A wake-up call for industry

Sept. 24, 2020
In this sponsored feature, we talk with Paul Galeski, founder of Maverick Technologies, about what lessons industry will take away from the COVID-19 pandemic

"What happens when everyone calls in sick? It’s just not a question that we ever asked.”

That’s how Paul Galeski characterizes the stunning wake-up call faced by manufacturers and processors when the coronavirus (COVID-19) pandemic struck earlier this year. We recently had a chance to chat with the founder of Maverick Technologies, a leading provider of automation services and strategic manufacturing solutions, to discuss nothing less than the future of industry and the continued importance of the automation professional. Read on to learn more of his seasoned perspective and “fitness” prescription for moving industry—and the profession—forward.

Paul Galeski

Founder, Maverick Technologies, and Vice President and General Manager, Rockwell Automation’s Control Products and Solutions Business

Q: In some of your recent musings, you've noted how we as an industry, especially those who specialize in automation, were caught unawares by the pandemic. In what ways do you think we didn't have our act together but thought we did? And how did we get it so wrong?

A: Yeah, it's pretty crazy. Talk about a paradigm shift. I won't say we got it wrong; we just didn't get it right. We looked at the world through the same manufacturing automation lens for the past 50 years. But, just like the army’s always equipped to fight the last war, we were unprepared for the new enemy that showed up. With the onset of the pandemic, we’ve needed to attack and manage in a very different way. And it's a more all-encompassing way.
We've done a good job of solving the problem and the challenge as we understood it—the efficiency of global manufacturing, of American manufacturing, has never been better. But our notion at Maverick is that industry needs more than just automation, and that’s where we fell short. Industry needs something we’re calling flexible, intuitive technology (FIT).

Q: This more all-encompassing view of automation and technology also entails a shift in perspective regarding the collaboration of people and machines. How does our view of that relationship need to change?

A: Well, first of all, we've got to do a better job of defining their respective roles. Think in terms of an org chart: each player should have defined roles, responsibilities and job descriptions. When it comes to a manufacturing environment, I don't know that we've done a good job of defining the role of technology versus that of labor, management or any number of external players. So, before we can go out and become FIT, we must develop that whole mosaic of roles and responsibilities. Once we define those purposes, then we as an industry can start to solve the interactions.

Q: Agility and flexibility have been a priority for industry for many years. What really makes FIT different than the old paradigm of being more flexible and agile?

A: In my experience, our view of agility has been too unidirectional. Sure, we implement changes we think will make our operations more agile, but as we move forward, we need a feedback loop that says, "Okay, we were agile, but we weren't quite agile enough. So, what made us not agile?"
And that's where the intuitive piece comes in. It’s not the open-loop environment of the past, but an environment that helps us continually learn as we go and get better with use.
The way I look at the world, there are two kinds of businesses: those that get better with use like Google or Amazon, and those that don't. We
really haven't fully explored—and certainly haven't implemented—the full complement of artificial intelligence and other tools that are very common in other industries and environments. We've got a huge opportunity for growth, and those kind of things are what makes FIT different.

Q: Can you give some specific examples of how a manufacturing environment might learn and adapt to changing conditions in real time?

A: Let’s just say we've got a pair of pumps that start misbehaving. One is surging and the other is carrying a heavier amperage load than the other, and back and forth they go. They're kind of getting sick, and ultimately a pump or valve fails. Eventually, we wake up, see what the problem is, and fix it. That's open loop, and we keep charging forward again until something else goes wrong.
Well, here the software needs to learn what happened and, when it sees it coming again, make adaptations to the process itself or bring in the human factor. And as we continue to adapt the process, the software will eventually get to the point where it can come up with many solutions to a particular problem.

Q: So leveraging more machine learning, AI-type technologies to do more closed-loop adaptations that are above and beyond what we'd normally do just with a PID loop or even an advanced control algorithm?

A: Yes, exactly. And to provide more contextual information to the human factors that are involved in this organization that we talked about. So, the technology has its role to bring those things bubbling up to the person's attention. And I'm not talking about an alarm that says, "Okay, the valve is closing. It's supposed to be open." That's easy and it’s old news. But what were the factors that led up to that? The operator or the maintenance technician needs to get the backstory to help them see what happened, and potentially feedback a better resolution before the failure, before the process interruption, before the potential safety breach.

Q: So what's next? We're six months into this pandemic and apparently still have some ways to go. What do manufacturers and processors really need to start doing now to first make their way forward through this, but also to be prepared for the next unanticipated thing—whatever that is—coming out the other side?

Well, let's start with what not to do, and that’s go in and make a bunch of changes because you think you know what you need to do. Certainly, if there are necessary safety issues that you’ve learned of, you go solve those.

But before you make a major initiative to take your systems, process and enterprise forward, take a step back, and recast everything in this new COVID-19 pandemic light. How does that change the landscape? How does it change our priorities? Do a risk-reward analysis, do a SWOT analysis in this new light, and see what you come up with.

Much of what we've done over the past years and decades will still be part and parcel of this exercise. But there's this whole new category, this whole new group of things that we need to be thinking about that we didn't see before.

Also, make sure you've got the right people in the organization that can drive this new paradigm. People who have an open mind, and really don't accept business as usual. People who are willing to say, "Hey, folks, the way we've been doing this ain't gonna work anymore."

How are we going about strategic planning? How are we developing our strategic roadmap? What are the big-picture items that we need to do? Because once we develop a what, we're usually pretty good at getting at the how. But if we don’t get the what right, and don't think about it in a big, free-thinking way, then the how is going to miss the target just like before.

For more information on Maverick's FIT paradigm, experience the company's interactive whitepaper at

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