Rosatom has launched pilot tests of a predictive analytics system at three Russian nuclear power plants. The solution, built on the AtomMind digital platform, aims to detect equipment malfunctions before they occur.
The system is currently being tested at the Novovoronezh NPP-2, Leningrad NPP-2, and Beloyarsk NPP. It utilizes machine learning algorithms and neural networks to monitor technological parameters in real time.
The software identifies deviations, analyzes potential causes, and forecasts future equipment behavior. When anomalies are detected, the system sends notifications to personnel, who then decide on the necessary maintenance actions.
The primary goal of the project is to enhance equipment reliability and reduce the risk of failures. The technology also enables more precise maintenance scheduling based on the actual condition of the machinery.
The pilot phase is designed to evaluate the system's performance in real-world industrial conditions. Following these tests, Rosatom intends to further develop its predictive analytics capabilities and expand the technology across its nuclear facilities.
