Research creates value when it works in daily operation

Our research showed what intelligent, data-based rail head lubrication can achieve and how this understanding has developed systemically.

The next step is crucial: transferring the research results into a real operational project. A concrete example of this is the implementation at BERNMOBIL, in collaboration with Substring as technology partner.

Based on the findings from the research, a system was implemented that:

• Records the lubrication requirements on the vehicle side
• Continuously evaluates noise and operating data
• Triggers lubrication proactively and route-specifically

What is different from before is that lubrication is now demand-driven, data-based and comprehensive across the entire fleet. The principles developed in the research project were specifically refined for operational use with a focus on robustness, scalability and integration into existing processes.

The result is a practical solution that reduces noise and minimises wear while taking operational and environmental requirements into account.

Further insights into the project can be found here: https://prose.one/noise-and-wear-reduction-for-trams-with-ai-based-rail-head-lubrication/