A Petri Net-based life cycle cost analysis approach

Kilsby, Paul; Remenyte-Prescott, Rasa; Andrews, John

Abstract

Railway infrastructure providers, such as Network Rail, who owns and manages the British railway infrastructure, can improve the performance and reduce the life cycle cost of their assets through delivering effective asset management. Having the capability to use computer based models to predict the future performance and life cycle cost of an asset group is a key enabling mechanism for implementing effective asset management. Decision makers can determine the optimum maintenance strategy and the best allocation of capital expenditure based on evidence from modelling results. This paper shows how probabilistic modelling can be used to evaluate asset management projects of the railway overhead line equipment (OLE) system and undertake a life cycle cost analysis through the use of a stochastically timed High Level Petri Net. A complete modelling framework has been developed, where the components and their maintenance strategies are selected as inputs, and the Petri Net model is used to calculate outputs associated with the performance and life cycle cost of the OLE system for the corresponding components and strategies considered. This paper presents the practical use of the developed model and describes how the outputs can be used by asset managers to understand the expected system performance and cost over its life cycle. The range of outputs described are the most detailed for such models studying the OLE and other engineering systems in literature. Whilst the railway OLE system is used as an example study, the modelling framework is transferable to asset management projects for other engineering systems.

Citation

Kilsby, P., Remenyte-Prescott, R., & Andrews, J. (2019). A Petri Net-based life cycle cost analysis approach. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 233(1), 90-102. https://doi.org/10.1177/0954409718780106

• Journal Article Type: Article
• Acceptance Date: May 5, 2018
• Online Publication Date: Jun 3, 2018
• Publication Date: Jan 1, 2019
• Deposit Date: May 9, 2018
• Publicly Available Date: Jun 3, 2018
• Journal: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
• Print ISSN: 0954-4097
• Electronic ISSN: 2041-3017
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 233
• Issue: 1
• Pages: 90-102
• DOI: https://doi.org/10.1177/0954409718780106
• Public URL: https://nottingham-repository.worktribe.com/output/936183
• Publisher URL: http://journals.sagepub.com/doi/full/10.1177/0954409718780106