Case Study: VINCI achieves faster trainline monitoring and predictive maintenance with ForePaaS

High-Speed Trainline Monitoring And Predictive Maintenance

VINCI, through its subsidiaries Mesea-Lisea, needed a better way to manage the LGV high-speed rail line between Tours and Bordeaux while meeting strict service-level commitments and reducing costly incidents. To support infrastructure monitoring, train identification, and maintenance optimization, VINCI worked with ForePaaS to unify more than 20 fragmented data sources, including IoT, meteorological, maintenance, and SNCF communication data.

ForePaaS, together with partner Eleven, provided an end-to-end data and AI platform covering collection, storage, exposition, and model training/run. The solution enabled VINCI to deploy a first demonstrator in less than 6 months and later launch a predictive maintenance phase; as a result, 20 different data sources were collected and processed into a 100% operational product.

VINCI

Philippe Sergent

VP Performance