The double sampling and the EWMA charts based on the sample variances

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorMachado, Marcela A. G.
dc.creatorCosta, Antonio F. B.
dc.date2014-05-20T13:28:33Z
dc.date2016-10-25T16:48:13Z
dc.date2014-05-20T13:28:33Z
dc.date2016-10-25T16:48:13Z
dc.date2008-07-01
dc.date.accessioned2017-04-05T20:11:41Z
dc.date.available2017-04-05T20:11:41Z
dc.identifierInternational Journal of Production Economics. Amsterdam: Elsevier B.V., v. 114, n. 1, p. 134-148, 2008.
dc.identifier0925-5273
dc.identifierhttp://hdl.handle.net/11449/9511
dc.identifierhttp://acervodigital.unesp.br/handle/11449/9511
dc.identifier10.1016/j.ijpe.2008.01.001
dc.identifierWOS:000257818300012
dc.identifierhttp://dx.doi.org/10.1016/j.ijpe.2008.01.001
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/857662
dc.descriptionWe propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample variances of the two quality characteristics, in short VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these two variances. The reasons to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is its faster detection of process changes and its better diagnostic feature; that is, with the VMAX statistic it is easier to identify the out-of-control variable. We study the double sampling (DS) and the exponentially weighted moving average (EWMA) charts based on the VMAX statistic. (C) 2008 Elsevier B.V. All rights reserved.
dc.languageeng
dc.publisherElsevier B.V.
dc.relationInternational Journal of Production Economics
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectcontrol charts
dc.subjectcovariance matrix
dc.subjectdouble sampling
dc.subjectEWMA
dc.subjectgeneralized variance
dc.titleThe double sampling and the EWMA charts based on the sample variances
dc.typeOtro


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