Podcast: Preparing for 2025 — What’s next for the manufacturing industry?
If 2024 was the year when the hype cycle for industrial AI hit its peak, what is in store for industry in 2025? Plant Services recently sat down with Aaron Merkin, Chief Technology Officer of Fluke Reliability, to get his insights and predictions on where manufacturing is headed. Merkin brings more than two decades of experience developing enterprise software across a variety of industries and markets, including roles at IBM, Dell, ABB, Aclara (now Hubbell), and Honeywell.
Below is an excerpt from the podcast:
PS: We're heading toward the end of the year, and the start of a new year. My first question is going to focus on trends that you're seeing in industry, perhaps in this year and going into next year. You work with a wide variety of manufacturers in nearly every industry and vertical around the globe. What are some of the key trends that you're seeing right now in manufacturing?
AM: The first is still the continued focus on digital transformation. Customers are looking to more instrument their plans, collect more data and use that stream of data they’re getting from IoT solutions to inform the decision making. It's been challenging times, and customers are trying to decide where to invest in terms of improving operations and improving reliability. That ability to have data allows them to improve their decision making, and it’s also accelerating a shift towards predictive maintenance. We see that customers are recognizing that by having instrumentation in their plant, they're able to better predict the health of assets and they're able to incorporate that into their short cycle planning for when they're going execute work in the facility. It's really prompting them to be much more aggressive in adopting predictive maintenance.
The second thing we've seen is continued concerns about supply chain resilience. We've had disruptions over the last few years coming from COVID and we’re still recovering after that. There's also a lot of uncertainty around reshoring and trade headwinds, and whether you’re going to be able to continue to rely on the suppliers that you've had overseas, so you see customers focusing on how to address that. The mitigation that they're looking at taking is adaptability and transparency into their supply chains – looking for alternate suppliers outside of potentially problematic countries, and looking to dual-source their suppliers for critical equipment.
More important is a look at effective inventory management, and how do they make sure that they have the right parts on hand when they need them, and at the same time balancing and minimizing the amount of inventory that they're holding. We see a lot of efforts looking at how they can incorporate AI into their supply chain planning, in their demand for parts, as well as for predictive maintenance – that ability to detect faults and plan for when you're going to have outages or predict when you may have an outage, which allows you to optimize the inventory you have on hand rather than being in reactive break-fix mode.
PS: It's been a weird year for manufacturing in the sense that I think a lot of manufacturers have been waiting (in the U.S. at least) for the Fed to cut interest rates, and we're starting to see that happening. As you were saying, supply chain is still weighing heavily in people's minds. We hear various stories where some supply chains are ironed out to where they were approximately pre-COVID, others are still sort of evening themselves out. What do you see specifically as the biggest challenges that are facing manufacturing coming into next year?
AM: I think one of the things that we've seen with manufacturers is the pace of technology change, the amount of information around generative AI, and the idea that we’ve hit an inflection point where if you're not already using GenAI over the last five years then you must clearly be behind.
We've seen a ton of pressure on manufacturers, particularly at the plant level, not just to analyze technology but to come up with a plan to adopt it whether it’s clear how they're going to use it or not. Irrespective of the problem that the end customer is trying to solve, we see RFPs and questionnaires asking for AI solutions, whether they're necessarily the appropriate solution or not. Our customers are really feeling this pressure to not be left behind and we encourage them to not fall victim to the siren song of being on the bleeding edge of technology, but instead really to focus on making sure that they understand the business outcome that they’re trying to achieve. Then as an organization you identify the business outcome, stick to working on your business priorities, and then work backwards to understand what the technology is that you need to address them.
Part of that is making sure you're not adopting technology for its own sake. Also because we're seeing such an incredibly fast pace of technology change, it's almost inevitable that you're going to define a problem, you're going to adopt technology, you'll run your pilot, and by time you complete that pilot something new or shinier has come along. You get tempted to keep chasing the latest leading edge technology and never actually quite go into production, versus really understanding the business outcome you're trying to achieve and then, once you're confident that the technology you've chosen accomplishes it, go straight into production usage.
PS: We're also hearing that people feel pressured to adopt “AI something.” With AI as maybe part of your answer, what emerging technologies do you see that are on the horizon that actually will revolutionize or change manufacturing?