Optimization of maintenance strategies for railway track-bed considering probabilistic degradation models and different reliability levels

Joao Miguel Oliveira dos Santos*, Sara Bressi, Massimo Losa

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)
65 Downloads (Pure)

Abstract

An optimization-based maintenance scheduling framework is an essential tool to plan the necessary investment to maintain the required performance of a railway line. In the present study, a methodology is proposed to minimize the present value of the life cycle maintenance costs and maximize the life cycle quality level of the track-bed considering different levels of reliability. Probabilistic degradation models are developed for predicting the evolution of the railway track condition over time. Afterwards, a Genetic Algorithm based optimization procedure is applied for obtaining a set of optimal solutions taking into account several constrains. The proposed methodology is applied to an Italian railway track-line case study. The results show that it is possible to develop a decision support system to help railway managers to schedule railway track maintenance operations based on the optimal trade-off between maintenance costs and railway track geometry condition for different levels of reliability.
Original languageEnglish
Article number107359
Number of pages17
JournalReliability engineering & system safety
Volume207
Early online date27 Nov 2020
DOIs
Publication statusPublished - Mar 2021

Keywords

  • UT-Hybrid-D

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