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Cited 6 time in webofscience Cited 7 time in scopus
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dc.contributor.authorMohsin, M-
dc.contributor.authorAslam, M-
dc.contributor.authorJun, CH-
dc.date.accessioned2017-07-19T13:28:15Z-
dc.date.available2017-07-19T13:28:15Z-
dc.date.created2017-02-01-
dc.date.issued2016-08-
dc.identifier.issn0954-4054-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/37039-
dc.description.abstractSeveral control charts have been constructed to simultaneously monitor the process mean and variability. A single chart is often used instead of two charts to detect shift in the process mean and variability separately. A new single generally weighted moving average control chart is now proposed to monitor the process mean and dispersion simultaneously, based on Taguchi's loss function. A Monte Carlo simulation is used to calculate average run length to study the performance of this control chart when the process is shifted. A comparison is made with an exponentially weighted moving average control chart in terms of average run lengths. Two examples are also included for showing the practical application of the proposed control chart.-
dc.languageEnglish-
dc.publisherSage Publications-
dc.relation.isPartOfProceedings of the Institution of Mechanical Engineers, Part B-
dc.titleA New Generally Weighted Moving Average Control Chart Based On Taguchi’s Loss Function To Monitor Process Mean and Dispersion-
dc.typeArticle-
dc.identifier.doi10.1177/0954405415625477-
dc.type.rimsART-
dc.identifier.bibliographicCitationProceedings of the Institution of Mechanical Engineers, Part B, v.230, no.8, pp.1537 - 1547-
dc.identifier.wosid000382465700016-
dc.date.tcdate2019-02-01-
dc.citation.endPage1547-
dc.citation.number8-
dc.citation.startPage1537-
dc.citation.titleProceedings of the Institution of Mechanical Engineers, Part B-
dc.citation.volume230-
dc.contributor.affiliatedAuthorJun, CH-
dc.identifier.scopusid2-s2.0-84983433730-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc2-
dc.description.scptc1*
dc.date.scptcdate2018-05-121*
dc.type.docTypeArticle-
dc.subject.keywordPlus(X)OVER-BAR CHART-
dc.subject.keywordPlusSYSTEM SUBJECT-
dc.subject.keywordPlusVARIABILITY-
dc.subject.keywordPlusEWMA-
dc.subject.keywordPlusREPLACEMENT-
dc.subject.keywordPlusVARIANCE-
dc.subject.keywordPlusDESIGNS-
dc.subject.keywordPlusSHOCKS-
dc.subject.keywordAuthorControl chart-
dc.subject.keywordAuthoraverage run length-
dc.subject.keywordAuthorloss function-
dc.subject.keywordAuthorMonte Carlo simulation-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.relation.journalWebOfScienceCategoryEngineering, Mechanical-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-

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전치혁JUN, CHI HYUCK
Dept of Industrial & Management Enginrg
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