Ruijters, E.J.J. and Guck, D. and Drolenga, P. and Peters, M. and Stoelinga, M.I.A.
Maintenance analysis and optimization via statistical model checking: Evaluating a train pneumatic compressor.
In: Proceedings of the 13th International Conference on Quantitative Evaluation of SysTems, QEST 2016, 23-25 Aug 2016, Québec City, Canada.
Lecture Notes in Computer Science 9826.
Full text available as:
Official URL: http://dx.doi.org/10.1007/978-3-319-43425-4_22
Maintenance is crucial to ensuring and improving system dependability: By performing timely inspections, repairs, and renewals the lifespan and reliability of systems can be significantly improved. Good maintenance planning, however, has to balance these improvements against the downsides of maintenance, such as costs and planned downtime.
In this paper, we study the effect of different maintenance strategies on a pneumatic compressor used in trains. This compressor is critical to the operation of the train, and a failure can lead to a lengthy and expensive disruption. Within the rolling stock maintenance company NedTrain, we have modelled this compressor as a fault maintenance tree (FMT), i.e. a fault tree augmented with maintenance aspects. We show how this FMT naturally models complex maintenance plans including condition-based maintenance with regular inspections. The FMT is analysed using statistical model checking, which allows us to obtain several key performance indicators such as the system reliability, number of failures, and required unscheduled maintenance.
Our analysis demonstrates that FMTs can be used to model the compressor, a practical system used in industry, including its maintenance policy. We validate this model against experiences in the field, compute the importance of performing minor services at a reasonable frequency, and find that the currently scheduled overhaul may not be cost-effective.
|Item Type:||Conference or Workshop Paper (Full Paper, Talk)|
|Research Group:||EWI-FMT: Formal Methods and Tools|
|Research Project:||ArRangeer: smARt Railroad maintenance eNGinEERing with stochastic model checking, TREsPASS: Technology-supported Risk Estimation By Predictive Assessment Of Socio-technical Security, BEAT: Better Testing With Game Theory|
|Additional Information:||Foreground = 20%;
Type of activity = conference publication;
Main leader = UT;
Type of audience = scientific community;
Size of audience = 70;
Countries addressed = International;
|Uncontrolled Keywords:||Fault Maintenance Trees, Fault Tree Analysis, Reliability analysis|
|Deposited On:||20 July 2016|
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