Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

J. Kehrer:
"Managing Light Rail Infrastructure - Towards Predictive Maintenance";
Vortrag: International Conference on Traffic and Transport Engineering (ICTTE) 2018, Belgrad; 27.09.2018 - 28.09.2018; in: "ICTTE Belgrade 2018 - Proceedings of the Fourth International Conference on Traffic and Transport Engineering", S. Zezelj (Hrg.); (2018), ISBN: 9788691615345; Paper-Nr. 53, 5 S.

Kurzfassung deutsch:
Usually designed as secluded networks in urban areas, light rail transit (LRT) infrastructures show specific properties regarding design, network-size, and operational factors. These constraints have led to the currently prevailing maintenance strategies amongst operators; while for heavy rail networks, various operators in Europe have already established condition based maintenance strategies, LRT-operators predominantly rely on qualitative observations and estimations when predicting future needs for maintenance. In a steadily growing market of LRT-systems, approaches for data-based and efficient maintenance strategies that meet the systems´ specific constraints are required since (public) funds for maintenance works are usually scarce. The present paper first gives an overview over the recent development of LRT-systems and - based on a specifically generated database of LRT-systems and their properties around the world - aims to prove it is a rapidly growing market. Subsequently, operational as well as physical constraints of LRT-systems regarding condition-monitoring and maintenance works are assessed and compared according to the systems´ different properties. Decisive factors that influence the condition of LRT-infrastructure are identified and expressed through representative and measurable parameters. Different methods to forecast the network´s condition or the end of it lifespan and thereby set the basis for predictive maintenance are presented. Finally, recommendations for implementing condition-based maintenance for LRT-infrastructure on the long term are given.

Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.