Outlining fuzzy decision making in maintenance planning
Main Author: | |
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Publication Date: | 2011 |
Other Authors: | , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/1822/14573 |
Summary: | In any management process, decision making assumes a very important dimension. Complex systems are commonly fed with large amounts of data that are quickly made available to experts and industrial engineers who, in most cases, are not provided with adequate decision support tools. Therefore, the quality of their decisions heavily relies on the quality and experience of them. Indeed, in general, such great availability of data makes the complex systems management planning, particularly in maintenance planning, a very difficult process, by tendentially diverting analysts from the main decisional aspects. Sometimes, unrealistic decisions come out from the process. In order to overcome these difficulties, this study purposes a set of methodological guidelines based on fuzzy theory to be applied in the planning processes, leading to optimized and more realistic results. The applicability of these guidelines is illustrated by a numerical example in the maintenance planning context. |
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Outlining fuzzy decision making in maintenance planningCost optimizationManagement planningDecision makingFuzzy set theoryUncertaintyIn any management process, decision making assumes a very important dimension. Complex systems are commonly fed with large amounts of data that are quickly made available to experts and industrial engineers who, in most cases, are not provided with adequate decision support tools. Therefore, the quality of their decisions heavily relies on the quality and experience of them. Indeed, in general, such great availability of data makes the complex systems management planning, particularly in maintenance planning, a very difficult process, by tendentially diverting analysts from the main decisional aspects. Sometimes, unrealistic decisions come out from the process. In order to overcome these difficulties, this study purposes a set of methodological guidelines based on fuzzy theory to be applied in the planning processes, leading to optimized and more realistic results. The applicability of these guidelines is illustrated by a numerical example in the maintenance planning context.Universidade do MinhoCarvalho, Mariana Teixeira Baptista deNunes, Eusébio P.Telhada, José2011-112011-11-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/14573enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:47:04Zoai:repositorium.sdum.uminho.pt:1822/14573Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:04:26.842732Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Outlining fuzzy decision making in maintenance planning |
title |
Outlining fuzzy decision making in maintenance planning |
spellingShingle |
Outlining fuzzy decision making in maintenance planning Carvalho, Mariana Teixeira Baptista de Cost optimization Management planning Decision making Fuzzy set theory Uncertainty |
title_short |
Outlining fuzzy decision making in maintenance planning |
title_full |
Outlining fuzzy decision making in maintenance planning |
title_fullStr |
Outlining fuzzy decision making in maintenance planning |
title_full_unstemmed |
Outlining fuzzy decision making in maintenance planning |
title_sort |
Outlining fuzzy decision making in maintenance planning |
author |
Carvalho, Mariana Teixeira Baptista de |
author_facet |
Carvalho, Mariana Teixeira Baptista de Nunes, Eusébio P. Telhada, José |
author_role |
author |
author2 |
Nunes, Eusébio P. Telhada, José |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Carvalho, Mariana Teixeira Baptista de Nunes, Eusébio P. Telhada, José |
dc.subject.por.fl_str_mv |
Cost optimization Management planning Decision making Fuzzy set theory Uncertainty |
topic |
Cost optimization Management planning Decision making Fuzzy set theory Uncertainty |
description |
In any management process, decision making assumes a very important dimension. Complex systems are commonly fed with large amounts of data that are quickly made available to experts and industrial engineers who, in most cases, are not provided with adequate decision support tools. Therefore, the quality of their decisions heavily relies on the quality and experience of them. Indeed, in general, such great availability of data makes the complex systems management planning, particularly in maintenance planning, a very difficult process, by tendentially diverting analysts from the main decisional aspects. Sometimes, unrealistic decisions come out from the process. In order to overcome these difficulties, this study purposes a set of methodological guidelines based on fuzzy theory to be applied in the planning processes, leading to optimized and more realistic results. The applicability of these guidelines is illustrated by a numerical example in the maintenance planning context. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-11 2011-11-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/14573 |
url |
http://hdl.handle.net/1822/14573 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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