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A change-point analysis for modeling incomplete burn-in for light displays

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dc.contributor.authorBae, SJ-
dc.contributor.authorKvam, PH-
dc.date.accessioned2022-12-21T11:15:35Z-
dc.date.available2022-12-21T11:15:35Z-
dc.date.issued2006-06-
dc.identifier.issn0740-817X-
dc.identifier.issn1545-8830-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/181423-
dc.description.abstractIn testing display devices such as Plasma Display Panels (PDPs), the observed degradation in luminosity can exhibit an unstable period due to incomplete burn-in during the manufacturing process. We introduce a log-linear model with random coefficients and a change point to describe the nonlinear degradation path. The change point represents the time at which the burn-in period has finished and the degradation in the luminosity changes to a slower and more stable rate. The inference procedure for the lifetime distribution is based on maximum likelihood estimators and results indicate that reliability estimation can be improved substantially by using the change-point model to account for product burn-in effects. An example based on laboratory tests of PDPs helps to illustrate the procedure.-
dc.format.extent10-
dc.language영어-
dc.language.isoENG-
dc.publisherTaylor & Francis-
dc.titleA change-point analysis for modeling incomplete burn-in for light displays-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1080/074081791009068-
dc.identifier.scopusid2-s2.0-33645542340-
dc.identifier.wosid000237079700004-
dc.identifier.bibliographicCitationIIE Transactions (Institute of Industrial Engineers), v.38, no.6, pp 489 - 498-
dc.citation.titleIIE Transactions (Institute of Industrial Engineers)-
dc.citation.volume38-
dc.citation.number6-
dc.citation.startPage489-
dc.citation.endPage498-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaOperations Research & Management Science-
dc.relation.journalWebOfScienceCategoryEngineering, Industrial-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.subject.keywordPlusTO-FAILURE DISTRIBUTION-
dc.subject.keywordPlusSEGMENTED REGRESSION-
dc.subject.keywordPlusLINEAR-REGRESSION-
dc.subject.keywordPlusDEGRADATION DATA-
dc.subject.keywordPlusRELIABILITY-
dc.subject.keywordPlusPARAMETERS-
dc.subject.keywordPlusINFERENCE-
dc.identifier.urlhttps://www.tandfonline.com/doi/full/10.1080/074081791009068-
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