Smart Management for Damaged rail cars Elevates Efficiency
DB Cargo has implemented an intelligent damage management system to increase the availability and operational time of its freight wagons. The company manages around 200,000 freight wagons in Europe annually, with approximately 70,000 belonging to its own fleet. These wagons transport a variety of goods, including ore, coal, chemicals, and wood. In the past, damage to the wagons, such as defective brakes or graffiti, often led to inefficient reallocations, as the wagons were sent to the nearest workshop, which was frequently either overloaded or lacked the necessary repair facilities.
The new system aims to significantly improve this inefficient process. The new cloud-based application analyzes real-time data to automatically assign defective wagons to the most suitable workshop. Factors such as the type of damage, distance to the workshop, workshop capacity, and repair expertise are considered in the decision-making process. The goal is to significantly reduce wagon downtime and the number of reallocations. DB Cargo has already managed to reduce reallocations of freight wagons by 14% and downtimes by 20%.
Another feature of the new system is a simulation algorithm that uses real data to model potential scenarios for optimal workshop assignment. This helps evenly distribute workload across workshops and prevent bottlenecks. Tim Herbstrith, who led the development of the application on Detecon side, explains, “We developed a simulation algorithm that, based on real data, simulates freight wagons breaking down in different regions.” This simulation is crucial in determining the most efficient allocation of repair jobs.
The application also takes into account scheduled maintenance, such as inspections, and prioritizes urgent repairs, allowing wagons to be put back into service more quickly. Operational planning also benefits from the new system, indirectly supporting 15,000 employees.
Christian Kühnast, Project Manager at DB Cargo, highlights the advantages: “The project has made a significant contribution to increasing efficiency in our damage management.” By optimizing damage management, DB Cargo has been able to reduce wagon downtime and workshop visits, leading to greater availability on the tracks. This not only increases efficiency and revenue but also reduces CO₂ emissions by avoiding unnecessary transport.
What are the next steps? DB Cargo plans to further develop the system to enhance big data analytics. By capturing operational data and using artificial intelligence, damages can be predicted more accurately, and maintenance can be better planned. In the long term, the system could become an important tool in decision-making, contributing to making freight transport by rail even more efficient.
