dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniv New Brunswick
dc.date.accessioned2014-05-20T13:28:31Z
dc.date.accessioned2022-10-05T13:26:18Z
dc.date.available2014-05-20T13:28:31Z
dc.date.available2022-10-05T13:26:18Z
dc.date.created2014-05-20T13:28:31Z
dc.date.issued2009-07-01
dc.identifierQuality and Reliability Engineering International. Chichester: John Wiley & Sons Ltd, v. 25, n. 5, p. 595-606, 2009.
dc.identifier0748-8017
dc.identifierhttp://hdl.handle.net/11449/9501
dc.identifier10.1002/qre.992
dc.identifierWOS:000268549800012
dc.identifier6100382011052492
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3885884
dc.description.abstractIn this article, we 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 are 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 synthetic chart based on the VMAX statistic. The proposed chart is always more efficient than the chart based on the generalized variance vertical bar S vertical bar. An example is presented to illustrate the application of the proposed chart. Copyright (C) 2008 John Wiley & Sons, Ltd.
dc.languageeng
dc.publisherJohn Wiley & Sons Ltd
dc.relationQuality and Reliability Engineering International
dc.relation1.604
dc.relation0,955
dc.rightsAcesso restrito
dc.sourceWeb of Science
dc.subjectcontrol charts
dc.subjectcovariance matrix
dc.subjectsynthetic
dc.subjectgeneralized variance
dc.titleThe Synthetic Control Chart Based on Two Sample Variances for Monitoring the Covariance Matrix
dc.typeArtigo


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