Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company

Detalhes bibliográficos
Autor(a) principal: Silva, Aneirson Francisco da [UNESP]
Data de Publicação: 2017
Outros Autores: Silva Marins, Fernando Augusto [UNESP], Tamura, Patricia Miyuki [UNESP], Dias, Erica Ximenes [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.jclepro.2017.04.147
http://hdl.handle.net/11449/159627
Resumo: The mass production companies need to seek high efficiency in the use of equipment and human resources, as well as in the consumption of their inputs. One of the key methods to address these challenges is the adoption of Overall Equipment Effectiveness, derived from Total Productive Maintenance. This work aims to propose a new efficiency indicator, called Overall Machinery Effectiveness, to be applied in an automotive company in Brazil that adopted Overall Equipment Effectiveness indicator. The studied company made available production data from ten months, associated to two Press machines, generating twenty Decision Making Units for Data Envelopment Analysis and Bi-Objective Multiple Criteria Data Envelopment Analysis models application. As results, Press #2 was identified as being the most critical because, among the first ten DMUs in the efficiency ranking, seven are associated to Press #1. The targets values recommended by the new indicator were considered feasible to be implemented by the company, thus validating in practice the new proposed procedure for the management of machines effectiveness. Moreover, the identification of the relevant variables (input and output) for the Press #1, and Press #2, allowed the decision maker to act in the best way to increase their efficiency. (C) 2017 Elsevier Ltd. All rights reserved.
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spelling Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive companyOverall machinery effectivenessData envelopment analysisMultiple criteria data envelopment analysisBiO-MCDEA modelsOverall equipment effectivenessThe mass production companies need to seek high efficiency in the use of equipment and human resources, as well as in the consumption of their inputs. One of the key methods to address these challenges is the adoption of Overall Equipment Effectiveness, derived from Total Productive Maintenance. This work aims to propose a new efficiency indicator, called Overall Machinery Effectiveness, to be applied in an automotive company in Brazil that adopted Overall Equipment Effectiveness indicator. The studied company made available production data from ten months, associated to two Press machines, generating twenty Decision Making Units for Data Envelopment Analysis and Bi-Objective Multiple Criteria Data Envelopment Analysis models application. As results, Press #2 was identified as being the most critical because, among the first ten DMUs in the efficiency ranking, seven are associated to Press #1. The targets values recommended by the new indicator were considered feasible to be implemented by the company, thus validating in practice the new proposed procedure for the management of machines effectiveness. Moreover, the identification of the relevant variables (input and output) for the Press #1, and Press #2, allowed the decision maker to act in the best way to increase their efficiency. (C) 2017 Elsevier Ltd. All rights reserved.National Council for Scientific and Technological DevelopmentFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Sao Paulo State Univ, Fac Engn, Campus Guaratingueta, BR-12516410 Guaratingueta, SP, BrazilSao Paulo State Univ, Fac Engn, Campus Guaratingueta, BR-12516410 Guaratingueta, SP, BrazilNational Council for Scientific and Technological Development: CNPq - 306214/2015-6FAPESP: FAPESP - 2015/12711-4FAPESP: FAPESP- 2015/24560-0Elsevier B.V.Universidade Estadual Paulista (Unesp)Silva, Aneirson Francisco da [UNESP]Silva Marins, Fernando Augusto [UNESP]Tamura, Patricia Miyuki [UNESP]Dias, Erica Ximenes [UNESP]2018-11-26T15:44:42Z2018-11-26T15:44:42Z2017-07-20info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article278-288application/pdfhttp://dx.doi.org/10.1016/j.jclepro.2017.04.147Journal Of Cleaner Production. Oxford: Elsevier Sci Ltd, v. 157, p. 278-288, 2017.0959-6526http://hdl.handle.net/11449/15962710.1016/j.jclepro.2017.04.147WOS:000405883600028WOS000405883600028.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal Of Cleaner Production1,467info:eu-repo/semantics/openAccess2023-11-06T06:08:22Zoai:repositorio.unesp.br:11449/159627Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:00:35.186283Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
title Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
spellingShingle Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
Silva, Aneirson Francisco da [UNESP]
Overall machinery effectiveness
Data envelopment analysis
Multiple criteria data envelopment analysis
BiO-MCDEA models
Overall equipment effectiveness
title_short Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
title_full Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
title_fullStr Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
title_full_unstemmed Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
title_sort Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
author Silva, Aneirson Francisco da [UNESP]
author_facet Silva, Aneirson Francisco da [UNESP]
Silva Marins, Fernando Augusto [UNESP]
Tamura, Patricia Miyuki [UNESP]
Dias, Erica Ximenes [UNESP]
author_role author
author2 Silva Marins, Fernando Augusto [UNESP]
Tamura, Patricia Miyuki [UNESP]
Dias, Erica Ximenes [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Silva, Aneirson Francisco da [UNESP]
Silva Marins, Fernando Augusto [UNESP]
Tamura, Patricia Miyuki [UNESP]
Dias, Erica Ximenes [UNESP]
dc.subject.por.fl_str_mv Overall machinery effectiveness
Data envelopment analysis
Multiple criteria data envelopment analysis
BiO-MCDEA models
Overall equipment effectiveness
topic Overall machinery effectiveness
Data envelopment analysis
Multiple criteria data envelopment analysis
BiO-MCDEA models
Overall equipment effectiveness
description The mass production companies need to seek high efficiency in the use of equipment and human resources, as well as in the consumption of their inputs. One of the key methods to address these challenges is the adoption of Overall Equipment Effectiveness, derived from Total Productive Maintenance. This work aims to propose a new efficiency indicator, called Overall Machinery Effectiveness, to be applied in an automotive company in Brazil that adopted Overall Equipment Effectiveness indicator. The studied company made available production data from ten months, associated to two Press machines, generating twenty Decision Making Units for Data Envelopment Analysis and Bi-Objective Multiple Criteria Data Envelopment Analysis models application. As results, Press #2 was identified as being the most critical because, among the first ten DMUs in the efficiency ranking, seven are associated to Press #1. The targets values recommended by the new indicator were considered feasible to be implemented by the company, thus validating in practice the new proposed procedure for the management of machines effectiveness. Moreover, the identification of the relevant variables (input and output) for the Press #1, and Press #2, allowed the decision maker to act in the best way to increase their efficiency. (C) 2017 Elsevier Ltd. All rights reserved.
publishDate 2017
dc.date.none.fl_str_mv 2017-07-20
2018-11-26T15:44:42Z
2018-11-26T15:44:42Z
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/10.1016/j.jclepro.2017.04.147
Journal Of Cleaner Production. Oxford: Elsevier Sci Ltd, v. 157, p. 278-288, 2017.
0959-6526
http://hdl.handle.net/11449/159627
10.1016/j.jclepro.2017.04.147
WOS:000405883600028
WOS000405883600028.pdf
url http://dx.doi.org/10.1016/j.jclepro.2017.04.147
http://hdl.handle.net/11449/159627
identifier_str_mv Journal Of Cleaner Production. Oxford: Elsevier Sci Ltd, v. 157, p. 278-288, 2017.
0959-6526
10.1016/j.jclepro.2017.04.147
WOS:000405883600028
WOS000405883600028.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal Of Cleaner Production
1,467
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 278-288
application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Web of Science
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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