An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing

Detalhes bibliográficos
Autor(a) principal: Babcinschi, Mihail
Data de Publicação: 2020
Outros Autores: Freire, Bernardo, Ferreira, Lúcia, Señaris, Baltasar, Vidal, Felix, Vaz, Paulo, Neto, Pedro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/106637
https://doi.org/10.1016/j.promfg.2020.10.005
Resumo: Increasingly, industry is looking to better integrate their industrial processes and related data. Interoperability is key since the organizations need to share data between them, between departments and the different stages of a given technological process. The problem is that many times there are no standard data formats for data exchange between heterogeneous engineering tools. In this paper we present an integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing (MAM). Data such as the MAM robot targets and process parameters are shared and edited along the different sub-stages of the process, from Computer-Aided Design (CAD), to path planning, to multi-physics simulation, to robot simulation and production. The AutomationML neutral data format allows the implementation of optimization loops connecting different sub-stages, for example the multi-physics simulation and the path planning. A practical use case using the Direct Energy Deposition (DED) process is presented and discussed. Results demonstrated the effectiveness of the proposed AutomationML-based solution.
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spelling An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturingInteroperabilityAutomationMLAdditive ManufacturingDataIncreasingly, industry is looking to better integrate their industrial processes and related data. Interoperability is key since the organizations need to share data between them, between departments and the different stages of a given technological process. The problem is that many times there are no standard data formats for data exchange between heterogeneous engineering tools. In this paper we present an integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing (MAM). Data such as the MAM robot targets and process parameters are shared and edited along the different sub-stages of the process, from Computer-Aided Design (CAD), to path planning, to multi-physics simulation, to robot simulation and production. The AutomationML neutral data format allows the implementation of optimization loops connecting different sub-stages, for example the multi-physics simulation and the path planning. A practical use case using the Direct Energy Deposition (DED) process is presented and discussed. Results demonstrated the effectiveness of the proposed AutomationML-based solution.Elsevier2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/106637http://hdl.handle.net/10316/106637https://doi.org/10.1016/j.promfg.2020.10.005eng23519789Babcinschi, MihailFreire, BernardoFerreira, LúciaSeñaris, BaltasarVidal, FelixVaz, PauloNeto, Pedroinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-04-13T11:08:59Zoai:estudogeral.uc.pt:10316/106637Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:23:03.528322Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
title An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
spellingShingle An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
Babcinschi, Mihail
Interoperability
AutomationML
Additive Manufacturing
Data
title_short An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
title_full An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
title_fullStr An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
title_full_unstemmed An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
title_sort An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing
author Babcinschi, Mihail
author_facet Babcinschi, Mihail
Freire, Bernardo
Ferreira, Lúcia
Señaris, Baltasar
Vidal, Felix
Vaz, Paulo
Neto, Pedro
author_role author
author2 Freire, Bernardo
Ferreira, Lúcia
Señaris, Baltasar
Vidal, Felix
Vaz, Paulo
Neto, Pedro
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Babcinschi, Mihail
Freire, Bernardo
Ferreira, Lúcia
Señaris, Baltasar
Vidal, Felix
Vaz, Paulo
Neto, Pedro
dc.subject.por.fl_str_mv Interoperability
AutomationML
Additive Manufacturing
Data
topic Interoperability
AutomationML
Additive Manufacturing
Data
description Increasingly, industry is looking to better integrate their industrial processes and related data. Interoperability is key since the organizations need to share data between them, between departments and the different stages of a given technological process. The problem is that many times there are no standard data formats for data exchange between heterogeneous engineering tools. In this paper we present an integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing (MAM). Data such as the MAM robot targets and process parameters are shared and edited along the different sub-stages of the process, from Computer-Aided Design (CAD), to path planning, to multi-physics simulation, to robot simulation and production. The AutomationML neutral data format allows the implementation of optimization loops connecting different sub-stages, for example the multi-physics simulation and the path planning. A practical use case using the Direct Energy Deposition (DED) process is presented and discussed. Results demonstrated the effectiveness of the proposed AutomationML-based solution.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/106637
http://hdl.handle.net/10316/106637
https://doi.org/10.1016/j.promfg.2020.10.005
url http://hdl.handle.net/10316/106637
https://doi.org/10.1016/j.promfg.2020.10.005
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 23519789
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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