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Assessing the Potential for Resilient Performance in Rolling Stock Maintenance: The Pitstop Case

  • Jan-Jaap MoermanEmail author
  • A. J. J. Braaksma
  • Leo A. M. van Dongen
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  • 320 Downloads
Part of the Asset Analytics book series (ASAN)

Abstract

Unexpected failures of physical assets are a primary operational risk to asset-intensive organisations. Managing these unexpected failures is essential for reliable performance. The main railway operator in the Netherlands expects more unexpected failures as a result of the introduction of new rolling stock in an already highly utilised railway system. One of the challenges of maintenance management is to determine if the current corrective maintenance system has the capabilities to cope with an increase of unexpected defects of rolling stock in the upcoming years or that further improvements are required. In the last decade, Resilience Engineering has emerged as a new paradigm in a number of high-risk sectors to detect and respond to unexpected events effectively. Attempts to apply this concept outside these sectors have so far been limited. The main purpose of this study is to explore the applicability of Resilience Engineering in the field of rolling stock maintenance by assessing the potential for resilient performance using an in-depth case study. A comparison between the characteristics of corrective maintenance and emergency healthcare showed that the studied contexts are highly comparable which suggests that the concept of Resilience Engineering may also apply to corrective maintenance of rolling stock. This study contributes to theory by replicating and adapting Resilience Engineering for corrective maintenance of rolling stock and provides maintenance practitioners guidance on how to measure current resilience and identify improvement areas.

Keywords

Resilience engineering Rolling stock Corrective maintenance 

Notes

Acknowledgements

This research was supported by the Nederlandse Spoorwegen (NS). The authors thank the NS organisation who provided insight and expertise that greatly assisted the research, although they may not agree with all of the interpretations or conclusions of this study.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Jan-Jaap Moerman
    • 1
    • 2
    Email author
  • A. J. J. Braaksma
    • 1
  • Leo A. M. van Dongen
    • 1
    • 2
  1. 1.Maintenance Engineering Group, University of TwenteEnschedeThe Netherlands
  2. 2.Netherlands RailwaysUtrechtThe Netherlands

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