Fleet Management 2.0

There is no doubt that the fast-moving world of artificial intelligence (AI) is upon us. What IBM defines as “technology that enables computers and machines to simulate human intelligence and problem-solving capabilities” is just as quickly being deployed in the systems and solutions used to manage commercial equipment operations.

The subject of how AI will continue to impact fleets was front and center at the 2024 EUFMC where Kenneth Jack, CEO of KenetIQ, discussed recent advancements in chip technology, increased accessibility to AI and how businesses looking for new efficiencies are thinking about where and how the technology could benefit their bottom line.

“Applications for AI technology include camera and telematics data from equipment, online technician training, predictive maintenance, repair effectiveness analysis and lifecycle planning,” Jack said. “Recent advancements that are bringing the discussion to the front lines involve more practical, efficient, accessible and affordable chip and AI technologies.”

AI driven systems and solutions, according to Jack, can be used to evaluate tasks such as work scheduling and Generative AI, like ChatGPT, can be used to write bulletins, outlines and reminders. For technician training, the technology is increasingly able to better tailor material and possibly predict maintenance issues.

“AI is definitely something to ask about if you are using or considering fleet management or telematics systems,” Jack added. 

Jack went on to advise fleets to ask several questions, including:

• Is there an opportunity to tie AI systems into other initiatives?
• What data do you have already that could benefit from the use of AI, such as maintenance, driver and fuel information?
• What specific problems could AI help solve?
• What is the cost of implementation, software and training?
• How do you determine if it’s working?
• Are there options to do something small and low cost in parallel with existing systems?
• Is my team or company ready to try something like this?

Jack has vast experience as an energy, telecom and transportation executive. As mentioned above, he currently serves as the CEO of KenetIQ, a company that provides innovative solutions for fleet optimization. His background also includes serving as vice president of national fleet operations at Verizon, and he spent time as the general manager of transportation operations and as the section manager of substation planning at Con Edison. He has served as an independent director at Lightning eMotors, on the board of directors of the NAFA Fleet Management Association and on the General Motors EV Vision advisory board.

Recently, Jack sat down with Crane Hot Line to discuss AI in more detail:

Q: How will AI technology change management practices for commercial assets?

AI seems poised to change how managers consume information about operations. Today, specialists cull through data and pull reports, but more and more AI systems are popping up that quickly cut to the chase, tell you what’s going on and can interact with you in plain language to help you rearrange or coordinate work in different ways. AI will also change how we spot trends in the performance of equipment and make better decisions about what to fix, replace, retire, etc. and when.

Q: How does the integration of telematics systems and data facilitate more effective and advanced management?

There’s so much telematics data from hydraulic systems, diesel engines and computer controls that it can be hard to know if you’re missing something or if there’s a bad trend, and that costs time and money. Experience has taught us how to read data from all kinds of sources and what decisions to make or actions to take but we can only pour over so much information before we need to make daily decisions.

We rely on our experience and knowledge to help guide us through what’s mission critical and where we can make decisions that are directionally correct. But imagine being able to process every data point and interpret its effect on your business and make better decisions to improve safety, reliability, efficiency or profitability. As AI can learn, you may have that opportunity in the not-too-distant future.

Q: How will AI advance the goal of achieving truly predictive maintenance?

More and more, systems can learn from the collective performance of components in the field. Self-diagnostics that talk to the cloud can learn the best maintenance practices given your environment, duty cycles, etc. based on the collective experience of literally every similar machine.

We expect more from our hardware so imagine equipment that, along with AI, can tell you just the right maintenance interval and what to do next time it’s in the shop to avoid a breakdown and to maximize your earnings on the machine between maintenance cycles. It’s already happening in industrial and manufacturing settings, and I think we’ll see more of this in other kinds of operations. It doesn’t replace a good operator, a good mechanic or a good scheduler yet, but it could help you get more done with the resources you have today.

Q: What should operations look for in terms of AI from their current system providers or solutions they might be considering?

If you’re using any kind of system ask your provider where AI is on their product roadmap. What kinds of features do they anticipate having and when? If you can see an important business impact from those features, hold the software supplier’s feet to the fire regarding when they’ll have the feature and how they’ll guarantee accurate advice and benefits. Talk with your IT manager about if and how they see benefits from AI impacting your business.

It’s not all roses and bags of money tomorrow, but don’t discount it and remember that eventually your competitors won’t either. AI is going to be a strategic eventuality you should anticipate at some point in your future.