Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Gestão & Produção |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2020000300301 |
Resumo: | Abstract: Advanced Manufacturing or Industry 4.0 concepts bring new advances and challenges to current industrial processes. Such concepts are not always well understood and their results in terms of production performance may not be clear. This work proposes a comparison between a traditional manufacturing process and an advanced manufacturing process, both modelled by a multiagent society. In the traditional manufacturing simulation, the agents follow the defined times of each process, including the maintenance times. In the advanced manufacturing simulation, the decision about when to stop a piece of equipment for maintenance is defined by the agent according to data received from sensors and the definitions of the process. The results indicate a significant improvement in equipment usage and consequently higher production in the same time interval. The process simulation clearly indicates that the application of advanced manufacturing concepts in industry is relevant in order to increase the efficiency of production processes. Among the main concepts introduced in advanced manufacturing models are the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Artificial Intelligence (AI). The models generated are computationally simulated using an agent-based simulation method from the software AnyLogic. The results obtained should contribute to encouraging small and medium sized enterprises to adopt the concepts of Industry 4.0 in their businesses. |
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Gestão & Produção |
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Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approachSmart manufacturingIndustry 4.0Cyber Physical SystemsMulti-Agent SystemsSimulationAbstract: Advanced Manufacturing or Industry 4.0 concepts bring new advances and challenges to current industrial processes. Such concepts are not always well understood and their results in terms of production performance may not be clear. This work proposes a comparison between a traditional manufacturing process and an advanced manufacturing process, both modelled by a multiagent society. In the traditional manufacturing simulation, the agents follow the defined times of each process, including the maintenance times. In the advanced manufacturing simulation, the decision about when to stop a piece of equipment for maintenance is defined by the agent according to data received from sensors and the definitions of the process. The results indicate a significant improvement in equipment usage and consequently higher production in the same time interval. The process simulation clearly indicates that the application of advanced manufacturing concepts in industry is relevant in order to increase the efficiency of production processes. Among the main concepts introduced in advanced manufacturing models are the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Artificial Intelligence (AI). The models generated are computationally simulated using an agent-based simulation method from the software AnyLogic. The results obtained should contribute to encouraging small and medium sized enterprises to adopt the concepts of Industry 4.0 in their businesses.Universidade Federal de São Carlos2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2020000300301Gestão & Produção v.27 n.3 2020reponame:Gestão & Produçãoinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCAR10.1590/0104-530x5619-20info:eu-repo/semantics/openAccessCavata,Julio TakashiMassote,Alexandre AugustoMaia,Rodrigo FilevLima,Fábioeng2020-06-25T00:00:00Zoai:scielo:S0104-530X2020000300301Revistahttps://www.gestaoeproducao.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpgp@dep.ufscar.br||revistagestaoemanalise@unichristus.edu.br1806-96490104-530Xopendoar:2020-06-25T00:00Gestão & Produção - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.none.fl_str_mv |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
title |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
spellingShingle |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach Cavata,Julio Takashi Smart manufacturing Industry 4.0 Cyber Physical Systems Multi-Agent Systems Simulation |
title_short |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
title_full |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
title_fullStr |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
title_full_unstemmed |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
title_sort |
Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach |
author |
Cavata,Julio Takashi |
author_facet |
Cavata,Julio Takashi Massote,Alexandre Augusto Maia,Rodrigo Filev Lima,Fábio |
author_role |
author |
author2 |
Massote,Alexandre Augusto Maia,Rodrigo Filev Lima,Fábio |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Cavata,Julio Takashi Massote,Alexandre Augusto Maia,Rodrigo Filev Lima,Fábio |
dc.subject.por.fl_str_mv |
Smart manufacturing Industry 4.0 Cyber Physical Systems Multi-Agent Systems Simulation |
topic |
Smart manufacturing Industry 4.0 Cyber Physical Systems Multi-Agent Systems Simulation |
description |
Abstract: Advanced Manufacturing or Industry 4.0 concepts bring new advances and challenges to current industrial processes. Such concepts are not always well understood and their results in terms of production performance may not be clear. This work proposes a comparison between a traditional manufacturing process and an advanced manufacturing process, both modelled by a multiagent society. In the traditional manufacturing simulation, the agents follow the defined times of each process, including the maintenance times. In the advanced manufacturing simulation, the decision about when to stop a piece of equipment for maintenance is defined by the agent according to data received from sensors and the definitions of the process. The results indicate a significant improvement in equipment usage and consequently higher production in the same time interval. The process simulation clearly indicates that the application of advanced manufacturing concepts in industry is relevant in order to increase the efficiency of production processes. Among the main concepts introduced in advanced manufacturing models are the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Artificial Intelligence (AI). The models generated are computationally simulated using an agent-based simulation method from the software AnyLogic. The results obtained should contribute to encouraging small and medium sized enterprises to adopt the concepts of Industry 4.0 in their businesses. |
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=S0104-530X2020000300301 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2020000300301 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0104-530x5619-20 |
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.27 n.3 2020 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 |
_version_ |
1750118207266488320 |