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dc.contributor.authorHsieh, KLen_US
dc.contributor.authorTong, LIen_US
dc.date.accessioned2014-12-08T15:17:29Z-
dc.date.available2014-12-08T15:17:29Z-
dc.date.issued2006-02-01en_US
dc.identifier.issn0268-3768en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s00170-004-2314-1en_US
dc.identifier.urihttp://hdl.handle.net/11536/12670-
dc.description.abstractProcess capability analysis (PCA) is frequently employed to evaluate a product or a process if it can meet the customer's requirement. In general, process capability analysis can be represented by using the process capability index (PCI). Until now, the PCI was frequently used for processes with quantitative characteristics. However, for process quality with the qualitative characteristic, the data's type and single specification caused limitations of using the PCI. When the product can not meet the target, even if it lies in the specified range, it should lead to the corresponding quality loss. Taguchi developed a quadratic quality loss function (QLF) to address such issues. In this study, we intend to construct a measurable index which incorporates the PCI philosophy and QLF concept to analyze the process capability with the consideration of the qualitative response data. The manufacturers can not only employ the proposed index to self-assess the process capability, but they also can make comparisons with the other competitors .en_US
dc.language.isoen_USen_US
dc.subjectprocess capability analysis (PCA)en_US
dc.subjectprocess capability indexes (PCIs)en_US
dc.subjectqualitative dataen_US
dc.subjectquality loss function (QLF)en_US
dc.titleIncorporating process capability index and quality loss function into analyzing the process capability for qualitative dataen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00170-004-2314-1en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGYen_US
dc.citation.volume27en_US
dc.citation.issue11-12en_US
dc.citation.spage1217en_US
dc.citation.epage1222en_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:000235013900022-
dc.citation.woscount9-
Appears in Collections:Articles


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