Cordiant enhances manufacturing reliability using AI

Cordiant has implemented digital vision technology at the rubber mixing stage of the Gislaved tire plant in Kaluga to ensure uninterrupted delivery of chemical component packages to the conveyor, eliminating the need for constant visual monitoring by operators.

The quality control automation system is based on an industrial computer and a USB camera, with its key component being an ML model—an algorithm for machine learning that, according to the company, “analyzes numerous examples and learns to independently distinguish normal conveyor operation from abnormal situations.”

The camera operates at 10 frames per second, and the model detects the presence or absence of a package, while also collecting data on conveyor speed and identifying the beginning and end of the work cycle. If a package continues to be detected in the monitoring zone several seconds after the conveyor stops, the system sends an alert to the industrial computer.

The system is fully autonomous, and the manufacturer claims its use completely eliminates the need for constant visual monitoring by operators and prevents unscheduled downtime at the production stage. In addition, it creates a database for further analysis.

Previously, “smart” cameras capable of recognizing over 30 tire sizes and types were installed at the Yaroslavl Tire Plant, which is also part of Cordiant. Cordiant’s CEO, Dmitry Gorbachev, noted that the holding is implementing several large-scale projects “that allow us to manage the efficiency of the entire production cycle in a completely new way.”

“We are paying special attention to automation at every stage of quality control, increasing process transparency, minimizing losses, and setting a new standard for digital quality management in the Russian tire market,” he added.