DB Cargo has implemented an AI-supported system to improve the provision of spare parts for locomotives. The initiative is taking place at the DB Cargo Railport Darmstadt, south of Frankfurt, and involves around 60 Class 77 diesel locomotives, according to the company.
The project has been called Spare Parts Forecasting 1.0. The choice of the Class 77 is tied to the fact that they were built in Canada, making the delivery a long process. “Traditional forecasting methods reach their limits here because many parts are only needed irregularly”, DB Cargo added.
AI-supported forecasting introduces the concept of targeted availability, with easily available parts “planned more leanly” and parts more expensive and difficult to get are “reliably secured”. Moreover, the model provides information on mileage and maintenance levels creating the conditions for better forecasting.
The oil pump case
One example of how implementing this AI-supported model in Darmstadt has improved forecasting of spare parts is the case of oil pumps. “While the old method did not identify any demand, the AI model predicted five units – actual consumption was six. With delivery times of around 500 days, this determines whether a vehicle is out of service or remains operational”, DB Cargo explained.
