Bettina Lamprecht

Digitization is the key factor for process optimization at DB Cargo

Post from 17. December 2020

Every day, DB Cargo operates 2,732 trains to provide an appropriate range of rail cargo services (source: Deutsche Bahn Facts & Figures 2019). To ensure the smooth transport of goods, processes need to run at the optimum level. Innovative capability and implementation strength form the driving force for this. This is why the DB Group has launched the corporate strategy Strong Rail, in which digitization plays an extremely important role.

In his position as Senior Project Manager at DB Cargo, Mr. Kühnast ensures digital transformation within the company. In an interview, he told us more about the digitization at CB Cargo.

Unexpected failures or malfunctions of rail vehicles not only entail financial risks, but also a high level of organizational effort. Which technologies or measures do you use to counteract such unplanned maintenance?

DB Cargo has set up its own program to deal with this topic in a targeted manner. As part of the Asset Automatization & Digitization (AAD) program, we are addressing all processes related to the topic of assets. The aim of the projects is to further optimize the process flows and make the best possible use of the assets, as well as to inform all those involved in the transport at an early stage. Both our customers and our colleagues should benefit from digitalization.


How did these measures influence the availability of your fleet? Is there a noticeable increase in availability compared to before? If so, to what extent?

Since the start of the project, we have been able to continuously reduce the number of so-called “avoidable workshop reassignments”. In the first step, processes were adapted and employees were made aware of the issue. Since mid-2020, the newly rolled-out IT system “iSWM” has been optimizing the automatic feed. Various variables are taken into account when selecting a workshop, such as the forecast maintenance package, traffic flows and workshop capacities. The developed control algorithm will now be successively supplemented with additional data sources and further enhanced via machine learning. In the final stage, we expect to be able to reduce the number of avoidable workshop reassignments by around 6,500 per year. Furthermore, the capacity queries of the workshops and the production facilities will allow better and more precise control of the feed planning. This ensures better advance planning within the workshops and subsequent processes, e.g. ordering materials can be triggered earlier. The aim of the project is to sustainably reduce the downtime of freight cars and thus increase the productive share. In addition, we are creating greater transparency in the process so that errors can be identified faster and corrected manually. In total, we expect an improvement in earnings of more than one million euros per year.


Are your vehicles already sufficiently equipped with IoT devices so that AI can be used sensibly?

By the end of 2020, DB Cargo will have equipped all its freight cars with GPS devices. Some of these vehicles will have additional sensors installed, such as impact sensors or load/empty detection.

First, we will only use the current location data for the freight car feed. Through the connection to the DB Data Lake, however, we will be able to use the entire data in the future and initiate measures in a timely manner so that damaged vehicles can be steered to the appropriate workshop in time.


How do you rate the degree of innovation of DB Cargo compared to other cargo companies?

With the numerous digitization initiatives in the rail freight sector at DB Cargo, I believe we are very well positioned for the future. We are the European industry leader in some areas, such as the networking of customers with DB Cargo via Link2Rail. Digitization issues will play a central role in the Group’s strategy Strong Rail.


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