AI central to Nestle’s innovation overhaul

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BARCELONA — Nestlé SA has accelerated its product development process by 60% since 2016, according to the company. Reduced time to market by restructuring the R&D process. Today, the company is investing in various forms of artificial intelligence (AI) and machine learning to further improve its research and development processes and produce better results.

“We actually changed the average project duration from 33 months to 12 months, which is the average for different categories,” said the chief technology officer at Nestlé’s Investor Day on Nov. 29. Stephen Palzer said. Sometimes projects only take him six to nine months, so he’s moving at a faster pace than most startups right now. “

The first accelerated schedule was developed by simplifying Nestlé’s overall research and development process. Project approvals have been cut from his six “gates” to three, and the company has established 14 of his R&D accelerators around the world. There, product development takes just six months ‘from idea to product’ and product testing takes place under real conditions. .

The use of AI is spreading across organizations and is being used in a variety of ways, including concept development, formulation development, plant breeding, clinical data mining, raw material quality assurance, advanced process control, and early detection of problems.

“We established an artificial intelligence concept engine that translates[social media]insights into concept suggestions that are then evaluated by employees,” said Palzer.

Approved concepts are prototyped and tested. As part of the prototyping process, you can use another AI module that streamlines the formulation development process.

Palzer said AI and machine learning are now the necessary product development tools to address the growing complexity of the product development process, where products must be delicious, healthy, sustainable and affordable. emphasized.

“We need artificial intelligence tools to deal with this complexity,” he said. “For example, we have developed a clinical data mining approach that allows us to make new discoveries based on existing clinical studies. We are making new discoveries and new inventions.”

Beyond product development, Nestlé is also using AI to improve manufacturing efficiency. Some of the company’s KitKat production lines are self-regulated, Palzer said.

“These lines have loops to detect product quality, measure wafer attributes, for example, and undo processes,” he said. “So it’s a self-regulating mechanism. But we’ve also developed a machine learning approach for preventive maintenance, for example, so we can reduce downtime on the line.”

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