Economic design of and R charts under Weibull shock models

Bibliographic Details
Main Author: Costa, Antonio F. B. [UNESP]
Publication Date: 2013
Other Authors: Rahim, M. A.
Format: Article
Language: eng
Source: Repositório Institucional da UNESP
Download full: http://dx.doi.org/10.1080/03610926.2012.748914
http://hdl.handle.net/11449/219941
Summary: This article considers the problem of a continuous production process, whose mean and variance are simultaneously monitored by and R control charts, respectively. The product variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as, tool wear-out, overheating, or vibration). One changes the process mean and the other the process variance. The occurrence of one kind of the assignable causes does not preclude the occurrence of the other kind. The occurrence times of the assignable causes are described by Weibull distributions having increasing failure rates. A cost model is developed for determining the economic design parameters. A non uniform decreasing sampling interval scheme is adopted to incorporate the effects of process deterioration. A two-step search procedure is employed to determine the economically optimum design parameters. The relative contribution of this article over the results obtained in Costa (1993) is addressed. This article introduces a few new assumptions and provides some theoretical derivations and results. These results may serve as readily available references for future studies. The article shows through numerical examples that ignoring the true (by assumption) Weibull shock model and incorrectly assuming exponential distributions of times to occurrences of assignable causes (and using constant sampling schemes), results in sizeable cost penalties. A sensitivity analysis of the model with respect to Weibull distribution parameters is performed. © 2013 Copyright Taylor and Francis Group, LLC.
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spelling Economic design of and R charts under Weibull shock modelsIncreasing hazard rateIntegrated hazard criterionNon uniform sampling intervalOptimum design parametersThis article considers the problem of a continuous production process, whose mean and variance are simultaneously monitored by and R control charts, respectively. The product variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as, tool wear-out, overheating, or vibration). One changes the process mean and the other the process variance. The occurrence of one kind of the assignable causes does not preclude the occurrence of the other kind. The occurrence times of the assignable causes are described by Weibull distributions having increasing failure rates. A cost model is developed for determining the economic design parameters. A non uniform decreasing sampling interval scheme is adopted to incorporate the effects of process deterioration. A two-step search procedure is employed to determine the economically optimum design parameters. The relative contribution of this article over the results obtained in Costa (1993) is addressed. This article introduces a few new assumptions and provides some theoretical derivations and results. These results may serve as readily available references for future studies. The article shows through numerical examples that ignoring the true (by assumption) Weibull shock model and incorrectly assuming exponential distributions of times to occurrences of assignable causes (and using constant sampling schemes), results in sizeable cost penalties. A sensitivity analysis of the model with respect to Weibull distribution parameters is performed. © 2013 Copyright Taylor and Francis Group, LLC.Natural Sciences and Engineering Research Council of CanadaFEG-UNESP, GuaratinguetáFaculty of Administration University of New Brunswick, Fredericton, NB E3B 5A3FEG-UNESP, GuaratinguetáUniversidade Estadual Paulista (UNESP)University of New BrunswickCosta, Antonio F. B. [UNESP]Rahim, M. A.2022-04-28T18:58:34Z2022-04-28T18:58:34Z2013-11-02info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article3902-3925http://dx.doi.org/10.1080/03610926.2012.748914Communications in Statistics - Theory and Methods, v. 42, n. 21, p. 3902-3925, 2013.0361-09261532-415Xhttp://hdl.handle.net/11449/21994110.1080/03610926.2012.7489142-s2.0-84885572686Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCommunications in Statistics - Theory and Methodsinfo:eu-repo/semantics/openAccess2022-04-28T18:58:34Zoai:repositorio.unesp.br:11449/219941Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T18:58:34Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Economic design of and R charts under Weibull shock models
title Economic design of and R charts under Weibull shock models
spellingShingle Economic design of and R charts under Weibull shock models
Costa, Antonio F. B. [UNESP]
Increasing hazard rate
Integrated hazard criterion
Non uniform sampling interval
Optimum design parameters
title_short Economic design of and R charts under Weibull shock models
title_full Economic design of and R charts under Weibull shock models
title_fullStr Economic design of and R charts under Weibull shock models
title_full_unstemmed Economic design of and R charts under Weibull shock models
title_sort Economic design of and R charts under Weibull shock models
author Costa, Antonio F. B. [UNESP]
author_facet Costa, Antonio F. B. [UNESP]
Rahim, M. A.
author_role author
author2 Rahim, M. A.
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
University of New Brunswick
dc.contributor.author.fl_str_mv Costa, Antonio F. B. [UNESP]
Rahim, M. A.
dc.subject.por.fl_str_mv Increasing hazard rate
Integrated hazard criterion
Non uniform sampling interval
Optimum design parameters
topic Increasing hazard rate
Integrated hazard criterion
Non uniform sampling interval
Optimum design parameters
description This article considers the problem of a continuous production process, whose mean and variance are simultaneously monitored by and R control charts, respectively. The product variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as, tool wear-out, overheating, or vibration). One changes the process mean and the other the process variance. The occurrence of one kind of the assignable causes does not preclude the occurrence of the other kind. The occurrence times of the assignable causes are described by Weibull distributions having increasing failure rates. A cost model is developed for determining the economic design parameters. A non uniform decreasing sampling interval scheme is adopted to incorporate the effects of process deterioration. A two-step search procedure is employed to determine the economically optimum design parameters. The relative contribution of this article over the results obtained in Costa (1993) is addressed. This article introduces a few new assumptions and provides some theoretical derivations and results. These results may serve as readily available references for future studies. The article shows through numerical examples that ignoring the true (by assumption) Weibull shock model and incorrectly assuming exponential distributions of times to occurrences of assignable causes (and using constant sampling schemes), results in sizeable cost penalties. A sensitivity analysis of the model with respect to Weibull distribution parameters is performed. © 2013 Copyright Taylor and Francis Group, LLC.
publishDate 2013
dc.date.none.fl_str_mv 2013-11-02
2022-04-28T18:58:34Z
2022-04-28T18:58:34Z
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/10.1080/03610926.2012.748914
Communications in Statistics - Theory and Methods, v. 42, n. 21, p. 3902-3925, 2013.
0361-0926
1532-415X
http://hdl.handle.net/11449/219941
10.1080/03610926.2012.748914
2-s2.0-84885572686
url http://dx.doi.org/10.1080/03610926.2012.748914
http://hdl.handle.net/11449/219941
identifier_str_mv Communications in Statistics - Theory and Methods, v. 42, n. 21, p. 3902-3925, 2013.
0361-0926
1532-415X
10.1080/03610926.2012.748914
2-s2.0-84885572686
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.format.none.fl_str_mv 3902-3925
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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