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dc.contributor.authorÇınar, Suna
dc.contributor.authorSzidarovszky, Ferenc
dc.contributor.authorYildirim, Mehmet Bayram
dc.identifier.citationCinar, S., Szidarovszky, F., & Yildirim, M. B. (2021). Enhancing reliability/availability in asset management with retrofitting: A wind turbine case study. International Journal of Operational Research, 42(3), 400-421. doi:10.1504/IJOR.2021.119410en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractIn this study, a mixed-integer linear programming (MILP) modelling approach is proposed to identify the optimum maintenance or retrofitting schedule under budget and energy production constraint(s) by improving failure rate of assets. The proposed reliability/availability asset management with retrofitting (RAAMWR) model seeks to maximise the total net profit subject to achieving a target reliability/availability value and minimise the total improvement cost subject to a budgetary constraint. We apply our model to a case study involving wind turbines (WTs). The results of this study show that to reach the target reliability value with improved failure rate data, model selects retrofitting due to lower loss time and high energy production rate of retrofitting options. This optimal retrofitting choice is not only due to low loss time, but also improving the existing failure rate of an asset to reach the target reliability. In addition, the effects of key parameters on total cost, such as operation and maintenance (O&M) cost, retrofitting cost, budget allocated for retrofitting, and different target reliability values on the optimal improvement policy were considered.en_US
dc.relation.ispartofseriesInternational Journal of Operational Research;Vol. 42, Iss. 3
dc.subjectMixed-integer linear programmingen_US
dc.subjectWind turbineen_US
dc.subjectAsset managementen_US
dc.titleEnhancing reliability/availability in asset management with retrofitting: A wind turbine case studyen_US
dc.rights.holder© 2021 Inderscience Enterprises Ltd.en_US

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    Research works published by faculty and students of the Department of Industrial, Systems, and Manufacturing Engineering

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