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Mahdieh Sedghi, Osmo Kauppila, Bjarne Bergquist, Erik Vanhatalo, Murat Kulahci, A taxonomy of railway track maintenance planning and scheduling: A review and research trends, Reliability Engineering & System Safety, Volume 215, 2021, 107827, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2021.107827

A taxonomy of railway track maintenance planning and scheduling : a review and research trends

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Author: Sedghi, Mahdieh1; Kauppila, Osmo1,2; Bergquist, Bjarne1;
Organizations: 1Luleå University of Technology, Luleå, Sweden
2University of Oulu, Oulu, Finland
3Technical University of Denmark, Lyngby, Denmark
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021102652277
Language: English
Published: Elsevier, 2021
Publish Date: 2021-10-26
Description:

Abstract

Railway track maintenance and renewal are vital for railway safety, train punctuality, and travel comfort. Therefore, having cost-effective maintenance is critical in managing railway infrastructure assets. There has been a considerable amount of research performed on mathematical and decision support models for improving the application of railway track maintenance planning and scheduling. This article reviews the literature in decision support models for railway track maintenance planning and scheduling and transforms the results into a problem taxonomy. Furthermore, the article discusses current approaches in optimising maintenance planning and scheduling, research trends, and possible gaps in the related decision-making models.

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Series: Reliability engineering & system safety
ISSN: 0951-8320
ISSN-E: 1879-0836
ISSN-L: 0951-8320
Volume: 215
Article number: 107827
DOI: 10.1016/j.ress.2021.107827
OADOI: https://oadoi.org/10.1016/j.ress.2021.107827
Type of Publication: A1 Journal article – refereed
Field of Science: 212 Civil and construction engineering
Subjects:
Decision support models
Maintenance management
Planning
Railway track
Scheduling
Article
Funding: The authors gratefully acknowledge the financial and other support obtained from the Swedish Transportation Administration and Luleå Railway Research Centre (JVTC) through the project “Statistical Methods in Railway Maintenance”.
Copyright information: © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
  https://creativecommons.org/licenses/by/4.0/