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A risk-based modelling approach to maintenance optimization of railway rolling stock: A case study of pantograph system

Fateme Dinmohammadi (School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, UK) (School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK)

Journal of Quality in Maintenance Engineering

ISSN: 1355-2511

Article publication date: 11 January 2019

Issue publication date: 23 April 2019

706

Abstract

Purpose

Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces the assets’ lifecycle cost, but also will ensure high standards of safety and comfort for rail passengers and workers. In recent years, the majority of studies have been focused on the application of risk-based tools and techniques to maintenance decision making of railway infrastructure assets (such as tracks, bridges, etc.). The purpose of this paper is to present a risk-based modeling approach for the inspection and maintenance optimization of railway rolling stock components.

Design/methodology/approach

All the “potential failure modes and root causes” related to rolling stock systems are identified from an extensive literature review followed by an expert’s panel assessment. The failure causes are categorized into six groups of electrical faults, structural damages, functional failures, degradation, human errors and natural (external) hazards. Stochastic models are then proposed to estimate the likelihood (probability) of occurrence of a failure in the rolling stock system. The consequences of failures are also modeled by an “inflated cost function” that involves safety-related costs, corrective maintenance and renewal (M&R) costs, the penalty charges due to train delays or service interruptions as well as the costs associated with loss of reputation (or loss of fares) in the case of trip cancellation. Lastly, a time-varying risk-cost function is formulated to determine the optimal frequency of preventive inspection and maintenance actions for rolling stock components.

Findings

For the purpose of clearly illustrating the proposed risk-based inspection and maintenance modeling methodology, a case study of the Class 380 train’s pantograph system from a Scottish train operating company is provided. The results indicate that the proposed model has a substantial potential to reduce the M&R costs while ensuring a higher level of safety and service quality compared to the currently used inspection methodologies.

Practical implications

The railway rolling stocks should be regularly inspected and maintained so as to ensure network availability and reliability, passenger safety and comfort, and operations efficiency. Despite the best efforts of the maintenance staff, it is reported that a considerable amount of maintenance resources (e.g. budget, time, manpower) is wasted due to insufficiency or inefficiency of current periodic M&R interventions. The model presented in this paper helps the maintenance engineers to assess the current maintenance practices and propose or initiate improvement actions when needed.

Originality/value

There are few studies investigating the application of risk-based tools and techniques to inspection and maintenance decision making of railway rolling stock components. This paper presents a modeling approach aimed at planning the preventive repair and maintenance interventions for rolling stock components based on risk measures. The author’s model is also capable of incorporating real measurement information gathered at each inspection epoch to update future inspection plans.

Keywords

Acknowledgements

The author gratefully acknowledges the support provided by the Scottish train operating company during field visits and data collection.

Citation

Dinmohammadi, F. (2019), "A risk-based modelling approach to maintenance optimization of railway rolling stock: A case study of pantograph system", Journal of Quality in Maintenance Engineering, Vol. 25 No. 2, pp. 272-293. https://doi.org/10.1108/JQME-11-2016-0070

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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