Publicação:
A hierarchy of adaptive (X)over-bar control charts

dc.contributor.authorMagalhaes, M.
dc.contributor.authorCosta, A. F. B.
dc.contributor.authorMoura Neto, F. D.
dc.contributor.institutionIBGE
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade do Estado do Rio de Janeiro (UERJ)
dc.date.accessioned2014-05-20T15:33:04Z
dc.date.available2014-05-20T15:33:04Z
dc.date.issued2009-06-01
dc.description.abstractThe purpose of this article is to present a statistical design of a hierarchy of two-states adaptive parameters (X) over bar charts. We assume that the shift in the process mean does not occur at the beginning of the production process but at some random time in the future. The occurrence time of the shift is assumed to be an exponentially distributed random variable. This assumption allows the application of the Markov chain approach for developing performance measures. Seven adaptive (X) over bar charts result from the combinations of the design parameters, that is, the sample size, the sampling interval, and the factor used to define the control limits, when one, two, or all of them are allowed to vary. arranged in a hierarchy. When comparing the performance between different two-state charts one sometimes can use a chart with fewer parameters varying and yet achieve good performance, however this depends on the size of process shift. One can change the probability of the control system to be in a state of loose control: considering that, its effect on the adjusted average time to signal and on the design parameters was analyzed numerically. (C) 2009 Elsevier B.V. All rights reserved.en
dc.description.affiliationIBGE, ENCE, Brazilian Inst Geog & Stat, Natl Sch Stat Sci, BR-20231050 Rio de Janeiro, Brazil
dc.description.affiliationState Univ São Paulo FEG UNESP, Guaratingueta Fac Engn, BR-12516410 Guaratingueta, SP, Brazil
dc.description.affiliationState Univ Rio de Janeiro IPRJ UERJ, Polytech Inst, BR-28601970 Nova Friburgo, RJ, Brazil
dc.description.affiliationUnespState Univ São Paulo FEG UNESP, Guaratingueta Fac Engn, BR-12516410 Guaratingueta, SP, Brazil
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)
dc.format.extent271-283
dc.identifierhttp://dx.doi.org/10.1016/j.ijpe.2008.10.017
dc.identifier.citationInternational Journal of Production Economics. Amsterdam: Elsevier B.V., v. 119, n. 2, p. 271-283, 2009.
dc.identifier.doi10.1016/j.ijpe.2008.10.017
dc.identifier.issn0925-5273
dc.identifier.urihttp://hdl.handle.net/11449/41799
dc.identifier.wosWOS:000267643400006
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofInternational Journal of Production Economics
dc.relation.ispartofjcr4.407
dc.relation.ispartofsjr2,401
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectQuality controlen
dc.subjectStatistical process controlen
dc.subjectAdaptive control chartsen
dc.titleA hierarchy of adaptive (X)over-bar control chartsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
dspace.entity.typePublication
unesp.author.lattes6100382011052492[2]
unesp.author.orcid0000-0003-2133-1098[2]

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