The Journey to Digital
DB Cargo manages one of the largest fleets of locomotives in the world. Last year alone, its fleet carried 300 million tons of cargo, including autos, construction materials and consumer goods across Europe. To improve the service quality of this asset-heavy business, with some of these locomotives up to 25 years old and the infrastructure supporting them also aging, the organization embarked on an effort to digitize the fleet.
A key driver for digitization was a recurring situation in which a train driver would receive a failure alert during operation and call the technical helpline for guidance on the best possible action. These alerts were in some cases unclear, in others benign. But since the technical helpline operators had no visibility into the real state of the locomotive, they often had to recommend that the driver take their locomotive into maintenance due to safety reasons. This led to service disruption, with assets out of service instead of earning money.
The DB Cargo fleet is made up of multiple locomotive types from different manufacturers. A locomotive produces about 60 different time series values from sensors — ranging from temperature to rpm of the engine — and 7,000 different diagnosis or status messages. “We needed a solution that could handle large volumes of diverse data in real time, which made Splunk® Enterprise an obvious choice,” says Fabian Stöffler, vice president of asset digitization at DB Cargo. The company now uses the Splunk platform to provide real-time insights across fleet control, engineering, maintenance and operations.