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dc.contributor.authorPearn, W. L.en_US
dc.contributor.authorWu, Chien-Weien_US
dc.date.accessioned2014-12-08T15:14:47Z-
dc.date.available2014-12-08T15:14:47Z-
dc.date.issued2007-02-01en_US
dc.identifier.issn0305-0483en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.omega.2005.01.018en_US
dc.identifier.urihttp://hdl.handle.net/11536/11171-
dc.description.abstractAcceptance sampling plans are practical tools for quality assurance applications involving quality contract on product orders. The sampling plans provide the vendor and buyer decision rules for product acceptance to meet the preset product quality requirement. As the rapid advancement of manufacturing technology, suppliers require their products to be of high quality with very low fraction of defectives often measured in parts per million. Unfortunately, traditional methods for calculating fraction of defectives no longer work since any sample of reasonable size probably contains no defective product items. In this paper, we introduce an effective sampling plan based on process capability index C-pk to deal with product acceptance determination for low fraction of defectives. The proposed new sampling plan is developed based on the exact sampling distribution rather than approximation. Practitioners can use the proposed method to determine the number of required inspection units, the critical acceptance value, and make reliable decisions in product acceptance. (c) 2005 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectacceptance sampling plansen_US
dc.subjectcritical acceptance valuesen_US
dc.subjectdecision makingen_US
dc.subjectfraction of defectivesen_US
dc.subjectprocess capability indicesen_US
dc.titleAn effective decision making method for product acceptanceen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.omega.2005.01.018en_US
dc.identifier.journalOMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCEen_US
dc.citation.volume35en_US
dc.citation.issue1en_US
dc.citation.spage12en_US
dc.citation.epage21en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000241297800003-
dc.citation.woscount31-
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