A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes

Detalhes bibliográficos
Autor(a) principal: Magalhães,Wauires Ribeiro de
Data de Publicação: 2021
Outros Autores: Lima Junior,Francisco Rodrigues
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Gestão & Produção
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000400202
Resumo: Abstract: FMEA is one of the most used methods to support risk analysis in business processes. Nonetheless, this method has some limitations, including the use of only three decision criteria, whose weights are not considered. With the objective of adding new features to FMEA, some studies combine it with multicriteria decision methods. This study proposes a model based on FMEA and Fuzzy TOPSIS to support risk prioritization in industrial production processes. A pilot application was performed to analyze and prioritize the risks of potential failures in a nodular iron melting and casting process. Based on the opinion of four company experts, potential failure modes were defined and assessed. The experts also chose the criteria and their respective weights. The pilot application results suggest that “fading time exceeded” and “chemical composition outside of the specified” should be treated with highest priority. The sensitivity analysis test results corroborate the relevance of these failures and demonstrate the effect of criteria weight variation. The proposed model is useful to support the formulation of actions plans focused on minimizing or eliminating priority failures. Other contributions from this study consist of: considering criteria weight; allowing the use of linguistic terms to express the decision makers’ judgments; considering the costs relating to the failures; and supporting group decisions.
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spelling A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processesRisk assessmentFMEAFuzzy TOPSISMulticriteria decision-makingAbstract: FMEA is one of the most used methods to support risk analysis in business processes. Nonetheless, this method has some limitations, including the use of only three decision criteria, whose weights are not considered. With the objective of adding new features to FMEA, some studies combine it with multicriteria decision methods. This study proposes a model based on FMEA and Fuzzy TOPSIS to support risk prioritization in industrial production processes. A pilot application was performed to analyze and prioritize the risks of potential failures in a nodular iron melting and casting process. Based on the opinion of four company experts, potential failure modes were defined and assessed. The experts also chose the criteria and their respective weights. The pilot application results suggest that “fading time exceeded” and “chemical composition outside of the specified” should be treated with highest priority. The sensitivity analysis test results corroborate the relevance of these failures and demonstrate the effect of criteria weight variation. The proposed model is useful to support the formulation of actions plans focused on minimizing or eliminating priority failures. Other contributions from this study consist of: considering criteria weight; allowing the use of linguistic terms to express the decision makers’ judgments; considering the costs relating to the failures; and supporting group decisions.Universidade Federal de São Carlos2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000400202Gestão & Produção v.28 n.4 2021reponame:Gestão & Produçãoinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCAR10.1590/1806-9649-2020v28e5535info:eu-repo/semantics/openAccessMagalhães,Wauires Ribeiro deLima Junior,Francisco Rodrigueseng2021-10-19T00:00:00Zoai:scielo:S0104-530X2021000400202Revistahttps://www.gestaoeproducao.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpgp@dep.ufscar.br||revistagestaoemanalise@unichristus.edu.br1806-96490104-530Xopendoar:2021-10-19T00:00Gestão & Produção - Universidade Federal de São Carlos (UFSCAR)false
dc.title.none.fl_str_mv A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
title A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
spellingShingle A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
Magalhães,Wauires Ribeiro de
Risk assessment
FMEA
Fuzzy TOPSIS
Multicriteria decision-making
title_short A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
title_full A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
title_fullStr A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
title_full_unstemmed A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
title_sort A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial processes
author Magalhães,Wauires Ribeiro de
author_facet Magalhães,Wauires Ribeiro de
Lima Junior,Francisco Rodrigues
author_role author
author2 Lima Junior,Francisco Rodrigues
author2_role author
dc.contributor.author.fl_str_mv Magalhães,Wauires Ribeiro de
Lima Junior,Francisco Rodrigues
dc.subject.por.fl_str_mv Risk assessment
FMEA
Fuzzy TOPSIS
Multicriteria decision-making
topic Risk assessment
FMEA
Fuzzy TOPSIS
Multicriteria decision-making
description Abstract: FMEA is one of the most used methods to support risk analysis in business processes. Nonetheless, this method has some limitations, including the use of only three decision criteria, whose weights are not considered. With the objective of adding new features to FMEA, some studies combine it with multicriteria decision methods. This study proposes a model based on FMEA and Fuzzy TOPSIS to support risk prioritization in industrial production processes. A pilot application was performed to analyze and prioritize the risks of potential failures in a nodular iron melting and casting process. Based on the opinion of four company experts, potential failure modes were defined and assessed. The experts also chose the criteria and their respective weights. The pilot application results suggest that “fading time exceeded” and “chemical composition outside of the specified” should be treated with highest priority. The sensitivity analysis test results corroborate the relevance of these failures and demonstrate the effect of criteria weight variation. The proposed model is useful to support the formulation of actions plans focused on minimizing or eliminating priority failures. Other contributions from this study consist of: considering criteria weight; allowing the use of linguistic terms to express the decision makers’ judgments; considering the costs relating to the failures; and supporting group decisions.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000400202
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000400202
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1806-9649-2020v28e5535
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal de São Carlos
publisher.none.fl_str_mv Universidade Federal de São Carlos
dc.source.none.fl_str_mv Gestão & Produção v.28 n.4 2021
reponame:Gestão & Produção
instname:Universidade Federal de São Carlos (UFSCAR)
instacron:UFSCAR
instname_str Universidade Federal de São Carlos (UFSCAR)
instacron_str UFSCAR
institution UFSCAR
reponame_str Gestão & Produção
collection Gestão & Produção
repository.name.fl_str_mv Gestão & Produção - Universidade Federal de São Carlos (UFSCAR)
repository.mail.fl_str_mv gp@dep.ufscar.br||revistagestaoemanalise@unichristus.edu.br
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