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dc.contributor.authorPearn, W. L.en_US
dc.contributor.authorCheng, Ya-Chingen_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/11536/6058-
dc.identifier.urihttp://dx.doi.org/10.1080/00207540903036313en_US
dc.description.abstractNumerous capability indices have been proposed to measure the performance of processes with multiple characteristics. The index [image omitted] provides an exact measure on the production yield of multinormal processes in which the characteristics are mutually independent. In this paper, we thoroughly investigate the relationship between process parameters and the sampling distribution of [image omitted]. Our investigation shows that for a fixed [image omitted], the variance of sample estimator of [image omitted] is restricted in an interval. For reliability consideration, the maximal variance is used in the estimation and testing of the production yield to ensure the level of confidence. Also, information about sample sizes required for specified precision of estimation and for convergence is determined. At last, we implement a trivariate process with data collected from a plastics manufacturing industrial to demonstrate the practicability of the proposed method in measuring the production yield.en_US
dc.language.isoen_USen_US
dc.subjectcapability indicesen_US
dc.subjectmanufacturing processesen_US
dc.subjectproduction yielden_US
dc.subjectreliabilityen_US
dc.titleMeasuring production yield for processes with multiple characteristicsen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00207540903036313en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF PRODUCTION RESEARCHen_US
dc.citation.volume48en_US
dc.citation.issue15en_US
dc.citation.spage4519en_US
dc.citation.epage4536en_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:000278647700010-
dc.citation.woscount9-
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