Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
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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Repositório Institucional da UNESP |
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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 |
|
_version_ |
1808128738722840576 |