Client

SNCF - Industrial and Engineering General Directorate

SNCF - Industrial and Engineering General Directorate (DGII ME), is a key division within the French National Railway Company (SNCF). This division is responsible for overseeing the industrial and engineering aspects of the railway network, ensuring the maintenance, optimization, and innovation of the infrastructure and rolling stock. Their focus is on enhancing the efficiency, safety, and reliability of the railway system through advanced engineering solutions and predictive maintenance strategies. This project with DGII ME highlights their commitment to leveraging cutting-edge technology to improve operational processes and deliver superior service to their customers.

Context

In its approach to optimizing predictive maintenance of its railway network, SNCF needed a system that could automatically associate measurement and control data with the corresponding locomotives. The challenge was to accurately identify trains with technical anomalies to improve the responsiveness and efficiency of maintenance interventions.

Solution

In collaboration with the DGII ME department, we participated in the development of SYRENE (System for Recognizing Engine Numbers), an innovative solution. This solution relies on a high-definition image capture system installed along the railway tracks. The captured images are then processed by an optical character recognition algorithm specifically designed to identify the numbers of moving locomotives. All data is accessible via a modern web interface that allows teams to efficiently visualize and analyze the collected information.

Result

The implementation of the SYRENE system enabled complete automatic identification of locomotives running on the network, thus eliminating the need for manual recognition. The monitoring of rolling stock maintenance has significantly improved thanks to the precision of the collected data. Intervention times have been considerably reduced, with the precise localization of failures allowing for quick and targeted action by maintenance teams. The user interface, developed according to the latest ergonomic standards, offers teams quick and intuitive access to essential data. This solution has also led to notable optimization of maintenance costs through better anticipation of intervention needs.
This project perfectly illustrates the use of computer vision technologies to improve industrial processes in the railway sector.