Monitoring the process mean with an ATTRIVAR chart

Detalhes bibliográficos
Autor(a) principal: Costa, Antonio Fernando Branco
Data de Publicação: 2020
Outros Autores: Faria Neto, Antonio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1080/03610926.2020.1828463
http://hdl.handle.net/11449/208026
Resumo: In this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data–ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the no-go gauge test, the sampling moves on to stage two, where the quality characteristic X of the first m and the remaining n-m items of the sample is measured. Otherwise, the sampling is interrupted and the process is declared to be in control. The number of tested items, if one, or two, or as many as m, is only known after the completion of the first stage. At the second stage, the (Formula presented.) value is computed and used to decide the state of the process. It is worthwhile to stress that the go/no-go gauge test truncates the X distribution and, because of that, the mathematical development to obtain the (Formula presented.) distribution is not trivial. The ATTRIVAR chart signals faster than the Double Sampling (Formula presented.) chart and, more important than that, it is simpler to use because the go/no-go gauge test reduces the frequency with which the quality characteristic X of the sample items is measured. The ATTRIVAR chart is also faster and simpler than the mixed chart. With the mixed chart, the sampling is also performed in two stages; the difference is that all items of the sample are always submitted to the go/no-go gauge test before deciding to go to stage two, where the (Formula presented.) value is computed.
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spelling Monitoring the process mean with an ATTRIVAR chartattribute/variable-type inspectionsATTRIVAR chartmixed chartprocess meanIn this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data–ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the no-go gauge test, the sampling moves on to stage two, where the quality characteristic X of the first m and the remaining n-m items of the sample is measured. Otherwise, the sampling is interrupted and the process is declared to be in control. The number of tested items, if one, or two, or as many as m, is only known after the completion of the first stage. At the second stage, the (Formula presented.) value is computed and used to decide the state of the process. It is worthwhile to stress that the go/no-go gauge test truncates the X distribution and, because of that, the mathematical development to obtain the (Formula presented.) distribution is not trivial. The ATTRIVAR chart signals faster than the Double Sampling (Formula presented.) chart and, more important than that, it is simpler to use because the go/no-go gauge test reduces the frequency with which the quality characteristic X of the sample items is measured. The ATTRIVAR chart is also faster and simpler than the mixed chart. With the mixed chart, the sampling is also performed in two stages; the difference is that all items of the sample are always submitted to the go/no-go gauge test before deciding to go to stage two, where the (Formula presented.) value is computed.IEPG Federal University of Itajubá (UNIFEI)Engineering Electric Department São Paulo State University (UNESP)Engineering Electric Department São Paulo State University (UNESP)Federal University of Itajubá (UNIFEI)Universidade Estadual Paulista (Unesp)Costa, Antonio Fernando BrancoFaria Neto, Antonio [UNESP]2021-06-25T11:05:09Z2021-06-25T11:05:09Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1080/03610926.2020.1828463Communications in Statistics - Theory and Methods.1532-415X0361-0926http://hdl.handle.net/11449/20802610.1080/03610926.2020.18284632-s2.0-85092189125Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCommunications in Statistics - Theory and Methodsinfo:eu-repo/semantics/openAccess2021-10-23T18:51:52Zoai:repositorio.unesp.br:11449/208026Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T18:51:52Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Monitoring the process mean with an ATTRIVAR chart
title Monitoring the process mean with an ATTRIVAR chart
spellingShingle Monitoring the process mean with an ATTRIVAR chart
Costa, Antonio Fernando Branco
attribute/variable-type inspections
ATTRIVAR chart
mixed chart
process mean
title_short Monitoring the process mean with an ATTRIVAR chart
title_full Monitoring the process mean with an ATTRIVAR chart
title_fullStr Monitoring the process mean with an ATTRIVAR chart
title_full_unstemmed Monitoring the process mean with an ATTRIVAR chart
title_sort Monitoring the process mean with an ATTRIVAR chart
author Costa, Antonio Fernando Branco
author_facet Costa, Antonio Fernando Branco
Faria Neto, Antonio [UNESP]
author_role author
author2 Faria Neto, Antonio [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Federal University of Itajubá (UNIFEI)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Costa, Antonio Fernando Branco
Faria Neto, Antonio [UNESP]
dc.subject.por.fl_str_mv attribute/variable-type inspections
ATTRIVAR chart
mixed chart
process mean
topic attribute/variable-type inspections
ATTRIVAR chart
mixed chart
process mean
description In this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data–ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the no-go gauge test, the sampling moves on to stage two, where the quality characteristic X of the first m and the remaining n-m items of the sample is measured. Otherwise, the sampling is interrupted and the process is declared to be in control. The number of tested items, if one, or two, or as many as m, is only known after the completion of the first stage. At the second stage, the (Formula presented.) value is computed and used to decide the state of the process. It is worthwhile to stress that the go/no-go gauge test truncates the X distribution and, because of that, the mathematical development to obtain the (Formula presented.) distribution is not trivial. The ATTRIVAR chart signals faster than the Double Sampling (Formula presented.) chart and, more important than that, it is simpler to use because the go/no-go gauge test reduces the frequency with which the quality characteristic X of the sample items is measured. The ATTRIVAR chart is also faster and simpler than the mixed chart. With the mixed chart, the sampling is also performed in two stages; the difference is that all items of the sample are always submitted to the go/no-go gauge test before deciding to go to stage two, where the (Formula presented.) value is computed.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
2021-06-25T11:05:09Z
2021-06-25T11:05:09Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1080/03610926.2020.1828463
Communications in Statistics - Theory and Methods.
1532-415X
0361-0926
http://hdl.handle.net/11449/208026
10.1080/03610926.2020.1828463
2-s2.0-85092189125
url http://dx.doi.org/10.1080/03610926.2020.1828463
http://hdl.handle.net/11449/208026
identifier_str_mv Communications in Statistics - Theory and Methods.
1532-415X
0361-0926
10.1080/03610926.2020.1828463
2-s2.0-85092189125
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Communications in Statistics - Theory and Methods
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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