Th e Non-Central Chi-Square Chart with Double Sampling

Detalhes bibliográficos
Autor(a) principal: Costa, Antonio F. B.
Data de Publicação: 2010
Outros Autores: Magalhães, Maysa S. de, Epprecht, Eugenio K.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Operations & Production Management (Online)
Texto Completo: https://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2
Resumo: In this article, we consider a non-central chi-square chart with double sampling (DS χ2 chart) to control the process mean and variance. As in the case of Shewhart control charts, samples of fi xed size are taken from the process at regular time intervals; however, the sampling is performed in two stages. Let X be the process quality variable being measured. During the fi rst stage, one item of the sample is inspected; if its X value is closeto the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and anon-central chi-square statistic, say T, is computed taking into account all n items of the sample, that is, their X values. A signal is triggered when the sample point given by theT value falls above the upper control limit of the proposed chart. The DS χ2 chart performs better than the joint X and R charts, except when there is a large change in the process mean. Furthermore, if the DS χ2 chart is used for monitoring diameters, volumes, weights, etc., then the employment of appropriate devices, such as go-no-go gauges can reduce the effort to decide if the sampling should go to the second stage or not.
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spelling Th e Non-Central Chi-Square Chart with Double SamplingIn this article, we consider a non-central chi-square chart with double sampling (DS χ2 chart) to control the process mean and variance. As in the case of Shewhart control charts, samples of fi xed size are taken from the process at regular time intervals; however, the sampling is performed in two stages. Let X be the process quality variable being measured. During the fi rst stage, one item of the sample is inspected; if its X value is closeto the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and anon-central chi-square statistic, say T, is computed taking into account all n items of the sample, that is, their X values. A signal is triggered when the sample point given by theT value falls above the upper control limit of the proposed chart. The DS χ2 chart performs better than the joint X and R charts, except when there is a large change in the process mean. Furthermore, if the DS χ2 chart is used for monitoring diameters, volumes, weights, etc., then the employment of appropriate devices, such as go-no-go gauges can reduce the effort to decide if the sampling should go to the second stage or not.Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)2010-02-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2Brazilian Journal of Operations & Production Management; Vol. 2 No. 2 (2005): December, 2005; 21-382237-8960reponame:Brazilian Journal of Operations & Production Management (Online)instname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPROenghttps://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2/pdf_32Costa, Antonio F. B.Magalhães, Maysa S. deEpprecht, Eugenio K.info:eu-repo/semantics/openAccess2019-04-04T07:29:08Zoai:ojs.bjopm.org.br:article/35Revistahttps://bjopm.org.br/bjopmONGhttps://bjopm.org.br/bjopm/oaibjopm.journal@gmail.com2237-89601679-8171opendoar:2023-03-13T09:45:01.300169Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)false
dc.title.none.fl_str_mv Th e Non-Central Chi-Square Chart with Double Sampling
title Th e Non-Central Chi-Square Chart with Double Sampling
spellingShingle Th e Non-Central Chi-Square Chart with Double Sampling
Costa, Antonio F. B.
title_short Th e Non-Central Chi-Square Chart with Double Sampling
title_full Th e Non-Central Chi-Square Chart with Double Sampling
title_fullStr Th e Non-Central Chi-Square Chart with Double Sampling
title_full_unstemmed Th e Non-Central Chi-Square Chart with Double Sampling
title_sort Th e Non-Central Chi-Square Chart with Double Sampling
author Costa, Antonio F. B.
author_facet Costa, Antonio F. B.
Magalhães, Maysa S. de
Epprecht, Eugenio K.
author_role author
author2 Magalhães, Maysa S. de
Epprecht, Eugenio K.
author2_role author
author
dc.contributor.author.fl_str_mv Costa, Antonio F. B.
Magalhães, Maysa S. de
Epprecht, Eugenio K.
description In this article, we consider a non-central chi-square chart with double sampling (DS χ2 chart) to control the process mean and variance. As in the case of Shewhart control charts, samples of fi xed size are taken from the process at regular time intervals; however, the sampling is performed in two stages. Let X be the process quality variable being measured. During the fi rst stage, one item of the sample is inspected; if its X value is closeto the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and anon-central chi-square statistic, say T, is computed taking into account all n items of the sample, that is, their X values. A signal is triggered when the sample point given by theT value falls above the upper control limit of the proposed chart. The DS χ2 chart performs better than the joint X and R charts, except when there is a large change in the process mean. Furthermore, if the DS χ2 chart is used for monitoring diameters, volumes, weights, etc., then the employment of appropriate devices, such as go-no-go gauges can reduce the effort to decide if the sampling should go to the second stage or not.
publishDate 2010
dc.date.none.fl_str_mv 2010-02-08
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2
url https://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2/pdf_32
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)
publisher.none.fl_str_mv Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)
dc.source.none.fl_str_mv Brazilian Journal of Operations & Production Management; Vol. 2 No. 2 (2005): December, 2005; 21-38
2237-8960
reponame:Brazilian Journal of Operations & Production Management (Online)
instname:Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron:ABEPRO
instname_str Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron_str ABEPRO
institution ABEPRO
reponame_str Brazilian Journal of Operations & Production Management (Online)
collection Brazilian Journal of Operations & Production Management (Online)
repository.name.fl_str_mv Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)
repository.mail.fl_str_mv bjopm.journal@gmail.com
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