Condition monitoring, prediction and management of railway track assets

The aim of the project is to develop a predictive maintenance approach for the Stockholm subway and commuter train traffic.

Sponsor: Vinnova InfraSweden2030
Researchers: Matti Rantatalo
Duration: 2016-2018

Infrastructure managers needs to make well informed operation and maintenance decisions. The decisions should be based on the asset condition or preferably predictions of future conditions and different maintenance scenarios. In this project WSP, LTU and the traffic management of Stockholm county will address the challenges of making an optimum maintenance decision. The aim of the project is to develop a predictive maintenance approach for the Stockholm subway and commuter train traffic. The project is divided into three parts: Investigation into the causes of defects, development of strategic measurement tools to allow predictions as well as statistical analysis of measurement data. The work will be aligned with the asset management standard ISO55000.