Case Study: Swiss Federal Railways SBB improves train operations with MongoDB Atlas

Swiss Federal Railways SBB saves months of development time with MongoDB

Swiss Federal Railways SBB faced significant inefficiencies in its train cleaning operations due to non-uniform train configurations, tight schedules, and variable passenger traffic, which made pre-planned cleaning highly inefficient. The company also struggled to track the real-time location of train engines and cars within its large yards, a process previously managed with error-prone Excel spreadsheets. To address these challenges, SBB partnered with MongoDB and implemented solutions using MongoDB Atlas.

Using MongoDB Atlas and its Atlas Device Sync feature, SBB developed the Cleaning 4.0 app to calculate real-time cleaning requirements and a track mirror app (Gleisspiegel) for real-time location tracking of assets. The solution provided cleaning crews with synchronized task lists via a mobile app and gave all staff a unified, real-time view of train locations. MongoDB's technology saved SBB months of development time by eliminating the need to build complex backend APIs and conflict resolution systems. The applications increased operational efficiency, minimized downtime, and enhanced asset accessibility, with the cleaning app planned to go live in 2024.

Swiss Federal Railways SBB