Please use this identifier to cite or link to this item: https://doi.org/10.1002/qre.543
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dc.titleInterval charting schemes for joint monitoring of process mean and variance
dc.contributor.authorGan, F.F.
dc.contributor.authorTing, K.W.
dc.contributor.authorChang, T.C.
dc.date.accessioned2014-10-28T05:12:45Z
dc.date.available2014-10-28T05:12:45Z
dc.date.issued2004-06
dc.identifier.citationGan, F.F., Ting, K.W., Chang, T.C. (2004-06). Interval charting schemes for joint monitoring of process mean and variance. Quality and Reliability Engineering International 20 (4) : 291-303. ScholarBank@NUS Repository. https://doi.org/10.1002/qre.543
dc.identifier.issn07488017
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105185
dc.description.abstractShewhart mean and variance schemes continue to enjoy great popularity among process engineers because they are easy to understand and are the most sensitive in detecting large process shifts. For some processes, for example the screen printing process in memory modules assembly, there is a possibility of the process mean and variance shifting at the same time due to special causes. Thus, instead of studying the joint behavior by looking at the mean and variance information on two separate charts, it is practical and usually more meaningful to look at the combined mean and variance information on an interval charting scheme. The interval scheme is found to have a similar run length performance to the Shewhart mean and variance schemes and only a single chart needs to be managed. A simple design procedure for the interval scheme that matches the corresponding Shewhart scheme is provided for easy implementation. Also, the interval and Shewhart schemes are compared based on real manufacturing data sets. Copyright © 2004 John Wiley & Sons, Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/qre.543
dc.sourceScopus
dc.subjectAverage run length
dc.subjectGeometrical representation
dc.subjectJoint monitoring
dc.subjectShewhart chart
dc.subjectStatistical process control
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1002/qre.543
dc.description.sourcetitleQuality and Reliability Engineering International
dc.description.volume20
dc.description.issue4
dc.description.page291-303
dc.description.codenQREIE
dc.identifier.isiut000222048700006
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