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dc.contributor.authorPearn, WLen_US
dc.contributor.authorLin, PCen_US
dc.date.accessioned2019-04-02T06:00:17Z-
dc.date.available2019-04-02T06:00:17Z-
dc.date.issued2004-12-01en_US
dc.identifier.issn0360-8352en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.cie.2003.03.001en_US
dc.identifier.urihttp://hdl.handle.net/11536/148846-
dc.description.abstractProcess capability index C-pk has been widely used in the manufacturing industry as a process performance measure. In this paper, we investigate the natural estimator of the index C-pk, and show that under the assumption of normality its distribution can be expressed as a mixture of the chi-square and the normal distributions. We also implement the theory of hypothesis testing using the natural estimator of C-pk, and provide efficient Maple programs to calculate the p-values as well as the critical values for various values of alpha-risk, capability requirements, and sample sizes. The behavior of the p-values and critical values as functions of the distribution parameters are investigated to obtain tight critical values for reliable testing. Based on the test, we develop a simple and practical procedure for in-plant applications. The practitioners can use the proposed procedure to determine whether their process meets the preset capability requirement, and make reliable decisions. (C) 2004 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectprocess capability indexen_US
dc.subjecttesting hypothesisen_US
dc.subjectcritical valueen_US
dc.titleTesting process performance based on capability index C-pk with critical valuesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.cie.2003.03.001en_US
dc.identifier.journalCOMPUTERS & INDUSTRIAL ENGINEERINGen_US
dc.citation.volume47en_US
dc.citation.spage351en_US
dc.citation.epage369en_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:000226330700003en_US
dc.citation.woscount34en_US
Appears in Collections:Articles