Archive for the 'Maintenance Prediction' Category

Welcome Arnaud van Harmelen

Tuesday, May 16th, 2017, posted by Djoerd Hiemstra

Welcome to the Database Group Arnaud van Harmelen!
Arnaud will work on SEQUOIA.

Two PhD positions on Maintenance Optimization for the Dutch railroads

Tuesday, January 3rd, 2017, posted by Djoerd Hiemstra

We are hiring two PhD positions on Maintenance Optimization for the Dutch railroads.

The Database and Formal Methods & Tools groups at the University of Twente seek two PhD candidates for SEQUOIA: Smart maintenance optimization via big data & fault tree analysis, a project funded by the Dutch Technology Foundation STW, and the companies ProRail and NS. ProRail is responsible for the Dutch railway network, including its construction, management, maintenance, and safety; NS has the same responsibility for the Dutch train fleed.

Predictive maintenance explained

SEQUOIA aims to improve the reliability of the Dutch railroads by deploying big data analytics to predict and prevent failures. Its scientific core is a novel combination of machine learning, fault tree analysis and stochastic model checking. Key idea is that big data analytics provide the statistics on failures, their correlations, dependencies etc. and fault trees provide the domain knowledge needed to interpret these data. The project outcome aims at fewer train disruptions and delays, lower maintenance cost and more passenger comfort. The project involves an intense cooperation with the RWTH Aachen University and with various engineers from ProRail and NS. The PhD candidates will spend a portion of their time at the ProRail / NS sites in Utrecht.

Apply on-line.