5 Ways AI Makes Maintenance Better for Everyone

According to Rockwell Automation’s 9th annual State of Smart Manufacturing Report (opens in new tab), 2024 is set to see a notable surge in the adoption of AI tools—but what impact, if any, will they have on maintenance teams? And could these tools perhaps be the key to better maintenance in 2024?

While AI technology is still evolving, a surprising 83% of respondents anticipate using GenAI this year, propelling it to #1 on the list of 2024’s top technological investments. So as AI takes the manufacturing world by storm, let’s explore five ways the industry’s biggest challenges—and newest AI solutions—are set change the face of maintenance for the better.

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The State of Smart Manufacturing

Surveying this year’s State of Smart Manufacturing Report, it’s hard to deny that despite the many challenges facing manufactures, there’s a certain optimism that shines through. Faced with economic headwinds, labor shortages, skills gaps, and cybersecurity concerns, advanced technologies like AI are giving leading manufacturers hope. In fact, GenAI ranks #1 for investment dollars and #2 for ROI in 2024, just trailing Cloud/SaaS platforms. That’s an interesting turn of events, because it wasn’t so long ago that most players in the space were skeptical, even a bit afraid, of AI.

“Over the past number of years,” says long-time Fiix veteran Sandy D’Souza, “it seems like there’s been an element of distrust around AI and an element of the unknown.”

But faced with new challenges, the conversation is shifting. Now, Sandy says, instead of focusing directly on the technology, people are asking, “How is AI technology ultimately going to transform and improve and make the life of the human beings who are actually working on the plant floor better?” Naturally, this got us wondering how AI technology can ultimately benefit maintenance teams.

People are asking, ‘How is AI technology ultimately going to transform and improve and make the life of the human beings who are actually working on the plant floor better?’

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5 Ways AI helps maintenance teams

Inspired by this year’s report, we’ve identified five benefits of AI for maintenance that we think really rise to the top:

1. Finding anomalies in a sea of maintenance data

As today’s manufacturing operations grow in complexity, the amount of data generated daily grows to a scale simply unmanageable by humans alone. AI really shines in digesting huge quantities of maintenance data—such as sensor data from a motor or temperature data from a PLC—and identifying the anomalies that could indicate failure. This is precisely the method employed by Fiix’s predictive maintenance solution, Fiix Asset Risk Predictor. The sooner anomalies can be detected, the sooner they can be resolved through preventive maintenance, averting asset failure and unplanned downtime.

2. Increasing efficiency through automation

Much of the work that maintenance technicians perform on a daily basis is extremely valuable. Other work, not so much. Creating work orders, analyzing data, generating reports; all these tasks can now be done by AI tools, freeing up valuable technician time to focus on the purely value-adding activities and making the most of your scarce labor resources. Speaking of which….

3. Filling labour shortages and knowledge gaps

With the recent rise of accessible prescriptive maintenance tools like Fiix Prescriptive Maintenance, generative AI can now be trained on asset and maintenance data to produce detailed, complete, and accurate work orders. Not only does this save time, easing the pressures resulting from a shorthanded labor force, but it can go a very long way towards filling in the knowledge gaps left by attrition and a rapidly changing technological landscape. Simply put, we’re at a point where AI-powered tools can increasingly complement humans in many of your daily maintenance tasks, serving as an expert co-pilot for your team.

Generative artificial intelligence (GenAI) rocketed up the technology priority list over the last twelve months, creating fierce demand for industrial applications embedded with this transformative technology
– SoSM, pg. 4

4. Improving data integrity

Like any human activity, manually gathering maintenance data and collating it into reports carries with it the real risk of human error. That also means the risk of compromised decisions based on bad data. And at its worst, these errors can lead to the stockouts and miscommunications that bring production to a grinding halt. To ensure your data is always of the highest integrity, consider using an AI-powered analytics tool to automatically collect, analyze, and action your data. Plus, it’s a lot faster to use AI than assembling these reports by hand.

5. Tracking progress on operational goals

As the saying goes: You can’t improve what you don’t measure. Fortunately, the AI built into many modern solutions like Fiix CMMS is always running, collecting and analyzing your maintenance data. With each closed work order, your team is adding to the wealth of intelligence that AI analytics tools can use to generate insights on important metrics like OEE and other KPIs. And this in turn means solid data and which to make the decisions needed to drive your maintenance program forward.

Turning AI Inspiration into AI Action

These are all great ideas, of course, but they don’t mean much without effective implementation. And that means contending with change management. As Sandy says, and many maintenance teams know too well, “it’s really hard to orchestrate the change inside an organization so you can ultimately adopt the new technology.”

When asked how teams can truly make change stick, Sandy suggested that teams reframe the motivation behind adopting new technologies. “Where I’ve seen successful change management occur,” he says, “really boils down to the business case behind ‘how is this technology ultimately going to transform and improve and make the life of the human beings who are actually working on the plant floor better?’”

Not only does this put a justified focus on the human impact of new technologies, but Sandy believes that “when framed up in that context, it tends to become a lot easier to get buy-in across the organization and certainly a lot easier to get a deployment off the ground.”

How Fiix is Supporting Maintenance with AI

For maintenance teams just coming around to the idea of AI, figuring out where to start can really be bewildering. Fortunately, it’s never easier to experiment with AI and the many ways it can help you harness the power of your data.

Fiix CMMS already makes use of AI as part of its Fiix Foresight analytics tool, analyzing your maintenance data to surface insights on work orders, assets, parts inventory, and more. But with last year’s release of Fiix Asset Risk Predictor, we’ve taken things to a whole new level, introducing the world’s most accessible, affordable, and complete predictive + prescriptive maintenance solution.

With the emergence of AI and especially GenAI technologies, strategies like prescriptive maintenance have suddenly become highly accessible to maintenance teams—and highly effective. “Rather than having to rely on somebody coming through with an instruction manual and asset manual, et cetera, or going on the Internet to find that information, what if you had a tool that could automatically mine some of that information?” Sandy asks. With this new technology, Sandy says, Fiix will “mine historical data and present it to you so that now you can focus on the task at hand rather than doing some of that research and doing some of that grunt work.” Whereas it used to take a Fortune 500-size budget and a team of data scientists, this new generation of AI-powered maintenance solutions can be implemented in just two weeks. Plus, they’re budget friendly.

“As we think about the benefit of prescriptive maintenance,” Sandy says, “it really is that copilot that works alongside the people on the factory floor who are doing the maintenance and acting as a tool, as an aide to really help everybody get their job done better.” Among AI’s many capabilities, prescriptive maintenance might be the single most transformative for maintenance teams in the coming years. And to think this was simply out of reach for most teams before the advent of GenAI!

Much like this year’s State of Smart Manufacturing Report, Sandy ends on a hopeful and human note: “Ultimately, I think where we see success is where clients have successfully articulated the human benefit of these technologies across the organization, and thus enabled the change to take effect and achieve a successful deployment and successful results.”

Download the full SoSM report now to find out what’s working for leading manufacturers. Plus, get a 10-step checklist for technology adoption success.

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