LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa operacional (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382021000100204 |
Resumo: | ABSTRACT Level of repair analysis (LORA) aims to determine the optimal repair policy for complex systems’ components. A repair policy is an a priori decision about which faulty components to discard or repair, and where these actions should take place. Traditionally, LORA models have assumed the maintenance network as pre-defined and identified the resources required to perform the maintenance at each facility as an output. In this paper, the maintenance network itself is an output rather than an input. Other advantages are the ability to deploy different types of resources at the operational level and to allow precise identification of the faulty component. We propose a mixed integer programming (MIP) formulation for the optimization problem, associated with a flow model. Experiments using a set of hypotheticals, but adequate for the purposes of the study, instances provide strong evidence that the formulation’s capabilities can lead to significant cost savings. |
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LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCESmaintenancelevel of repair analysismixed integer programmingABSTRACT Level of repair analysis (LORA) aims to determine the optimal repair policy for complex systems’ components. A repair policy is an a priori decision about which faulty components to discard or repair, and where these actions should take place. Traditionally, LORA models have assumed the maintenance network as pre-defined and identified the resources required to perform the maintenance at each facility as an output. In this paper, the maintenance network itself is an output rather than an input. Other advantages are the ability to deploy different types of resources at the operational level and to allow precise identification of the faulty component. We propose a mixed integer programming (MIP) formulation for the optimization problem, associated with a flow model. Experiments using a set of hypotheticals, but adequate for the purposes of the study, instances provide strong evidence that the formulation’s capabilities can lead to significant cost savings.Sociedade Brasileira de Pesquisa Operacional2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382021000100204Pesquisa Operacional v.41 2021reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2021.041.00238051info:eu-repo/semantics/openAccessBrick,Eduardo SiqueiraPessoa,Artur AlvesSacramento,Karina Thiebauteng2021-10-08T00:00:00Zoai:scielo:S0101-74382021000100204Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2021-10-08T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
title |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
spellingShingle |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES Brick,Eduardo Siqueira maintenance level of repair analysis mixed integer programming |
title_short |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
title_full |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
title_fullStr |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
title_full_unstemmed |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
title_sort |
LEVEL OF REPAIR ANALYSIS INCLUDING FAILURE ANALYSIS AND OPTIMAL LOCATION OF MAINTENANCE FACILITIES AND RESOURCES |
author |
Brick,Eduardo Siqueira |
author_facet |
Brick,Eduardo Siqueira Pessoa,Artur Alves Sacramento,Karina Thiebaut |
author_role |
author |
author2 |
Pessoa,Artur Alves Sacramento,Karina Thiebaut |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Brick,Eduardo Siqueira Pessoa,Artur Alves Sacramento,Karina Thiebaut |
dc.subject.por.fl_str_mv |
maintenance level of repair analysis mixed integer programming |
topic |
maintenance level of repair analysis mixed integer programming |
description |
ABSTRACT Level of repair analysis (LORA) aims to determine the optimal repair policy for complex systems’ components. A repair policy is an a priori decision about which faulty components to discard or repair, and where these actions should take place. Traditionally, LORA models have assumed the maintenance network as pre-defined and identified the resources required to perform the maintenance at each facility as an output. In this paper, the maintenance network itself is an output rather than an input. Other advantages are the ability to deploy different types of resources at the operational level and to allow precise identification of the faulty component. We propose a mixed integer programming (MIP) formulation for the optimization problem, associated with a flow model. Experiments using a set of hypotheticals, but adequate for the purposes of the study, instances provide strong evidence that the formulation’s capabilities can lead to significant cost savings. |
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=S0101-74382021000100204 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382021000100204 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0101-7438.2021.041.00238051 |
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 |
Sociedade Brasileira de Pesquisa Operacional |
publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Operacional |
dc.source.none.fl_str_mv |
Pesquisa Operacional v.41 2021 reponame:Pesquisa operacional (Online) instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) instacron:SOBRAPO |
instname_str |
Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
instacron_str |
SOBRAPO |
institution |
SOBRAPO |
reponame_str |
Pesquisa operacional (Online) |
collection |
Pesquisa operacional (Online) |
repository.name.fl_str_mv |
Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
repository.mail.fl_str_mv |
||sobrapo@sobrapo.org.br |
_version_ |
1750318018464841728 |