Startups developing 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 efficiencies from 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, predictive maintenance systems at four Frito-Lay plants have reduced unexpected failures, disruptions and overtime costs for spare parts, among other things have other advantages.
The technology developed by New York startup Augury Inc. has helped Frito-Lay increase production capacity by about 4,000 hours a year — the equivalent of several million pounds of snacks coming off the production line and being delivered to store shelves, Ms Farberov said .
PepsiCo is now shipping the technology to most of its U.S. Frito-Lay plants and plans to roll it out to its southern U.S. beverage plants and eventually all of its bottling plants in North America, she said. “We had a very clear business goal to achieve,” she said.
Other manufacturers seem to be following suit. According to data analytics firm Research and Markets, the global market for predictive maintenance technology, also known as machine health technology, is expected to reach $18.6 billion by 2027 and grow at a compound annual growth rate of just over 26%. When Covid-19 struck in 2020, shutting down factories and disrupting shipping routes, global predictive maintenance spending was about $4 billion, the company 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 officer. In addition to Pepsi, current customers include Colgate-Palmolive co
Dupont de Nemours inc
and Hershey co
among around a hundred beverage and food manufacturers, pharmaceutical companies, consumer goods manufacturers and other large manufacturers, according to the company.
Launched in 2011, Augury makes wireless sensors that attach to factory equipment and record the sounds they emit. The data is streamed to its cloud-based platform and analyzed by artificial intelligence software trained to recognize more than 80,000 sounds from industrial machines in different operational lifecycles – from working properly to falling apart – and to overlay those sounds to recognize patterns. Augury’s system then relays its insights to the facility’s maintenance team in real time, allowing them to better focus equipment inspections and meet maintenance needs faster.
Other tech startups offering similar predictive maintenance technologies are C3.ai inc,
DataProphet and Senseye. While the technology isn’t new, rising demand – fueled by additional supply chain disruptions in the wake of the Russian invasion of Ukraine and ongoing Covid-19-related shutdowns in China – is making these and other startups increasingly valuable to manufacturers.
Senseye, a UK-based predictive maintenance software developer, was acquired by Siemens in June Inc
. Announcing the deal, Siemens said that Senseye’s technology can reduce unplanned machine downtime by up to 50% while increasing maintenance staff productivity by up to 30%. Terms were not disclosed.
When Augury raised $180 million in a Series E funding round in October – taking its private market valuation to over $1 billion – its lead investor was oilfield giant Baker Hughes co
Another was the corporate venture arm of Schneider Electric SE.
Under the terms of the deal, Baker Hughes took a seat on Augury’s board of directors. It also signed a multi-year commercial agreement, Augury said.
In May, Augury itself acquired Seebo, an AI-based process intelligence startup, for more than $100 million.
Augury chief Mr Yoskovitz said his long-term goal for the company is not to be acquired by a giant manufacturer or IT vendor, but to go public “when the time comes”.
Large IT vendors are increasingly offering their own predictive maintenance tools, increasing competition in an already tight market.
“The value of startup vendors like Augury originally lay in the combination of hardware and software solutions for predictive maintenance, particularly based on machine learning,” said Emil Berthelsen, vice president and analyst at IT research and advisory firm Gartner inc
By using multiple data sources, such as historical and operational data, acoustic sensors and imagery, Berthelsen said, “the quality and level of insights from predictive maintenance continue to improve.”
Warren Pruitt, Colgate-Palmolive’s vice president of global engineering, said the company has turned to predictive maintenance tools to improve machine performance and reduce machine fleet count. The company used to rely on preventative and calendar-based maintenance for device management, he said.
Colgate-Palmolive has deployed Augury’s platform at all of its plants in North America, as well as many in Europe, Latin America and Asia, he said.
“Our predictive maintenance program also educates our workforce and gives our employees the breadth to look at the big picture and consider how they can leverage new technologies and initiatives to continually improve our operations,” said Mr. Pruitt.
write to Angus Loten at [email protected]
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