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Effect of pre-determined maintenance repair rates on the health index state distribution and performance condition curve based on the Markov Prediction Model for sustainable transformers asset management strategies

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dc.citedby7
dc.contributor.authorYahaya M.S.en_US
dc.contributor.authorAzis N.en_US
dc.contributor.authorSelva A.M.en_US
dc.contributor.authorKadir M.Z.A.A.en_US
dc.contributor.authorJasni J.en_US
dc.contributor.authorHairi M.H.en_US
dc.contributor.authorGhazali Y.Z.en_US
dc.contributor.authorTalib M.A.en_US
dc.contributor.authorid36083783000en_US
dc.contributor.authorid56120698200en_US
dc.contributor.authorid57203742582en_US
dc.contributor.authorid25947297000en_US
dc.contributor.authorid25632671500en_US
dc.contributor.authorid26422962100en_US
dc.contributor.authorid55336569600en_US
dc.contributor.authorid36609320500en_US
dc.date.accessioned2023-05-29T06:51:04Z
dc.date.available2023-05-29T06:51:04Z
dc.date.issued2018
dc.descriptionalgorithm; detection method; index method; maintenance; management practice; Markov chain; numerical method; numerical model; performance assessment; probability; repair; strategic approachen_US
dc.description.abstractThis paper presents an investigation of the condition state distribution and performance condition curve of the transformer population under different pre-determined maintenance repair rates based on the Markov Prediction Model (MPM). In total, 3195 oil samples from 373 transformers with an age between one and 25 years were tested. The previously computed Health Index (HI) prediction model of the transformer population based on MPM utilizing the nonlinear minimization technique was employed in this study. The transition probabilities for each of the states were updated based on 10%, 20% and 30% pre-determined maintenance repair rates for the sensitivity study. Next, the HI state distribution and performance condition curve were analyzed based on the Markov chain algorithm. Based on the case study, it is found that the pre-determined maintenance repair rates can affect the HI state distribution and improve the performance condition curve. The 30% pre-determined maintenance repair rate gives the highest impact, especially for the transformer population at state 4 (poor). Overall, the average percentage of change for all HI state distributions is 16.48%. A clear improvement of HI state distribution is found at state 4 (poor) where the highest percentage can be up to 63.25%. � 2018 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo3399
dc.identifier.doi10.3390/su10103399
dc.identifier.issue10
dc.identifier.scopus2-s2.0-85053820735
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85053820735&doi=10.3390%2fsu10103399&partnerID=40&md5=a7cb61ba67cfbfa92037ec600aa5901a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23695
dc.identifier.volume10
dc.publisherMDPIen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleSustainability (Switzerland)
dc.titleEffect of pre-determined maintenance repair rates on the health index state distribution and performance condition curve based on the Markov Prediction Model for sustainable transformers asset management strategiesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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