Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/61597
DC FieldValueLanguage
dc.contributor統計系en_US
dc.creator楊素芬zh_TW
dc.creatorYang, S.-F. ; Cheng, S. W-
dc.date2011.12en_US
dc.date.accessioned2013-11-11T09:44:06Z-
dc.date.available2013-11-11T09:44:06Z-
dc.date.issued2013-11-11T09:44:06Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/61597-
dc.description.abstractNot all data in practice came from a process with normal distribution. When the process distribution is non-normal or unknown, the commonly used Shewhart control charts are not suitable. In this paper, a new non-parametric CUSUM Mean Chart is proposed to monitor the possible small mean shifts in the process. The sampling properties of the new monitoring statistics are examined and the average run lengths of the proposed chart are examined. Two numerical examples are used to illustrate the proposed chart and compare with the two existing charts, assuming normality and Beta distribution, respectively. The CUSUM Mean Chart showed better detection ability than those two charts in monitoring and detecting small process mean shifts. Copyright © 2010 John Wiley & Sons, Ltd.en_US
dc.format.extent340603 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.relationQuality and reliability engineering international, 27(7) , 867-875en_US
dc.subjectCUSUM chart;process mean;binomial distribution;beta distribution;ARLen_US
dc.titleA new non-parametric CUSUM mean charten_US
dc.typearticleen
dc.identifier.doi10.1002/qre.1171-
dc.doi.urihttp://dx.doi.org/10.1002/qre.1171-
item.languageiso639-1en_US-
item.cerifentitytypePublications-
item.grantfulltextrestricted-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
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