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Manufacturers See Early AI Gains in 3 Areas

July 10, 2024
Automotive and gigafactory use cases center on safety, quality and efficiency.

Continuous optimization has been a key element of auto manufacturing for many years, so OEMs have process improvement in their institutional “muscle memory.” But now, automakers are reaching a plateau in terms of how much more optimization their current technologies and strategies can deliver to shop-floor operations.

To continue realizing efficiency gains, it’s time for manufacturers to develop a new type of muscle memory, using artificial intelligence (AI) and machine learning (ML).

AI and ML offer new opportunities for auto manufacturers to drive higher levels of production efficiency, overall equipment effectiveness (OEE), safety and quality on their shop floor than they've seen through traditional process improvement and digital upgrades. These benefits are among the reasons why the automotive AI market is forecast to grow at a 22.7% (CAGR) through 2030.

Lots of Experimentation

Although AI is evolving quickly, realizing the full scope of AI-related auto manufacturing improvements will take time. Right now, AI and ML adoption by manufacturing facilities is spotty and in its earliest stages. It’s an acute issue for legacy manufacturing facilities, but even new EV battery gigafactories are slow adopters, relying on muscle memory to guide their processes that is more aligned to traditional continuous improvement.

However, we’re already seeing organizations experimenting with these new technology tools on a case-by-case basis and initiating the change-management efforts needed to scale solutions. They are able to see how AI and ML can influence and impact their operational efficiency and raise awareness among key manufacturing leaders on the potential of these solutions on their overall operations.

About the Author

Bill Graca | Senior Director, NA Automotive, Capgemini Invent

Bill Graca is a senior director at Capgemini Invent North America within the automotive and manufacturing practice. He brings over 20 years of experience in formulating and leading the implementation of digital transformations. Prior to joining Capgemini in 2023, Bill worked in a variety of consulting leadership roles. He has also served as the CIO and head of strategy at a global technology services firm and led IT strategy for a large, global automotive OEM.

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