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Tyson Takes Computer Vision to the Chicken Plant

Tracking chicken inventory was traditionally a manual process where workers looked at meat wheeled in on carts, used hand signals to communicate information about the product to other workers, and entered data into a system. That process wasn’t always accurate. Incorrect counts could result in too much chicken being processed, meaning it could spoil, or an undersupply of chicken. Both problems could cost the company money.

Lee Slezak, Tyson's vice president of IT architecture, emerging technologies and analytics

Photo: Tyson Foods

“We’re trying to apply the most cutting-edge technology in order to derive new insights and enable new ways to work,” said Lee Slezak, vice president of IT architecture, emerging technologies and analytics at the Springdale, Ark.-based company.

The technology will allow Tyson to better control its inventory and manage the freshness of its chicken, said Mr. Slezak, who reports to Scott Spradley, Tyson’s chief technology officer. The move could result in some reductions in the number of workers, though that isn’t the main goal, Mr. Slezak said.

The company is investing in technology to improve operations as it faces volatile commodity prices, The Wall Street Journal has reported. Over the past five years, the company has spent more than $215 million on robotics and automation technologies, Mr. Slezak said.

Tyson, whose brands include Jimmy Dean, Hillshire Farm and others, said Thursday that profit rose to $557 million in its latest quarter, up 1% from a year earlier, as growing U.S. chicken production put a lid on prices. The company’s beef sales slipped 2% on weaker volumes, but sales of chicken increased 6%.

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Computer-vision systems, which use cameras and other technology to identify products, are relatively common in the food and beverage industry, said Kevin Prouty, group vice president at market-intelligence firm International Data Corp.’s manufacturing insights team. They are mostly used to validate correct packaging and labeling stickers on manufacturing lines that process products in large quantities, he said.

But over the past five years, the cost to install computer-vision systems has dropped by tens of thousands of dollars, Mr. Prouty said. That’s partly because good cameras are now more affordable, machine-learning algorithms are more advanced and data-management capabilities have improved.

“You’re starting to see cameras being set up everywhere to track every piece of production information they can,” Mr. Prouty said.

The inspiration for the computer-vision technology at Tyson came over a year ago after Mr. Slezak and his team visited an Amazon.com Inc. cashierless checkout store in Seattle, he said. Amazon Go stores use cameras and sensors to identify products that customers take off the shelves, automatically billing their accounts when they walk out the door.

Mr. Slezak and his team of data scientists and technologists sought insight from machine-learning experts at Amazon’s cloud services division and launched a pilot program last year based on similar technology.

The system identifies the type of product, such as a package of chicken thighs, and the stock-keeping unit, or SKU, number for the batch of products, using computer vision. An automated scale records the weight of a batch of chicken packages in the cart. An operator looks at a nearby screen and confirms the weight and SKU number.

The accuracy rate for identifying the product type and SKU number is in the high-90% range, using computer vision, an estimated 20% improvement over manual processes, Mr. Slezak said. Humans still validate some of the computer’s inventory tracking and train the algorithms, he said.

The computer-vision systems could also help detect foreign objects such as pieces of conveyor belt at facilities that process products at a high volume, which could be useful for food safety, he said. “We’re trying to apply technology everywhere we can as a company to drive down costs and drive up efficiency and business value,” Mr. Slezak said.

Write to Sara Castellanos at sara.castellanos@wsj.com


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