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dc.contributor.authorPearn, WLen_US
dc.contributor.authorChuang, CCen_US
dc.date.accessioned2014-12-08T15:39:06Z-
dc.date.available2014-12-08T15:39:06Z-
dc.date.issued2004-06-01en_US
dc.identifier.issn0748-8017en_US
dc.identifier.urihttp://dx.doi.org/10.1002/qre.544en_US
dc.identifier.urihttp://hdl.handle.net/11536/26728-
dc.description.abstractProcess yield has been the most basic and common criterion used in the manufacturing industry as a base for measuring process performance. Boyles considered a measurement formula called S-pk, which establishes the relationship between the manufacturing specification and the actual process performance, providing an exact (rather than approximate) measure of process yield. Unfortunately, the sampling distribution and the associated statistical properties of Spk are analytically intractable. In this paper, we consider the natural estimator of the measure S-pk. We investigate the accuracy of the natural estimator of S-pk computationally, using a simulation technique to find the relative bias and the relative mean square error for some commonly used quality requirements. Extensive simulation results are provided and analyzed, which are useful to the engineers for factory applications in measuring process performance. Copyright (C) 2004 John Wiley Sons, Ltd.en_US
dc.language.isoen_USen_US
dc.subjectprocess yield measureen_US
dc.subjectrelative biasen_US
dc.subjectrelative mean square erroren_US
dc.titleAccuracy analysis of the estimated process treld based onS(pk)en_US
dc.typeArticleen_US
dc.identifier.doi10.1002/qre.544en_US
dc.identifier.journalQUALITY AND RELIABILITY ENGINEERING INTERNATIONALen_US
dc.citation.volume20en_US
dc.citation.issue4en_US
dc.citation.spage305en_US
dc.citation.epage316en_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:000222048700007-
dc.citation.woscount9-
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