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Parallel Session

CT-02 – From Preventative to Predictive Maintenance: IoT is on the Right Track with SNCF Rail Assets Monitoring

Congress Connected Transport

Tuesday 29, 17:30h - 18:15h Room 4
17:30 18:15 Europe/Madrid CT-02 – From Preventative to Predictive Maintenance: IoT is on the Right Track with SNCF Rail Assets Monitoring

France's public rail company, the Société Nationale des Chemins de fer Français (SNCF) has a keen focus on innovation. The company manages the scheduling, operations and maintenance of a network covering 30,000 km of track, 15,000 trains and 3,000 stations in France. This session highlights the journey of migrating from preventive maintenance to current IoT predictive maintenance using non-intrusive mobile sensors and deep-learning algorithms to detect alerts and predict diagnosis and consequences. SNCF has set up a Digital Open Lab (DOL) to foster open innovation and develop interest from the Industry. After one year of the DOL, results are encouraging. Meanwhile, the maturity of the IoT technology and the ROI of the use case will be presented. Discover how, by life observation and predicting maintenance requirements, SNCF can have a more efficient supervision, and prevent outage on the network.  

Room 4

France's public rail company, the Société Nationale des Chemins de fer Français (SNCF) has a keen focus on innovation. The company manages the scheduling, operations and maintenance of a network covering 30,000 km of track, 15,000 trains and 3,000 stations in France. This session highlights the journey of migrating from preventive maintenance to current IoT predictive maintenance using non-intrusive mobile sensors and deep-learning algorithms to detect alerts and predict diagnosis and consequences. SNCF has set up a Digital Open Lab (DOL) to foster open innovation and develop interest from the Industry. After one year of the DOL, results are encouraging. Meanwhile, the maturity of the IoT technology and the ROI of the use case will be presented. Discover how, by life observation and predicting maintenance requirements, SNCF can have a more efficient supervision, and prevent outage on the network.  

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