By all indications, the use of artificial intelligence to improve manufacturing operations has reached something of an inflection point.

In a new Manufacturing Leadership Council survey on Transformative Technologies, about half of manufacturers said they believe that, over the next five years, AI and machine learning will be game-changers for their companies.

Twenty-six percent said their companies will invest in AI and machine learning tools, techniques, and skills over the next 12-24 months.

And, on a recent MLC Critical Issues call, manufacturers detailed some of their early AI projects and the positive impact these projects are having on their companies’ quality, asset utilization, performance, and productivity. One large industrial has created AI algorithms that allow it to not only monitor continuous processes but to predict when those processes are about to break down due to material variation or other factors.

Similarly, this company is also using AI to predict quality problems. Next, it plans to use the technology to assess and predict asset performance with an eye toward improving asset utilization.

Already, as a result of its AI implementations, this company is seeing a 40%-50% reduction in process variability, a 5% improvement in asset uptime, and a 10%-20% improvement in base productivity.

Another manufacturer, this one in high tech, has been able to predict semiconductor die failures well in advance of electrical testing by using AI to understand and learn from detailed die images. The company is also using AI to learn from the production tool acoustic signatures and to predict failures before they happen. So far, this company reports a 35% reduction in quality events, and a 10% improvement in manufacturing output.

By virtue of such breakthrough initiatives, both of these companies were winners of Manufacturing Leadership Awards in 2018.

These examples, and others like them, convinced us at the Manufacturing Leadership Awards to increase our focus on AI in 2019. We upgraded one of the programs award categories to specifically target outstanding AI projects. (You can read the description for the new Artificial Intelligence and Analytics Leadership Category—and all of the categories for the 2019 ML Awards—here.)

Our goal in creating the AI category is to encourage manufacturers that are doing great things to share what they have learned. And, of course, winners in this category will receive global recognition as a leader in the application of an exciting Manufacturing 4.0 technology.

As encouraging as the above success stories are, it’s also clear that most manufacturers are in the early days of pulling value out of AI. Most still need direction on where the greatest opportunities lie and on what  challenges they can expect. Effectively identifying, collecting, and managing the vast quantities of data needed to power successful AI projects, for example, has been a common challenge. So is keeping algorithms up to date with operational and competitive changes and finding people with the right skills.

If your company has successfully addressed these challenges, we encourage you to share your stories by nominating your AI project for a 2019 ML Award. It’s a great way to get recognized as a M4.0 leader while also helping to move manufacturing forward.