AI-powered pit stops for trains

The Rhein-Ruhr-Express (RRX) fleet runs around the clock. One reason for that is artificial intelligence.

Achieving up to 100 percent system availability

The train rolls into the depot, the gates close, and the maintenance crew swings into action – the clock is ticking.

Within a matter of hours, the Rhein-Ruhr-Express (RRX) train must roll back out of the Rail Service Center (RSC), operated by Siemens Mobility in Dortmund, and be back on the track. Eighty-four Siemens Desiro HC vehicles have connected Cologne, Düsseldorf and the Ruhr region since 2018 – operating around the clock. TÜV SÜD validated that the RRX fleet demonstrated an availability level of almost 100 percent over a defined period of time (last validation through September 2024). A secret: Artificial intelligence helps to monitor the condition of the train components, and many processes are automated.

A team member checks the Health States dashboard for monitoring the condition of the bogies.

The trains spend little time in the depot because repairs can be planned in advance thanks to the condition monitoring. If there's a hint of a defect, the parts affected will be replaced at exactly the right time, in other words, not too soon and not too late. That improves efficiency.

The RSC works like a Formula 1 pit stop: in and out of the pit as quickly as possible. More trains in less time, so less space is needed. The RSC in Dortmund has just 70,000 square meters of space, which is very compact for a depot that services 84 vehicles. That makes it a role model for other national and international maintenance centers where trains are kept in good running order by Siemens Mobility. All customers benefit from the knowledge within the Siemens network of experts, as the AI algorithms constantly keep on learning, for instance.

Do you want to see more about the outstanding system availability? Hop on the Rhein-Ruhr-Express – in our video.

Smooth operations and seamless maintenance transition

Advance planning is key to smooth operations and optimized maintenance stops at the depot. That is why the vehicles are equipped with sensors that are continuously monitor mobility critical components during operation.

The collected data is transmitted almost in real time to Railigent X, a suite of services and applications built on the principles of Siemens Xcelerator. Using Artificial intelligence, the system detects anomalies and proposes dates for the next maintenance interval.

While the train is operational, the system already automatically generates work orders within the maintenance management system (CMMS). When the train then rolls into the depot, the maintenance team with the right expertise is waiting for it with the right tools at the appropriate track, and the right spare parts are already there. Frequently used mechanical parts, such as brackets for first aid kits, can be replaced with more robust, on-site 3D-printed versions that are based on SMO's expertise in additive manufacturing. Metal components are produced through Siemens Mobility's global additive manufacturing network, with printers located around the world. Combined with the intelligent maintenance strategy, this approach reduces downtime, optimizes spare parts availability, and significantly enhances sustainability and efficiency in railway operations.

A Sustainable Development Goals assessment by TÜV SÜD in 2024, which evaluated the maintenance services, the provision of the service infrastructure, and the cleaning of the RRX vehicles at the RSC, gave the RSC an outstanding score of 91 percent. By comparison: The average score in similar sustainability assessments by TÜV SÜD in various industries is between 60 and 70 percent.

Technicians receive their work orders digitally on mobile devices, as seen here during a visual inspection of a train.

Blending human expertise and AI

Despite all of the automation, the RRX vehicles do not, of course, repair themselves. Humans continue to play the leading role at the depot. Artificial intelligence does, however, help them make the right decisions.

Despite all the automation, humans continue to play the leading role in repairing the vehicles.

AI can be found in several subprocesses that build on each other:

Condition monitoring: Sensors measure vibrations in wheels and bogies. Algorithms detect anomalies in the measurements. The heart of the system is a special diagnosis tool for bogies, which uses acceleration sensors to detect defects.
Decision-making support: Apps in Railigent X use this information to extrapolate irregularities in train operation. The condition of the bogies can be tracked in the Health States dashboards. Remaining Useful Life is a complementary app for the condition of the wheels. The AI calculates the optimum maintenance time in advance, such for wheel calibration and replacement.

What is special is that the AI can see up to several months into the future. Since every train has to go to the depot at regular intervals, necessary repairs can be included in the planning as well. Each vehicle undergoes a comprehensive general inspection every eight years. Although the AI is not yet able to see that far into the future, it constantly keeps on learning every day – and will also do so in the future from other locations where Siemens Mobility operates similar maintenance models. One day, the AI could indeed perhaps predict as far as the next general inspection.

By then, nearly 100 percent of work orders might be automatically issued by the AI, compared with 80 percent today. It is always the human who decides whether a work order is actually executed – still. At the depot in Dortmund, the train passes through a gate in front of the hall, where cameras are installed around it. In the future, an AI could detect damage or graffiti and automatically issue the work order – without any personnel at all for the otherwise time-consuming visual inspection. That’s a research project, but the goal is clear: Humans would no longer be required to do laborious inspections, and the trained staff could focus on the really tough problems.

The RRX is the largest rail infrastructure project in the German state of North Rhine-Westphalia. It is intended to provide optimal connections between the state's metropolitan areas - including Cologne.

The future of public transport

The customers, an alliance of five regional transportation associations, have contractually agreed with Siemens Mobility until 2050 which services are to be provided, such as availability of the vehicles.

When the trains run reliably and on time, it is not only the train operators that benefit but also their customers, the passengers. That boosts the appeal of public transport. The Rhein-Ruhr-Express is therefore something of a blueprint for public transport of the future – worldwide.

About railigent

Railigent X is part of the Siemens Xcelerator ecosystem. The data-based application suite for rail systems bundles software-as-a-service applications for managing railway hardware and software. It collects data from trains and rail infrastructure, processes it intelligently and helps to improve operations, optimize maintenance, reduce costs, and increase availability to almost 100 percent. Railigent X is already being used in many passenger, infrastructure and rail freight transport projects worldwide.