Railroad companies must ensure safe and proper operation in accordance with basic legal requirements. In this context, maintenance plays a major role. With their maintenance activities, rail transport companies pursue the following goals
- of high-quality operation from the passenger's point of view,
- a high level of vehicle availability for ongoing operations,
- economic efficiency, especially in intermodal and intramodal competition,
- and improving the safety of operations.
In recent years, various approaches have been established for recording the condition data of rail vehicles. The condition data can be recorded both on the infrastructure side and on the vehicle side. All these approaches have in common that they require an appropriate system architecture for the acquisition and processing of the mass data. In general, the aim of setting up such IoT platforms (IoT - Internet of Things) is to use the analysis of the available data to determine predictions about the future usage behavior of technical components beyond condition-based maintenance. If necessary, further conclusions can be drawn for system improvements planned for the future.
Digitalization opens up the possibility of predictive maintenance based on comprehensive condition data collected during operation of the various subsystems of rail vehicles by means of powerful algorithms. In their article, the authors discuss the criteria for designing a data infrastructure for cross-manufacturer collaborative condition monitoring.
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