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The C ''(pk) index for asymmetric tolerances: Implications and inference

dc.citation.epage136en_US
dc.citation.issue2en_US
dc.citation.spage119en_US
dc.citation.volume60en_US
dc.citation.woscount20
dc.contributor.authorPearn, WLen_US
dc.contributor.authorLin, PCen_US
dc.contributor.authorChen, KSen_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.date.accessioned2014-12-08T15:39:46Z
dc.date.available2014-12-08T15:39:46Z
dc.date.issued2004en_US
dc.description.abstractThe process capability index C-pk has been widely used in the manufacturing industry to provide numerical measures on process performance. Since C-pk is a yield-based index which is independent of the target T, it fails to account for process centering with symmetric tolerances, and presents an even greater problem with asymmetric tolerances. Pearn and Chen (1998) considered a new generalization C-pk" which was shown to be superior to other existing generalizations of C-pk for processes with asymmetric tolerances. In this paper, we investigate the relation between the fraction nonconforming and the value of C-pk", Furthermore, we derive explicit forms of the cumulative distribution function and the probability density function for the natural estimator (C) over cap (pk)" under the assumption of normality. We also develop a decision making rule based on the natural estimator (C) over cap (pk)", which can be used to test whether the process is capable or not.en_US
dc.identifier.doi10.1007/s001840300300en_US
dc.identifier.issn0026-1335en_US
dc.identifier.journalMETRIKAen_US
dc.identifier.urihttp://dx.doi.org/10.1007/s001840300300en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/27162
dc.identifier.wosnumberWOS:000224054200002
dc.language.isoen_USen_US
dc.subjectasymmetric toleranceen_US
dc.subjectdecision making ruleen_US
dc.subjectnormally distributed processen_US
dc.subjectprocess yielden_US
dc.titleThe C ''(pk) index for asymmetric tolerances: Implications and inferenceen_US
dc.typeArticleen_US

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