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Publicação:
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management

dc.contributor.authorOhta, Robison [UNESP]
dc.contributor.authorSalomon, Valerio A. P. [UNESP]
dc.contributor.authorSilva, Messias B. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T19:46:18Z
dc.date.available2020-12-10T19:46:18Z
dc.date.issued2020-01-01
dc.description.abstractA multi-criteria problem involves the consideration of two or more criteria in the prioritization of alternative solutions. The Analytic Hierarchy Process (AHP) is a leading multi-criteria method. Consistency checking is a great advantage of AHP. Since in AHP priorities come from pairwise comparisons, it is possible to check the consistency of these comparisons. However, a problem occurs when comparisons fail the consistency check. Then, the excluding options are to review some comparisons (Option 1) or to keep the comparisons (Option 2). This paper presents an AHP application in the maintenance management of an industrial plant. Industrial maintenance is not in the core business of an organization. However, maintenance costs can account over 50% of production costs. One of the first maintenance management decisions is on the maintenance strategy. Shall maintenance anticipate the occurrence of failure? Or shall maintenance be performed after an equipment breakdown? Answering those questions with classical AHP resulted in inconsistent comparison matrices. In that case, Fuzzy AHP (FAHP) were applied, avoiding this situation. Therefore, the purpose of this paper is to present the applications of four AHP models: Classical AHP and three models of FAHP, including hesitant fuzzy sets and intuitionistic fuzzy sets. The application of Hesitant FAHP (HFAHP) and Intuitionistic FAHP (IFAHP) are the novelty of this paper. The four AHP models were also applied in the same case of maintenance management of an industrial plant. Results were very similar, but experts could express their preferred model.en
dc.description.affiliationSao Paulo State Univ, Dept Prod, BR-12516410 Guaratingueta, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Prod, BR-12516410 Guaratingueta, SP, Brazil
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdFAPESP: 2017/22963-6
dc.format.extent601-608
dc.identifierhttp://dx.doi.org/10.3233/JIFS-179433
dc.identifier.citationJournal Of Intelligent & Fuzzy Systems. Amsterdam: Ios Press, v. 38, n. 1, p. 601-608, 2020.
dc.identifier.doi10.3233/JIFS-179433
dc.identifier.issn1064-1246
dc.identifier.urihttp://hdl.handle.net/11449/196480
dc.identifier.wosWOS:000506856200060
dc.language.isoeng
dc.publisherIos Press
dc.relation.ispartofJournal Of Intelligent & Fuzzy Systems
dc.sourceWeb of Science
dc.subjectAnalytic hierarchy process
dc.subjecthesitant fuzzy sets
dc.subjectintuitionistic fuzzy sets
dc.subjectmaintenance management
dc.titleClassical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance managementen
dc.typeArtigo
dcterms.licensehttp://www.iospress.nl/service/authors/author-copyright-agreement/
dcterms.rightsHolderIos Press
dspace.entity.typePublication
unesp.departmentProdução - FEGpt

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