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dc.contributor.authorPearn, WLen_US
dc.contributor.authorShu, MHen_US
dc.contributor.authorHsu, BMen_US
dc.date.accessioned2014-12-08T15:18:52Z-
dc.date.available2014-12-08T15:18:52Z-
dc.date.issued2005-06-15en_US
dc.identifier.issn0020-7543en_US
dc.identifier.urihttp://dx.doi.org/10.1080/00207540500045741en_US
dc.identifier.urihttp://hdl.handle.net/11536/13578-
dc.description.abstractThe multi-process performance analysis chart (MPPAC) based on process capability indices has been developed to analyse the manufacturing performance for multiple processes, which conveys critical information regarding the departure of the process mean from the target value, process variability, capability levels, which provides a guideline of directions for capability improvement. Existing MPPAC researches have plotted the sample estimates of the process indices on the chart. Conclusions were then made on whether processes meet the capability requirement and directions need to be taken for further quality improvement. Such an approach is highly unreliable since the sample point estimate is a random variable with no assessment of the sampling errors. Further, existing MPPAC researches only considered one single sample. Current quality control practice is to estimate process capability using multiple groups of control chart samples rather than one single sample. In this paper, we propose the C-pmk MPPAC combining the accuracy index C-a to access the performance of multiple manufacturing processes. Distributions of the estimated C-pmk and C-a are derived based on multiple control chart samples, and accurate lower confidence bounds are calculated. The lower confidence bounds of the estimated Cpmk and Ca are then employed to the MPPAC to provide reliable capability grouping for those multiple processes. A real-world example is presented to illustrate the applicability of the proposed MPPAC.en_US
dc.language.isoen_USen_US
dc.subjectmulti-process performance analysis chart (MPPAC)en_US
dc.subjectprocess capability indexen_US
dc.subjectmultiple characteristicsen_US
dc.subjectlower confidence bounden_US
dc.subjectprocess yielden_US
dc.titleMonitoring manufacturing quality for multiple Li-BPIC processes based on capability index C-pmken_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00207540500045741en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF PRODUCTION RESEARCHen_US
dc.citation.volume43en_US
dc.citation.issue12en_US
dc.citation.spage2493en_US
dc.citation.epage2512en_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:000229181900008-
dc.citation.woscount5-
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