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Big data - basis for predictive maintenance of rail vehicle

An article by Dr.-Ing. Lars Schnieder and Dr.-Ing. Ulrich Bock was published in the March edition of the journal ZEVrail.

"The essential objective of Asset Management in railway companies is to maintain value and a reduction of down-times of rail vehicles over their entire life cycle. Digitization opens up the potential to develop the maintenance strategy to predictive maintenance. This article introduces a structured approach to the introduction of innovative maintenance concepts in existing rail vehicle fleets. On the basis of a comprehensive IT system architecture, an efficient analysis of massive data (big data) can be achieved, which provides specific recommendations for the optimization of maintenance."

You have questions concerning the basis for predictive maintenance of rail verhicles or predictive maintenance in general? Please contact Dr.-Ing. Lars Schnieder or Dr.-Ing. Ulrich Bock to find out more about your individual questions or requirements or let them present you some of their recent projects.

Please send us a mail to pr(at)ese.de to get access to the complete article.