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

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dc.contributor.authorSilva, Aneirson Francisco da [UNESP]
dc.contributor.authorSilva Marins, Fernando Augusto [UNESP]
dc.contributor.authorTamura, Patricia Miyuki [UNESP]
dc.contributor.authorDias, Erica Ximenes [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-11-26T15:44:42Z
dc.date.available2018-11-26T15:44:42Z
dc.date.issued2017-07-20
dc.description.abstractThe 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.en
dc.description.affiliationSao Paulo State Univ, Fac Engn, Campus Guaratingueta, BR-12516410 Guaratingueta, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Fac Engn, Campus Guaratingueta, BR-12516410 Guaratingueta, SP, Brazil
dc.description.sponsorshipNational Council for Scientific and Technological Development
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdNational Council for Scientific and Technological Development: CNPq - 306214/2015-6
dc.description.sponsorshipIdFAPESP: FAPESP - 2015/12711-4
dc.description.sponsorshipIdFAPESP: FAPESP- 2015/24560-0
dc.format.extent278-288
dc.identifierhttp://dx.doi.org/10.1016/j.jclepro.2017.04.147
dc.identifier.citationJournal Of Cleaner Production. Oxford: Elsevier Sci Ltd, v. 157, p. 278-288, 2017.
dc.identifier.doi10.1016/j.jclepro.2017.04.147
dc.identifier.fileWOS000405883600028.pdf
dc.identifier.issn0959-6526
dc.identifier.urihttp://hdl.handle.net/11449/159627
dc.identifier.wosWOS:000405883600028
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofJournal Of Cleaner Production
dc.relation.ispartofsjr1,467
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectOverall machinery effectiveness
dc.subjectData envelopment analysis
dc.subjectMultiple criteria data envelopment analysis
dc.subjectBiO-MCDEA models
dc.subjectOverall equipment effectiveness
dc.titleBi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive companyen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
unesp.author.lattes2151242493491034[1]
unesp.author.lattes9008186664173955[2]
unesp.author.orcid0000-0002-2215-0734[1]
unesp.author.orcid0000-0001-6510-9187[2]

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