Rail failures and day-time maintenance can result in unwanted delays for passengers, as well as for freight trains. To optimize rail reliability, availability, maintainability, and safety, the SEQUOIA project aims to combine fault maintenance trees with big data analytics. The failure behavior of rail, however, is influenced by various stationary and dynamic features. Therefore, a first step is to understand how the rail reliability varies for different rail features. To this end, we used survival analysis techniques to determine the failure distribution of rail over time for key stationary features. In this seminar I will provide background information on rail defects, treat the relevant data available at ProRail (e.g. rail and defect properties), and share results on the reliability of the Dutch rail.
Rail failures and day-time maintenance can result in unwanted delays for passengers, as well as for freight trains. To optimize rail reliability, availability, maintainability, and safety, the SEQUOIA project aims to combine fault maintenance trees with big data analytics. The failure behavior of rail, however, is influenced by various stationary and dynamic features. Therefore, a first step is to understand how the rail reliability varies for different rail features. To this end, we used survival analysis techniques to determine the failure distribution of rail over time for key stationary features. In this seminar I will provide background information on rail defects, treat the relevant data available at ProRail (e.g. rail and defect properties), and share results on the reliability of the Dutch rail.
Zilverling 2042falseDD/MM/YYYYHallenweg 19
7522 NH Enschede
Netherlands