RUSAL Deploys AI to Boost Efficiency and Product Quality in Aluminium Production

RUSAL, one of the world’s largest aluminium producers, has rolled out two advanced AI systems — machine hearing and machine vision — across its production lines to improve efficiency, reduce costs, and enhance product quality.

The Russia-headquartered company said the new technologies are being used in alumina production and aluminium melt preparation — two of the most critical stages in the production process.

The machine hearing system applies mathematical algorithms to analyse acoustic vibrations from milling operations. By interpreting these sound patterns, the AI can optimise bauxite ore loading, reduce energy consumption, and minimise equipment wear.

The system is trained to distinguish meaningful signals from background noise, maintaining the precise mill load needed for energy efficiency, consistent grinding, and equipment safety.

In alloy production, RUSAL has implemented a machine vision-based AI system to oversee aluminium melt preparation — a process involving up to 20 sequential operations. The neural network assists operators in achieving the correct alloy chemistry and identifying impurities that may affect metal quality.

“The system, which operates using machine vision, reduces the impact of human error as it helps the operator not to miss key moments during alloy preparation, and to better identify the areas of dross on the hot melt surface to improve the efficiency of its cleaning,” said Mikhail Grinishin, Director of Production Automation at RUSAL’s Engineering and Technology Centre.

RUSAL continues to expand its use of in-house AI technologies across operations — from smelter sealing and electrolysis control to logistics and raw material quality analysis — reinforcing its position as a global leader in digital aluminium manufacturing.