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

datacite.subject.fosEngenharia e Tecnologia
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorBabcinschi, Mihail
dc.contributor.authorFreire, Bernardo
dc.contributor.authorFerreira, Lucía
dc.contributor.authorSeñaris, Baltasar
dc.contributor.authorVidal, Felix
dc.contributor.authorVaz, Paulo
dc.contributor.authorNeto, Pedro
dc.date.accessioned2026-03-04T16:21:07Z
dc.date.available2026-03-04T16:21:07Z
dc.date.issued2020
dc.descriptionApresentado na "30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021), 15-18 June 2021, Athens, Greece".
dc.description.abstractIncreasingly, 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 multiphysics 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.por
dc.identifier.citationBabcinschi, M., Freire, B., Ferreira, L., Señaris, B., Vidal, F., Vaz, P., & Neto, P. (2020). An integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturing. Procedia Manufacturing, 30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021), 51, 26–31. https://doi.org/10.1016/j.promfg.2020.10.005
dc.identifier.doihttps://doi.org/10.1016/j.promfg.2020.10.005
dc.identifier.issn2351-9789
dc.identifier.urihttp://hdl.handle.net/10400.19/9729
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationPOCI01-0145-FEDER-016418
dc.relationPTDC/EME-EME/32595/2017
dc.relationUIDB/00285/2020
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/pii/S2351978920318606?via%3Dihub
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectInteroperability
dc.subjectAutomationML
dc.subjectAdditive Manufacturing
dc.subjectData
dc.titleAn integrated and interoperable AutomationML-based platform for the robotic process of metal additive manufacturingpor
dc.typetext
dspace.entity.typePublication
oaire.citation.endPage31
oaire.citation.startPage26
oaire.citation.titleProcedia Manufacturing
oaire.citation.volume51
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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