Case Study: ENGIE achieves predictive maintenance at power plants with Amazon Web Services

ENGIE Digital Uses Amazon SageMaker for Predictive Maintenance at Power Plants

ENGIE wanted to improve predictive maintenance across its power plants by developing, training, and deploying machine learning models that could anticipate equipment breakdowns and malfunctions while keeping costs and resource allocation under control. The company turned to Amazon Web Services, using Amazon SageMaker with support from AWS partner Mangrove to scale its predictive maintenance efforts.

Amazon Web Services helped ENGIE Digital build models for predicting equipment lifespan, detecting anomalies early, and using IoT sensor data to assess equipment health. With Amazon SageMaker, ENGIE gained a scalable, industrialized platform to better plan maintenance cycles, reduce unplanned shutdowns, and support its energy transition by making thermal plant operations more resilient and efficient.

ENGIE

Céline Mallet

Head of the Predictive Maintenance Platform Agathe