Railway infrastructure managers face the challenge of attaining a high level of performance and safety while meeting strict financial targets. To assist with decision making, modelling is needed to predict and evaluate the outcomes of different maintenance strategies and investment options, to understand which will deliver the optimum result. Railway networks are complex systems containing a diverse range of assets. To date most modelling approaches have focused on a single asset class, treating it as a silo. Although beneficial, these models are unable to capture the inherent interactions between components and, although greatly improving the decision-making process, may still not lead to optimum outcomes. The aim of this paper is to present a whole system framework that can model a range of asset classes simultaneously, enabling the interactions between asset classes to be considered, thus allowing practitioners to make decisions based on whole system and whole life cost. The feasibility and benefits of such a model are explored through application to a case study on the UK railway network. A sensitivity analysis was then conducted on the maintenance and renewal budget to explore the impact on life cycle cost.
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June 2025
Research Article|
December 10 2024
System Petri net modelling for railway infrastructure asset management
Jack Litherland, BSc, PhD
;
Jack Litherland, BSc, PhD
Resilience Engineering Research Group, University of Nottingham, UK
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John Andrews, BSc, PhD, CEng
John Andrews, BSc, PhD, CEng
Professor, Resilience Engineering Research Group, University of Nottingham, UK (corresponding author: John.Andrews@Nottingham.ac.uk)
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Publisher: Emerald Publishing
Received:
October 01 2023
Accepted:
December 03 2024
Online ISSN: 2053-0250
Print ISSN: 2053-0242
Emerald Publishing Limited: All rights reserved
2025
Infrastructure Asset Management (2025) 12 (2): 110–128.
Article history
Received:
October 01 2023
Accepted:
December 03 2024
Citation
Litherland J, Andrews J (2025), "System Petri net modelling for railway infrastructure asset management". Infrastructure Asset Management, Vol. 12 No. 2 pp. 110–128, doi: https://doi.org/10.1680/jinam.23.00046
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