Case Study: ENGIE achieves predictive maintenance savings with AWS Glue

ENGIE Digital Uses Amazon SageMaker for Predictive Maintenance at Power Plants

ENGIE Digital, part of ENGIE, needed a scalable way to build and deploy predictive maintenance models for its power plants and B2B customers so it could anticipate equipment failures, optimize maintenance cycles, and control costs. To support this effort, ENGIE turned to AWS Glue alongside other AWS services such as Amazon S3 and Amazon SageMaker.

Using AWS Glue for data integration and preparation, along with Amazon SageMaker for model training, ENGIE Digital was able to develop and train more than 1,000 predictive maintenance models quickly and securely. The solution is expected to connect nearly 10,000 pieces of equipment within five years and deliver estimated savings of €800,000 per year, while helping reduce unexpected shutdowns and improve maintenance planning.

ENGIE

Mihir Sarkar

Chief Data Officer