完整後設資料紀錄
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dc.contributor.authorPearn, W. L.en_US
dc.contributor.authorHung, Hui Nienen_US
dc.contributor.authorCheng, Ya Chingen_US
dc.contributor.authorLin, Gu Hongen_US
dc.date.accessioned2014-12-08T15:07:43Z-
dc.date.available2014-12-08T15:07:43Z-
dc.date.issued2010en_US
dc.identifier.issn0020-7543en_US
dc.identifier.urihttp://hdl.handle.net/11536/6056-
dc.identifier.urihttp://dx.doi.org/10.1080/00207540802552667en_US
dc.description.abstractThe yield index S(pk) proposed by Boyles (1994. Process capability with asymmetric tolerances. Communications in Statistics - Simulation and Computation, 23 (1), 615-643) provides an exact measure on the production yield of normal processes. Lee et al. (Lee, J.C., Hung, H.N., Pearn, W. L. and Kueng, T. L., 2002. On the distribution of the estimated process yield index Spk. Quality and Reliability Engineering International, 18 (2), 111-116) considered a normal approximation for estimating Spk. In this paper, we consider a convolution approximation for estimating Spk, and compare with the normal approximation. The comparison results show that the convolution method does provide a more accurate estimation to Spk as well as the production yield than the normal approximation. An efficient step-by-step procedure based on the convolution method is developed to illustrate how to estimate the production yield. Also investigated is the accuracy of the convolution method which provides useful information about sample size required for designated power levels, and for convergence.en_US
dc.language.isoen_USen_US
dc.subjectproduction yielden_US
dc.subjectprocess capabilityen_US
dc.subjectquality assuranceen_US
dc.subjectcritical valueen_US
dc.subjectpower of testen_US
dc.titleProcedure of the convolution method for estimating production yield with sample size informationen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00207540802552667en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF PRODUCTION RESEARCHen_US
dc.citation.volume48en_US
dc.citation.issue5en_US
dc.citation.spage1245en_US
dc.citation.epage1265en_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:000272988800002-
dc.citation.woscount2-
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