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Maintenance processes modelling and optimisation
Resilience Engineering Research Group, University of Nottingham, UK.
Resilience Engineering Research Group, University of Nottingham, UK.
Resilience Engineering Research Group, University of Nottingham, UK.ORCID iD: 0000-0002-5698-6740
Faste Laboratory, Luleå University of Technology, Sweden.
2017 (English)In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 168, p. 150-160Article in journal (Refereed) Published
Abstract [en]

A Maintenance Procedure is conducted in order to prevent the failure of a system or to restore the functionality of a failed system. Such a procedure consists of a series of tasks, each of which has a distribution of times to complete and a probability of being performed incorrectly. The inclusion of tests can be used to identify any maintenance errors which have occurred. When an error is identified it can be addressed through a corresponding correction sequence which will have associated costs and add to the maintenance process completion time. A modified FMEA approach has been used to identify the possible tests. By incorporating any selection of tests into the maintenance process it can then analysed using a discrete-event simulation to predict the expected completion time distribution. The choice of tests to perform and when to do them is then made to successfully complete the maintenance objective in the shortest possible time using a genetic algorithm. The methodology is demonstrated by applying it to the repair process for a car braking system. The developed method is suitable for application in abroad range of industries. 

Place, publisher, year, edition, pages
Elsevier , 2017. Vol. 168, p. 150-160
Keywords [en]
Maintenance, Optimisation, Failure mode and effect analysis, Discrete-event simulation, Genetic algorithm, System availability
National Category
Other Civil Engineering
Identifiers
URN: urn:nbn:se:oru:diva-91269DOI: 10.1016/j.ress.2017.02.011ISI: 000413878100016Scopus ID: 2-s2.0-85014076702OAI: oai:DiVA.org:oru-91269DiVA, id: diva2:1651525
Note

Funding agency:

Faste Laboratory, Centre for Functional Product Innovation at Luleå University of Technology

Available from: 2022-04-12 Created: 2022-04-12 Last updated: 2022-04-13Bibliographically approved

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Reed, Sean

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CiteExportLink to record
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