Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach

Detalhes bibliográficos
Autor(a) principal: Cavata,Julio Takashi
Data de Publicação: 2020
Outros Autores: Massote,Alexandre Augusto, Maia,Rodrigo Filev, Lima,Fábio
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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spelling 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
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