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Artificial Intelligence “Listens” to Machines to Predict Maintenance and Improve Efficiency

September 9, 2022 By Jeremy Jones, CFA

By Phonlamai Photo @ Shutterstock.com

A new trend among industrial companies is “predictive maintenance.” In order to better predict when machines need maintenance, artificial intelligence systems use sensors to “listen” to the machines and then analyze the data and changes in the sounds. Using the data, the AI predicts when maintenance must be performed for maximum efficiency. Angus Loten reports in The Wall Street Journal:

Startups that make technology designed to predict industrial equipment failures before they happen are seeing a surge in demand, as strained supply chains prompt manufacturers to squeeze more efficiency out of production lines, startup founders and analysts say.

Anna Farberov, general manager of PepsiCo Labs, the technology venture arm of PepsiCo Inc., said that over the past year so-called predictive-maintenance systems at four Frito-Lay plants reduced unexpected breakdowns, interruptions and incremental costs for replacement parts, among other benefits.

Developed by New York-based startup Augury Inc., the technology has helped Frito-Lay add some 4,000 hours a year of manufacturing capacity—the equivalent of several million pounds of snacks coming off the production line and shipped to store shelves, Ms. Farberov said.

PepsiCo is now sending the technology to most of its U.S. Frito-Lay plants, and plans to roll it out in its Southern U.S. beverage plants and eventually to all its bottling facilities in North America, she said. “We had a very clear business target to achieve,” she said.

Other manufacturers appear to be following suit. The global market for predictive-maintenance technology, also called machine-health tech, is expected to reach $18.6 billion by 2027, growing at a compound annual growth rate of just over 26%, according to data analysis firm Research and Markets. When Covid-19 struck in 2020, closing factories and disrupting shipping routes, worldwide spending on predictive maintenance stood at roughly $4 billion, the firm said.

Augury expects to add up to 50 new industrial customers by the end of the year, said Saar Yoskovitz, the company’s co-founder and chief executive. In addition to Pepsi, current customers include Colgate-Palmolive Co. , DuPont de Nemours Inc. and Hershey Co. , among roughly one hundred beverage and food producers, pharmaceutical firms, consumer packaged goods makers and other large-scale manufacturers, the company says.

Launched in 2011, Augury makes wireless sensors that attach to factory equipment and pick up the sounds they emit. The data is transmitted to its cloud-based platform and analyzed by artificial-intelligence software trained to recognize more than 80,000 industrial machinery sounds at various life cycles of operations—from functioning smoothly to falling apart—and overlays these sounds to detect patterns. Augury’s system then relays its insights to the plant’s maintenance team in real time, enabling them to better focus equipment inspections and get a jump on maintenance needs.

Read more here.

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Jeremy Jones, CFA
Jeremy Jones, CFA, CFP® is the Director of Research at Young Research & Publishing Inc., and the Chief Investment Officer at Richard C. Young & Co., Ltd. CNBC has ranked Richard C. Young & Co., Ltd. as one of the Top 100 Financial Advisors in the nation (2019-2022) Disclosure. Jeremy is also a contributing editor of youngresearch.com.
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