Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3233/JIFS-179433 http://hdl.handle.net/11449/196480 |
Resumo: | A 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. |
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Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance managementAnalytic hierarchy processhesitant fuzzy setsintuitionistic fuzzy setsmaintenance managementA 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.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Sao Paulo State Univ, Dept Prod, BR-12516410 Guaratingueta, SP, BrazilSao Paulo State Univ, Dept Prod, BR-12516410 Guaratingueta, SP, BrazilFAPESP: 2017/22963-6Ios PressUniversidade Estadual Paulista (Unesp)Ohta, Robison [UNESP]Salomon, Valerio A. P. [UNESP]Silva, Messias B. [UNESP]2020-12-10T19:46:18Z2020-12-10T19:46:18Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article601-608http://dx.doi.org/10.3233/JIFS-179433Journal Of Intelligent & Fuzzy Systems. Amsterdam: Ios Press, v. 38, n. 1, p. 601-608, 2020.1064-1246http://hdl.handle.net/11449/19648010.3233/JIFS-179433WOS:000506856200060Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal Of Intelligent & Fuzzy Systemsinfo:eu-repo/semantics/openAccess2024-07-02T17:37:20Zoai:repositorio.unesp.br:11449/196480Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:47:29.407256Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
title |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
spellingShingle |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management Ohta, Robison [UNESP] Analytic hierarchy process hesitant fuzzy sets intuitionistic fuzzy sets maintenance management |
title_short |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
title_full |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
title_fullStr |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
title_full_unstemmed |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
title_sort |
Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management |
author |
Ohta, Robison [UNESP] |
author_facet |
Ohta, Robison [UNESP] Salomon, Valerio A. P. [UNESP] Silva, Messias B. [UNESP] |
author_role |
author |
author2 |
Salomon, Valerio A. P. [UNESP] Silva, Messias B. [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Ohta, Robison [UNESP] Salomon, Valerio A. P. [UNESP] Silva, Messias B. [UNESP] |
dc.subject.por.fl_str_mv |
Analytic hierarchy process hesitant fuzzy sets intuitionistic fuzzy sets maintenance management |
topic |
Analytic hierarchy process hesitant fuzzy sets intuitionistic fuzzy sets maintenance management |
description |
A 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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-10T19:46:18Z 2020-12-10T19:46:18Z 2020-01-01 |
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/10.3233/JIFS-179433 Journal Of Intelligent & Fuzzy Systems. Amsterdam: Ios Press, v. 38, n. 1, p. 601-608, 2020. 1064-1246 http://hdl.handle.net/11449/196480 10.3233/JIFS-179433 WOS:000506856200060 |
url |
http://dx.doi.org/10.3233/JIFS-179433 http://hdl.handle.net/11449/196480 |
identifier_str_mv |
Journal Of Intelligent & Fuzzy Systems. Amsterdam: Ios Press, v. 38, n. 1, p. 601-608, 2020. 1064-1246 10.3233/JIFS-179433 WOS:000506856200060 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal Of Intelligent & Fuzzy Systems |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
601-608 |
dc.publisher.none.fl_str_mv |
Ios Press |
publisher.none.fl_str_mv |
Ios Press |
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_ |
1808128238894972928 |