and get repair parts in.
PS: For our listeners, we're recording this podcast right before Christmas, and Aaron, the supply chain topic makes me think about the toy shortage we were all worried about. We haven't felt it here in Chicago so much, we were okay. But where I see it all the time actually is baseball cards. It's such a minor thing.
AM: Oh, really?
PS: Yeah, the Topps company releases their yearly set in two different waves. And we found a lot of the first wave before the summertime, but now for the second year in a row we haven't seen the second wave, and we're not sure what the supply chain issue is. Whether it's a delivery issue, whether it's a cardboard shortage, or whether it's a choice by Topps to say, "Okay, sales weren't great in the first half, so now let's dial back in the second half." Though it's just interesting how one little thing like that can sort of stand-in for such a large issue.
AM: Yeah, certainly. Within Fluke Reliability broadly, we've had significant supply chain challenges. It's been an ongoing activity. And you and I discussed, even earlier this week, we were supposed to meet to record this podcast, and I, unfortunately, had to bail out so I could go deal with some of our own supply chain challenges internally. It’s definitely been an interesting 12 months or so, and it looks like it's going to stay this way. I mean, we're forecasting continued supply chain challenges through the end of '22.
PS: Yeah, that's an issue that's even more foregrounded in our readers' minds than even remote condition monitoring. Since you mentioned eMaint before, can you talk a little bit about how an EAM system can help bring reliability back to the supply chain, the impact that it can make when it's all being done right?
AM: I think the key thing on the reliability side is that in order to have an effective maintenance program, you need to understand what preventive maintenance procedures need to be run, and you need to know when you're going to run them. Ideally, when there's a lot of work being done, particularly in the RCM side to transition from meter-based to time-based maintenance and to condition-based maintenance. But still, if you have all that condition monitoring up-front, or you have your meters coming into a system triggering the maintenance program, if you're not actually effectively tracking and performing that maintenance, then knowing that you need to do it is only half of the solution.
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A software tool like eMaint is really there to help you perform, track, and execute well the PMs that need to be done. We also see the application of AI and ML in that space as well. Again, the advantage of a SaaS platform such as eMaint is with large datasets we have PMs being done for a wide variety of assets. We're able to start looking at comparing best practices across multiple customers, as well as looking for which PM routines are constructive for a given asset class. You're actually seeing an improvement in reliability asset in which a PM routine is actually potentially disruptive. I don't know about you, but when I perform my maintenance routine at home, I feel like there's always that one screw left over that I forgot where it goes back to.
PS: I know. Where did it come from, right? Always. There's something left over.
AM: And so one of the things that we're looking at is exactly on the PM side, is a similar thing. The OEM will tell you, “here are the routines you should perform” but it's quite possible that they're not necessary because they're not really contributing to the health of the asset, or potentially that, as I said, you're cracking the system open into performing some maintenance on it is actually ultimately leading to a long-term degradation of its reliability. So we see that the structure of the PMs and eMaint, and the application of AI and ML as being the basics of PM being a firm foundation for reliability, and it being a starting point to actually do PM optimization over the long term as well.
PS: That's really fascinating. A lot of the AI and ML use cases that we've encountered at least have been to predict the imminent failure, to identify the anomaly. What you're talking about is an intriguing new case, this is the first I'm hearing about it, where you can identify the harmful work – not just work that's no longer useful, but work that may actually be introducing the faults.
AM: We think about asset performance management broadly, the evolution of reliability, again, away from sort of the time-based, and scheduled PMs into condition-based and prescriptive maintenance driven by AI and analytics. What we've seen is that the kernel of it, the nugget of it is really what we might consider asset health, and that is this condition-based predictive maintenance, using condition monitoring to do predictions of the asset health. But the evolution of that is, as I said, ultimately PM optimization in deciding which maintenance routines really are the ones which make sense to be done because it's improving the health versus, as I said, the ones which could be set aside. There's also some room there as well, if you have a large enough fleet of assets to start doing some comparisons, both in terms of not just, “is this PM routine effective or not?” but with detailed work instructions in the capturing of the PM in a work order and a tool like eMaint, you can start doing analysis to determine if two different entities or two different maintenance crews are performing the same PM, looking at the variation between the actual execution of the PMs, and seeing which of the PM routines is more effective at improving the asset health as well.
PS: That's fascinating. I can see why AI and ML made your 2022 trends list because we're talking not just about the conventional applications. It occurs to me too that when it comes to PM optimization, one of the challenges is always getting the workforce on board with it, because you’ve got the anecdotal case of say you've got a time-based maintenance round that's in the system, it may not be useful anymore and the people walking around might know it, but they may want a little 10-minute break, so they go ahead and do the round anyway. It could be a case where you've got someone new, and you put them on lubrication duty, and all they do is they go and squirt some grease into the bearing – if it leaks, who cares, if it doesn't leak, who cares? They know that they just did it on time. Do you see AI and ML giving teams a chance to sort of tighten up their approach to maintenance, and avoid these kinds of issues where the workforce mindset might change towards more of a reliability mindset?
