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Article: An empirical study of two classes of estimators for process variation transmission

TitleAn empirical study of two classes of estimators for process variation transmission
Authors
KeywordsMaximum likelihood estimators
Measurement error
Missing data
Process variation
Issue Date1999
PublisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijrqse/ijrqse.shtml
Citation
International Journal Of Reliability, Quality And Safety Engineering, 1999, v. 6 n. 3, p. 289-300 How to Cite?
AbstractManufacturing processes often consist of a number of sequential stages. Of interest is to control the variation in one or more quality characteristics of a production unit at the final stage. By understanding how variation is transmitted and added across the stages, remedial actions in reducing variation at the final stage can be properly planned. With one quality characteristic measured at each stage, a set of naive estimators is previously proposed and shown to perform indistinguishably well with maximum likelihood estimators. Thus naive estimators are more convenient than maximum likelihood estimators as the former exist in closed form while the latter do not. This article considers situations when more than one quality characteristic is measured throughout the stages. Methods of analyzing variation transmission are briefly reviewed and the finite sample properties of naive and maximum likelihood estimators for multivariate measurements are further examined. A broad conclusion is that for moderate number of production units, naive estimators have smaller bias and variability. Furthermore, "proper" naive estimates provide more accurate interval estimates at a given confidence level. Finally, a set of piston-machining data is used for illustration. © World Scientific Publishing Company.
Persistent Identifierhttp://hdl.handle.net/10722/87569
ISSN
2015 SCImago Journal Rankings: 0.315
References

 

DC FieldValueLanguage
dc.contributor.authorFong, DYTen_HK
dc.date.accessioned2010-09-06T09:31:32Z-
dc.date.available2010-09-06T09:31:32Z-
dc.date.issued1999en_HK
dc.identifier.citationInternational Journal Of Reliability, Quality And Safety Engineering, 1999, v. 6 n. 3, p. 289-300en_HK
dc.identifier.issn0218-5393en_HK
dc.identifier.urihttp://hdl.handle.net/10722/87569-
dc.description.abstractManufacturing processes often consist of a number of sequential stages. Of interest is to control the variation in one or more quality characteristics of a production unit at the final stage. By understanding how variation is transmitted and added across the stages, remedial actions in reducing variation at the final stage can be properly planned. With one quality characteristic measured at each stage, a set of naive estimators is previously proposed and shown to perform indistinguishably well with maximum likelihood estimators. Thus naive estimators are more convenient than maximum likelihood estimators as the former exist in closed form while the latter do not. This article considers situations when more than one quality characteristic is measured throughout the stages. Methods of analyzing variation transmission are briefly reviewed and the finite sample properties of naive and maximum likelihood estimators for multivariate measurements are further examined. A broad conclusion is that for moderate number of production units, naive estimators have smaller bias and variability. Furthermore, "proper" naive estimates provide more accurate interval estimates at a given confidence level. Finally, a set of piston-machining data is used for illustration. © World Scientific Publishing Company.en_HK
dc.languageengen_HK
dc.publisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijrqse/ijrqse.shtmlen_HK
dc.relation.ispartofInternational Journal of Reliability, Quality and Safety Engineeringen_HK
dc.subjectMaximum likelihood estimatorsen_HK
dc.subjectMeasurement erroren_HK
dc.subjectMissing dataen_HK
dc.subjectProcess variationen_HK
dc.titleAn empirical study of two classes of estimators for process variation transmissionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0218-5393&volume=6 &issue=3&spage=289&epage=300&date=1999&atitle=An+Empirical+Study+of+Two+Classes+of+Estimators+for+Process+Variation+Transmissionen_HK
dc.identifier.emailFong, DYT: dytfong@hku.hken_HK
dc.identifier.authorityFong, DYT=rp00253en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1142/S0218539399000279-
dc.identifier.scopuseid_2-s2.0-0002816183en_HK
dc.identifier.hkuros48513en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0002816183&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.issue3en_HK
dc.identifier.spage289en_HK
dc.identifier.epage300en_HK
dc.publisher.placeSingaporeen_HK
dc.identifier.scopusauthoridFong, DYT=35261710300en_HK

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