What are the key determinants of maintenance performance?
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Production |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100212 |
Resumo: | Abstract Paper aims The main objective of the research is to present a combination of fuzzy decision-making techniques to measure the performance of preventive maintenance systems. Originality This research is a timely response to studying the prominent role of preventive maintenance performance in reducing cost, profitability, and overall organization’s output. Research method This study considers the application of “fuzzy DEMATEL” and ANP techniques for measuring maintenance performance and determining the causal relationships between the criteria and sub-criteria. Main findings It is conjectured that functional and technical criteria, along that with individual and the environmental are of great importance. Among the sub-criteria, employee satisfaction, growth and learning, availability of machinery and equipment, quality of maintenance by the skilled and highly-trained workforce, deem to be the most important ones. Implications for theory and practice The application of the decision techniques and the proposed measurement model for continuous improvement and promotion of maintenance performance. |
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What are the key determinants of maintenance performance?MaintenancePM Performance MeasurementFuzzy DEMATEL TechniqueFuzzy Network Analysis (ANP)Multi-criteria Decision MakingAbstract Paper aims The main objective of the research is to present a combination of fuzzy decision-making techniques to measure the performance of preventive maintenance systems. Originality This research is a timely response to studying the prominent role of preventive maintenance performance in reducing cost, profitability, and overall organization’s output. Research method This study considers the application of “fuzzy DEMATEL” and ANP techniques for measuring maintenance performance and determining the causal relationships between the criteria and sub-criteria. Main findings It is conjectured that functional and technical criteria, along that with individual and the environmental are of great importance. Among the sub-criteria, employee satisfaction, growth and learning, availability of machinery and equipment, quality of maintenance by the skilled and highly-trained workforce, deem to be the most important ones. Implications for theory and practice The application of the decision techniques and the proposed measurement model for continuous improvement and promotion of maintenance performance.Associação Brasileira de Engenharia de Produção2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100212Production v.30 2020reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20190155info:eu-repo/semantics/openAccessDarestani,Soroush AvakhGanji,MandanaImannezhad,Ranaeng2020-10-15T00:00:00Zoai:scielo:S0103-65132020000100212Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2020-10-15T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
What are the key determinants of maintenance performance? |
title |
What are the key determinants of maintenance performance? |
spellingShingle |
What are the key determinants of maintenance performance? Darestani,Soroush Avakh Maintenance PM Performance Measurement Fuzzy DEMATEL Technique Fuzzy Network Analysis (ANP) Multi-criteria Decision Making |
title_short |
What are the key determinants of maintenance performance? |
title_full |
What are the key determinants of maintenance performance? |
title_fullStr |
What are the key determinants of maintenance performance? |
title_full_unstemmed |
What are the key determinants of maintenance performance? |
title_sort |
What are the key determinants of maintenance performance? |
author |
Darestani,Soroush Avakh |
author_facet |
Darestani,Soroush Avakh Ganji,Mandana Imannezhad,Rana |
author_role |
author |
author2 |
Ganji,Mandana Imannezhad,Rana |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Darestani,Soroush Avakh Ganji,Mandana Imannezhad,Rana |
dc.subject.por.fl_str_mv |
Maintenance PM Performance Measurement Fuzzy DEMATEL Technique Fuzzy Network Analysis (ANP) Multi-criteria Decision Making |
topic |
Maintenance PM Performance Measurement Fuzzy DEMATEL Technique Fuzzy Network Analysis (ANP) Multi-criteria Decision Making |
description |
Abstract Paper aims The main objective of the research is to present a combination of fuzzy decision-making techniques to measure the performance of preventive maintenance systems. Originality This research is a timely response to studying the prominent role of preventive maintenance performance in reducing cost, profitability, and overall organization’s output. Research method This study considers the application of “fuzzy DEMATEL” and ANP techniques for measuring maintenance performance and determining the causal relationships between the criteria and sub-criteria. Main findings It is conjectured that functional and technical criteria, along that with individual and the environmental are of great importance. Among the sub-criteria, employee satisfaction, growth and learning, availability of machinery and equipment, quality of maintenance by the skilled and highly-trained workforce, deem to be the most important ones. Implications for theory and practice The application of the decision techniques and the proposed measurement model for continuous improvement and promotion of maintenance performance. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
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=S0103-65132020000100212 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100212 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-6513.20190155 |
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 |
Associação Brasileira de Engenharia de Produção |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
dc.source.none.fl_str_mv |
Production v.30 2020 reponame:Production instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Production |
collection |
Production |
repository.name.fl_str_mv |
Production - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
||production@editoracubo.com.br |
_version_ |
1754213154534981632 |