AM: I think there's certainly opportunity in the sense that by having the larger datasets and being able to look for variation in the performance of an asset after a maintenance routine, to try and identify common root causes. Certainly the toolset will enable a workforce to be more effective, but there’s fundamentally a significant change management activity that needs to be undertaken by the leadership of that maintenance team because of the things you're alluding to: “this is the way we've always done it, and we think this is what works, and you're bringing in a tool and the tool is telling us to do something different.” People need to be educated as to maybe not all the underlying math, but being given a bit of background as to what have we looked at, who are we benchmarking you against, and why do we think that what the tools is telling you to do is actually correct, even if the recommendations may fly in the face of your anecdotal experience? So I think we see that the adoption of more sophisticated planning and analytics tools powered by AI and ML will require change management champions within reliability organizations to see widespread adoption.
PS: Do you see AI and ML helping teams embrace a more proactive mindset especially if they want to? Or do you see AI and ML having an effect where it's really going to spread across proactive, some reactive, and some time-based tasks, where eventually we're going to see applications for this leading technology to be applied not just in the cutting-edge areas, but on everything people are doing anyway right now?
AM: I think certainly in the near term, what we see is the use of AI and ML democratizing expertise, taking a maintenance organization that is already interested in improving reliability, and making them able to scale their existing expertise and scaling different resources to really take on the balance of plant. Every facility has their handful of critical assets, and then they have the balance of plant assets as well. And if you've already got a proactive mindset towards reliability, probably focused on your most critical assets, we see that the use of advanced software solutions, or potentially the adoption of RCM by a third party, allowing you to apply that proactive mindset to the balance of plant.
And then I think over time, you'll see, there's always in every industry that I've served and that I've built solutions for, there's always your leading lights, your lighthouse adopters of technology, who set the gold standard that other people fall behind. And I think that's what we'll see here. We'll see the people who already have a proactive mindset aggressively adopting the AI- and ML-based solutions or RCM solutions to get to balance of plant, and then the people who are taking a wait and see attitude, when they see that it's successful, then they'll come behind it as well.
PS: Aaron, let me ask you one more trends question, and this one's on cybersecurity. A year ago, we did our cover story on drone attacks and physical security, because there had just been a drone attack on Saudi Aramco a couple of months previous, in 2019 I believe it was. Suddenly, after that SolarWinds happened, and there hasn't been any more dramatic physical attacks, but cyberattacks are making daily headlines. Is cybersecurity now so baked into what people are doing, with remote condition monitoring, with machine learning and AI, with EAM systems, that as these conversations develop within plants, with service providers, is it now baked in enough that people have a reasonable expectation that what's in the market is going to be as secure as it can be?
AM: I think it is table stakes expectations, and rightly so of customers of solutions like ours, and of any SaaS or remote management solution that you have a very high bar for cybersecurity. But I think it is still a differentiator in the market, it's still something that as a security service, you should be poking on and pushing on your vendor to ensure that they are meeting your expectations. Cybersecurity is inherently a risk, and it can't ever be 100% mitigated, but there's some basic groundwork that should exist in any vendor. And there's a lot of room to continue to provide best of breed capabilities in cybersecurity to protect your assets, protect your customers, your customers' assets. I don't know if it's not being talked about because it's taken for granted, but certainly it shouldn't be taken for granted. It should be something that as a customer you are pushing on your suppliers to ensure that they have high standards.
PS: It's just funny that for a while there, it seemed like it was the hot topic, and it hasn't gone away exactly, but I appreciate your perspective on that. We've been hearing too that people are embracing the idea of that without a response plan also, you're not really cyber secure, because that response plan helps drive things like effective backup systems.
AM: It's interesting that you mentioned that, because there was a vulnerability announced last Friday in a software utility called Log4J. For us, we immediately triggered our incident response program, and we had our head of cybersecurity, our head of production operations, and a large portion of my engineering team working around the clock, starting as soon as that announcement came out to remediate the issue. In our case, we immediately took the required steps to mitigate the risk, and we're still in the process now of doing the after-action reporting and retrospectives to see how we could have handled it better.
PS: On a consumer level, the way it impacted my life was that my kids wanted to play Minecraft Java Edition, which is only available over PCs. The version they've got in their Xbox right now apparently is unaffected by this flaw, but if you had the edition for Java, that was where the error was creeping in. Thankfully, it's something they want from Santa, so they don't have it yet, and I'm glad about that.
AM: They may be merely downloading an update for it as soon as they unwrap it.
PS: Oh, gosh, they we're yelling like crazy, "why is Fortnite taking 45 minutes to update?"
AM: This is why it's something that is table stakes, and that as a customer, you should be able to take for granted. But practically speaking, it's an evolving landscape, and it's always important that you do check with your vendors, and you're comfortable that they have the right practices in place. And it should be one of your decision criteria before purchasing a particular solution.