Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model

Condition-based maintenance (CBM) is an increasingly applicable policy in the competitive marketplace as a means of improving equipment reliability and efficiency. Not only has maintenance a close relationship with safety but its costs also make it even more attractive issue for researchers. This st...

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Bibliographic Details
Published inReliability engineering & system safety Vol. 142; pp. 357 - 368
Main Authors Azadeh, A., Asadzadeh, S.M., Salehi, N., Firoozi, M.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.10.2015
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Summary:Condition-based maintenance (CBM) is an increasingly applicable policy in the competitive marketplace as a means of improving equipment reliability and efficiency. Not only has maintenance a close relationship with safety but its costs also make it even more attractive issue for researchers. This study proposes a model to evaluate the effectiveness of CBM policy compared to two other maintenance policies: Corrective Maintenance (CM) and Preventive Maintenance (PM). Maintenance policies are compared through two system performance indicators: reliability and cost. To estimate the reliability and costs of the system, the proposed Markovian discrete-event simulation model is developed under each of these policies. The applicability and usefulness of the proposed Markovian simulation model is illustrated for a series–parallel power generation system. The simulated characteristics of CBM system include its prognostics efficiency to estimate remaining useful life of the equipment. Results show that with an efficient prognostics, CBM policy is an effective strategy compared to other maintenance strategies. •A model is developed to evaluate the effectiveness of CBM policy.•Maintenance policies are compared through reliability and cost.•A Markovian simulation model is developed.•A series–parallel power generation system is considered.•CBM is an effective strategy compared to others.
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SourceType-Scholarly Journals-1
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content type line 23
ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2015.04.009