Russia Deploys AI to Protect Heavy Mining Equipment

A steel plant in Cherepovets has introduced an AI-driven system that predicts motor loads and prevents breakdowns, reducing downtime and delivering significant economic gains.

The Cherepovets Steel Mill has improved the reliability of its Mill 5000 rolling line by deploying a machine learning model that helps avoid emergency shutdowns caused by electric motor overloads. In just the first half of 2025, the system cut downtime by 3.6 hours, generating an economic benefit of 4.53 million rubles, according to CNews.

Mill 5000 operates with powerful electric motors whose torque plays a critical role in equipment wear. Previously, operators calculated loads manually, relying on experience—a process that didn’t always ensure safety. Now, the AI system, based on gradient boosting, analyzes rolling parameters such as gaps, compression, and deformation modes to forecast motor load. If the risk of failure is high, it alerts the operator with yellow or red signals, enabling adjustments before production begins.

The system not only prevents breakdowns but also adapts to changing production conditions. This is a clear example of digital transformation delivering rapid economic returns. The project’s success paves the way for similar solutions across other industrial operations.