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dc.contributor.authorPearn, WLen_US
dc.contributor.authorShu, MHen_US
dc.contributor.authorHsu, BMen_US
dc.date.accessioned2014-12-08T15:17:59Z-
dc.date.available2014-12-08T15:17:59Z-
dc.date.issued2005-12-01en_US
dc.identifier.issn0266-4763en_US
dc.identifier.urihttp://dx.doi.org/10.1080/02664760500164951en_US
dc.identifier.urihttp://hdl.handle.net/11536/13004-
dc.description.abstractProcess capability indices have been widely used in the manufacturing industry providing numerical measures on process performance. The index C-p provides measures on process precision (or product consistency). The index C-pm,C- sometimes called the Taguchi index, meditates on process centring ability and process loss. Most research work related to C-p and C-pm assumes no gauge measurement errors. This assumption insufficiently reflects real situations even with highly advanced measuring instruments. Conclusions drawn from process capability analysis are therefore unreliable and misleading. In this paper, we conduct sensitivity investigation on process capability C-p and C-pm in the presence of gauge measurement errors. Due to the randomness of variations in the data, we consider capability testing for C-p and C-pm to obtain lower confidence bounds and critical values for true process capability when gauge measurement errors are unavoidable. The results show that the estimator with sample data contaminated by the measurement errors severely underestimates the true capability, resulting in imperceptible smaller test power. To obtain the true process capability, adjusted confidence bounds and critical values are presented to practitioners for their factory applications.en_US
dc.language.isoen_USen_US
dc.subjectgauge measurement erroren_US
dc.subjectlower confidence bounden_US
dc.subjectcritical valueen_US
dc.subjectprocess capability analysisen_US
dc.titleTesting process capability based on C-pm in the presence of random measurement errorsen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/02664760500164951en_US
dc.identifier.journalJOURNAL OF APPLIED STATISTICSen_US
dc.citation.volume32en_US
dc.citation.issue10en_US
dc.citation.spage1003en_US
dc.citation.epage1024en_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:000234427900002-
dc.citation.woscount8-
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