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A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

dc.contributor.authorCosta, A. F. B. [UNESP]
dc.contributor.authorMachado, M. A. G. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T13:28:31Z
dc.date.available2014-05-20T13:28:31Z
dc.date.issued2009-04-01
dc.description.abstractIn this article, we propose a control chart for detecting shifts in the covariance matrix of a multivariate process. The monitoring statistic is based on the standardized sample variance of p quality characteristics we call the VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these p variances. The reasons to consider the VMAX statistic instead of the generalized variance |S| are faster detection of process changes and better diagnostic features, which mean that the VMAX statistic is better at identifying the out-of-control variable. User's familiarity with sample variances is another point in favor of the VMAX statistic. An example is presented to illustrate the application of the proposed chart.en
dc.description.affiliationSão Paulo State Univ UNESP, Prod Dept, Guaratingueta, SP, Brazil
dc.description.affiliationUnespSão Paulo State Univ UNESP, Prod Dept, Guaratingueta, SP, Brazil
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdCNPq: 307744/2006-0
dc.description.sponsorshipIdFAPESP: 06/00491-0
dc.format.extent770-779
dc.identifierhttp://dx.doi.org/10.1007/s00170-008-1502-9
dc.identifier.citationInternational Journal of Advanced Manufacturing Technology. Artington: Springer London Ltd, v. 41, n. 7-8, p. 770-779, 2009.
dc.identifier.dimensionspub.1031633167
dc.identifier.doi10.1007/s00170-008-1502-9
dc.identifier.issn0268-3768
dc.identifier.issn1433-3015
dc.identifier.lattes6100382011052492
dc.identifier.orcid0000-0002-0621-6932
dc.identifier.orcid0000-0001-6620-4573
dc.identifier.orcid0000-0002-2272-7572
dc.identifier.urihttp://hdl.handle.net/11449/9498
dc.identifier.wosWOS:000264136500016
dc.language.isoeng
dc.publisherSpringer London Ltd
dc.publisherSpringer Nature
dc.relation.ispartofInternational Journal of Advanced Manufacturing Technology
dc.relation.ispartofjcr2.601
dc.relation.ispartofsjr0,994
dc.rights.accessRightsAcesso restritopt
dc.sourceWeb of Science
dc.sourceDimensions
dc.subjectControl chartsen
dc.subjectMultivariate processesen
dc.subjectCovariance matrixen
dc.subjectGeneralized varianceen
dc.titleA new chart based on sample variances for monitoring the covariance matrix of multivariate processesen
dc.typeArtigopt
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer London Ltd
dspace.entity.typePublication
relation.isDepartmentOfPublication56bbe690-9443-4a55-a711-04b74e0aaa22
relation.isDepartmentOfPublication.latestForDiscovery56bbe690-9443-4a55-a711-04b74e0aaa22
relation.isOrgUnitOfPublicationa4071986-4355-47c3-a5a3-bd4d1a966e4f
relation.isOrgUnitOfPublication.latestForDiscoverya4071986-4355-47c3-a5a3-bd4d1a966e4f
unesp.author.lattes6100382011052492[1]
unesp.author.orcid0000-0003-2133-1098[1]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Engenharia, Guaratinguetápt
unesp.departmentProdução - FEGpt

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