Big data – the basis for predictive maintenance of rail vehicles

A technical article by Dr.-Ing. Lars Schnieder and Dr.-Ing. Ulrich Bock was published in the March issue of the trade journal “ZEVrail”.

“One of the aims of asset management in rail transport companies is to maintain value and reduce asset downtimes over the entire life cycle of a rail vehicle. Digitalization opens up potential through the further development of the maintenance strategy into predictive maintenance. This article presents a structured procedure for the introduction of innovative maintenance concepts in the existing fleets of railroad companies. On the basis of a powerful IT system architecture, an efficient analysis of mass data is possible, which provides concrete recommendations for action to optimize maintenance.”

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