Improving additive manufacturing performance by build orientation optimization
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/66431 |
Resumo: | Additive manufacturing (AM) is an emerging type of production technology to create three-dimensional objects layer-by-layer directly from a 3D CAD model. AM is being extensively used in several areas by engineers and designers. Build orientation is a critical issue in AM since it is associated with the part accuracy, the number of supports required and the processing time to produce the object. This paper presents an optimization approach to solve the part build orientation problem taking into account some characteristics or measures that can affect the accuracy of the part, namely the volumetric error, the support area, the staircase effect, the build time, the surface roughness and the surface quality. A global optimization method, the Electromagnetism-like algorithm, is used to solve the part build orientation problem. |
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Improving additive manufacturing performance by build orientation optimizationAdditive manufacturing3D printingGlobal optimizationBuild orientationScience & TechnologyAdditive manufacturing (AM) is an emerging type of production technology to create three-dimensional objects layer-by-layer directly from a 3D CAD model. AM is being extensively used in several areas by engineers and designers. Build orientation is a critical issue in AM since it is associated with the part accuracy, the number of supports required and the processing time to produce the object. This paper presents an optimization approach to solve the part build orientation problem taking into account some characteristics or measures that can affect the accuracy of the part, namely the volumetric error, the support area, the staircase effect, the build time, the surface roughness and the surface quality. A global optimization method, the Electromagnetism-like algorithm, is used to solve the part build orientation problem.The authors are grateful to the anonymous referees for their fruitfulcomments and suggestions. This work has been supported and developed under the FIBR3Dproject - Hybrid processes based on additive manufacturing of composites with long or shortfibers reinforced thermoplastic matrix (POCI-01-0145-FEDER-016414), supported by theLisbon Regional Operational Programme 2020, under the PORTUGAL 2020 PartnershipAgreement, through the European Regional Development Fund (ERDF). This work hasbeen also supported by national funds through FCT - Funda ̧c ̃ao para a Ciˆencia e Tecnologiawithin the Project Scope: UID/CEC/00319/2019SpringerUniversidade do MinhoMatos, Marina A.Rocha, Ana Maria A. C.Pereira, Ana I.20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/66431eng0268-376810.1007/s00170-020-04942-6info: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:RCAAP2023-07-21T12:17:14Zoai:repositorium.sdum.uminho.pt:1822/66431Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:09:49.618285Repositório 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 |
Improving additive manufacturing performance by build orientation optimization |
title |
Improving additive manufacturing performance by build orientation optimization |
spellingShingle |
Improving additive manufacturing performance by build orientation optimization Matos, Marina A. Additive manufacturing 3D printing Global optimization Build orientation Science & Technology |
title_short |
Improving additive manufacturing performance by build orientation optimization |
title_full |
Improving additive manufacturing performance by build orientation optimization |
title_fullStr |
Improving additive manufacturing performance by build orientation optimization |
title_full_unstemmed |
Improving additive manufacturing performance by build orientation optimization |
title_sort |
Improving additive manufacturing performance by build orientation optimization |
author |
Matos, Marina A. |
author_facet |
Matos, Marina A. Rocha, Ana Maria A. C. Pereira, Ana I. |
author_role |
author |
author2 |
Rocha, Ana Maria A. C. Pereira, Ana I. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Matos, Marina A. Rocha, Ana Maria A. C. Pereira, Ana I. |
dc.subject.por.fl_str_mv |
Additive manufacturing 3D printing Global optimization Build orientation Science & Technology |
topic |
Additive manufacturing 3D printing Global optimization Build orientation Science & Technology |
description |
Additive manufacturing (AM) is an emerging type of production technology to create three-dimensional objects layer-by-layer directly from a 3D CAD model. AM is being extensively used in several areas by engineers and designers. Build orientation is a critical issue in AM since it is associated with the part accuracy, the number of supports required and the processing time to produce the object. This paper presents an optimization approach to solve the part build orientation problem taking into account some characteristics or measures that can affect the accuracy of the part, namely the volumetric error, the support area, the staircase effect, the build time, the surface roughness and the surface quality. A global optimization method, the Electromagnetism-like algorithm, is used to solve the part build orientation problem. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/66431 |
url |
http://hdl.handle.net/1822/66431 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0268-3768 10.1007/s00170-020-04942-6 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799132524728811520 |