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Cited 10 time in webofscience Cited 13 time in scopus
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dc.contributor.authorAslam, M-
dc.contributor.authorAzam, M-
dc.contributor.authorJun, CH-
dc.date.accessioned2016-03-31T08:17:04Z-
dc.date.available2016-03-31T08:17:04Z-
dc.date.created2014-02-25-
dc.date.issued2013-01-
dc.identifier.issn0747-4946-
dc.identifier.other2013-OAK-0000028952-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/14964-
dc.description.abstractThis article deals with the group acceptance sampling plan based on truncated life tests when the lifetime of a product follows the inverse Gaussian distribution. The design parameters such as the acceptance number and the number of groups are determined according to the specified number of testers, experiment time, and mean ratio. Tables are presented for different known values of the shape parameter. The misspecification issue of the model parameter is also studied. Some examples are discussed to illustrate the plan under the inverse Gaussian distribution.-
dc.description.statementofresponsibilityX-
dc.languageEnglish-
dc.publisherTAYLOR & FRANCIS INC-
dc.relation.isPartOfSEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS-
dc.subjectAcceptance sampling-
dc.subjectConsumer&apos-
dc.subjects risks-
dc.subjectInverse Gaussian distribution-
dc.subjectLife tests-
dc.subjectProducer&apos-
dc.subjects risk-
dc.subjectTRUNCATED LIFE TESTS-
dc.subjectRELIABILITY-
dc.subjectRAYLEIGH-
dc.subjectMODEL-
dc.titleDecision Rule Based on Group Sampling Plan Under the Inverse Gaussian Distribution-
dc.typeArticle-
dc.contributor.college산업경영공학과-
dc.identifier.doi10.1080/07474946.2013.751849-
dc.author.googleAslam, M-
dc.author.googleAzam, M-
dc.author.googleJun, CH-
dc.relation.volume32-
dc.relation.issue1-
dc.relation.startpage71-
dc.relation.lastpage82-
dc.contributor.id10070938-
dc.relation.journalSEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS-
dc.relation.indexSCI급, SCOPUS 등재논문-
dc.relation.sciSCIE-
dc.collections.nameJournal Papers-
dc.type.rimsART-
dc.identifier.bibliographicCitationSEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS, v.32, no.1, pp.71 - 82-
dc.identifier.wosid000323819400011-
dc.date.tcdate2019-01-01-
dc.citation.endPage82-
dc.citation.number1-
dc.citation.startPage71-
dc.citation.titleSEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS-
dc.citation.volume32-
dc.contributor.affiliatedAuthorJun, CH-
dc.identifier.scopusid2-s2.0-84873658479-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc6-
dc.description.scptc5*
dc.date.scptcdate2018-05-121*
dc.type.docTypeArticle-
dc.subject.keywordPlusTRUNCATED LIFE TESTS-
dc.subject.keywordPlusRELIABILITY-
dc.subject.keywordPlusRAYLEIGH-
dc.subject.keywordPlusMODEL-
dc.subject.keywordAuthorAcceptance sampling-
dc.subject.keywordAuthorConsumer&apos-
dc.subject.keywordAuthors risks-
dc.subject.keywordAuthorInverse Gaussian distribution-
dc.subject.keywordAuthorLife tests-
dc.subject.keywordAuthorProducer&apos-
dc.subject.keywordAuthors risk-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMathematics-

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전치혁JUN, CHI HYUCK
Dept of Industrial & Management Enginrg
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