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Cited 30 time in webofscience Cited 36 time in scopus
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dc.contributor.authorBalamurali, S-
dc.contributor.authorJun, CH-
dc.date.accessioned2016-03-31T09:26:53Z-
dc.date.available2016-03-31T09:26:53Z-
dc.date.created2011-08-12-
dc.date.issued2011-05-
dc.identifier.issn1524-1904-
dc.identifier.other2011-OAK-0000024035-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/17197-
dc.description.abstractThe skip-lot sampling program can be used for reducing the amount of inspection on a product that has excellent quality history. Thus skip-lot sampling plans are designed to reduce inspection costs. Moreover, the skip-lot concept is sound and useful and is economically advantageous to use in the design of sampling plans. Hence, a new system of skip-lot sampling plans designated as the SkSP-V plan is developed in this paper. The proposed plan requires a return to normal inspection whenever a lot is rejected during sampling inspection, but has a provision for a reduced normal inspection upon demonstration of superior product quality. A Markov chain formulation and derivation of performance measures for this new plan are presented. The properties of SkSP-V plan are studied with single sampling plan as the reference plan. Advantages of this new plan are also discussed. Finally, certain cost models are given for the economic design of the SkSP-V plan. Copyright (C) 2010 John Wiley & Sons, Ltd.-
dc.description.statementofresponsibilityX-
dc.languageEnglish-
dc.publisherWILEY-BLACKWELL-
dc.relation.isPartOfAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY-
dc.subjectquality-
dc.subjectskip-lot sampling-
dc.subjectMarkov chain-
dc.subjectcost models-
dc.titleA new system of skip-lot sampling plans having a provision for reducing normal inspection-
dc.typeArticle-
dc.contributor.college산업경영공학과-
dc.identifier.doi10.1002/ASMB.844-
dc.author.googleBalamurali, S-
dc.author.googleJun, CH-
dc.relation.volume27-
dc.relation.issue3-
dc.relation.startpage348-
dc.relation.lastpage363-
dc.contributor.id10070938-
dc.relation.journalAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY-
dc.relation.indexSCI급, SCOPUS 등재논문-
dc.relation.sciSCIE-
dc.collections.nameJournal Papers-
dc.type.rimsART-
dc.identifier.bibliographicCitationAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, v.27, no.3, pp.348 - 363-
dc.identifier.wosid000292660100016-
dc.date.tcdate2019-01-01-
dc.citation.endPage363-
dc.citation.number3-
dc.citation.startPage348-
dc.citation.titleAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY-
dc.citation.volume27-
dc.contributor.affiliatedAuthorJun, CH-
dc.identifier.scopusid2-s2.0-79960008827-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc16-
dc.description.scptc15*
dc.date.scptcdate2018-05-121*
dc.type.docTypeArticle-
dc.subject.keywordAuthorquality-
dc.subject.keywordAuthorskip-lot sampling-
dc.subject.keywordAuthorMarkov chain-
dc.subject.keywordAuthorcost models-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.relation.journalWebOfScienceCategoryMathematics, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaOperations Research & Management Science-
dc.relation.journalResearchAreaMathematics-

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전치혁JUN, CHI HYUCK
Dept of Industrial & Management Enginrg
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