Full metadata record
DC FieldValueLanguage
dc.contributor.authorPearn, Wen Leaen_US
dc.contributor.authorWu, Chin Chiehen_US
dc.contributor.authorWu, Chia Huangen_US
dc.date.accessioned2015-07-21T08:29:44Z-
dc.date.available2015-07-21T08:29:44Z-
dc.date.issued2015-07-03en_US
dc.identifier.issn0094-9655en_US
dc.identifier.urihttp://dx.doi.org/10.1080/00949655.2014.914211en_US
dc.identifier.urihttp://hdl.handle.net/11536/124624-
dc.description.abstractProcess capability index C-pk has been the most popular one used in the manufacturing industry dealing with problems of measuring reproduction capability of processes to enhance product development with very low fraction of defectives. In the manufacturing industry, lower confidence bound (LCB) estimates the minimum process capability providing pivotal information for quality engineers to monitoring the process and assessing process performance for quality assurance. The main objective of this paper is to compare and contrast the LCBs on C-pk using two approaches, Classical method and Bayesian method.en_US
dc.language.isoen_USen_US
dc.subjectprocess capability indexen_US
dc.subjectClassical methoden_US
dc.subjectBayesian methoden_US
dc.subjectcredible intervalen_US
dc.subjectlower confidence bounden_US
dc.titleEstimating process capability index C-pk: classical approach versus Bayesian approachen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00949655.2014.914211en_US
dc.identifier.journalJOURNAL OF STATISTICAL COMPUTATION AND SIMULATIONen_US
dc.citation.volume85en_US
dc.citation.issue10en_US
dc.citation.spage2007en_US
dc.citation.epage2021en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000352642500006en_US
dc.citation.woscount0en_US
Appears in Collections:Articles