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On optimizing the build orientation problem using genetic algorithm

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Resumo:Build orientation is a critical issue in Additive manufacturing (AM), where three-dimensional objects are created layer-by-layer directly from a 3D CAD model, since it is associated with the object accuracy, the number of supports required and the processing time to produce the object. Finding the best build orientation in the AM will reduce, significantly, the building costs and will improve the object accuracy. This work presents the solutions obtained by the Genetic Algorithm (GA) in solving the part build orientation optimization problem, considering the staircase effect, support area characteristics and the building time of four models. Preliminary experiments show that GA gives competitive results in solving the build orientation problem when compared with other metaheuristics.
Autores principais:Matos, Marina A.
Outros Autores:Rocha, Ana Maria A.C.; Pereira, Ana I.
Assunto:Evolutionary computation Optimization
Ano:2019
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
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author Matos, Marina A.
author2 Rocha, Ana Maria A.C.
Pereira, Ana I.
author2_role author
author
author_facet Matos, Marina A.
Rocha, Ana Maria A.C.
Pereira, Ana I.
author_role author
contributor_name_str_mv Biblioteca Digital do IPB
country_str PT
creators_json_txt [{\"Person.name\":\"Matos, Marina A.\"},{\"Person.name\":\"Rocha, Ana Maria A.C.\"},{\"Person.name\":\"Pereira, Ana I.\",\"Person.identifier.orcid\":\"0000-0003-3803-2043\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Biblioteca Digital do IPB
datacite.creators.creator.creatorName.fl_str_mv Matos, Marina A.
Rocha, Ana Maria A.C.
Pereira, Ana I.
datacite.date.Accepted.fl_str_mv 2019-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2020-04-08T10:58:12Z
datacite.date.embargoed.fl_str_mv 2020-04-08T10:58:12Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Evolutionary computation
Optimization
datacite.titles.title.fl_str_mv On optimizing the build orientation problem using genetic algorithm
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.creator.none.fl_str_mv Matos, Marina A.
Rocha, Ana Maria A.C.
Pereira, Ana I.
dc.date.Accepted.fl_str_mv 2019-01-01T00:00:00Z
dc.date.available.fl_str_mv 2020-04-08T10:58:12Z
dc.date.embargoed.fl_str_mv 2020-04-08T10:58:12Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10198/21611
dc.language.none.fl_str_mv eng
dc.rights.cclincense.fl_str_mv http://creativecommons.org/licenses/by/4.0/
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Evolutionary computation
Optimization
dc.title.fl_str_mv On optimizing the build orientation problem using genetic algorithm
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_5794
description Build orientation is a critical issue in Additive manufacturing (AM), where three-dimensional objects are created layer-by-layer directly from a 3D CAD model, since it is associated with the object accuracy, the number of supports required and the processing time to produce the object. Finding the best build orientation in the AM will reduce, significantly, the building costs and will improve the object accuracy. This work presents the solutions obtained by the Genetic Algorithm (GA) in solving the part build orientation optimization problem, considering the staircase effect, support area characteristics and the building time of four models. Preliminary experiments show that GA gives competitive results in solving the build orientation problem when compared with other metaheuristics.
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eu_rights_str_mv openAccess
format conferencePaper
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institution Instituto Politécnico de Bragança
instname_str Instituto Politécnico de Bragança
language eng
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oai_identifier_str oai:bibliotecadigital.ipb.pt:10198/21611
organization_str_mv urn:organizationAcronym:ipb
person_str_mv Matos, Marina A.
Rocha, Ana Maria A.C.
Pereira, Ana I.
Pereira, Ana I.
https://www.ciencia-id.pt/0716-B7C2-93E4
0716-B7C2-93E4
http://orcid.org/0000-0003-3803-2043
0000-0003-3803-2043
publishDate 2019
reponame_str Biblioteca Digital do IPB
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service_str_mv urn:repositoryAcronym:ipb
spelling engpt_PTBuild orientation is a critical issue in Additive manufacturing (AM), where three-dimensional objects are created layer-by-layer directly from a 3D CAD model, since it is associated with the object accuracy, the number of supports required and the processing time to produce the object. Finding the best build orientation in the AM will reduce, significantly, the building costs and will improve the object accuracy. This work presents the solutions obtained by the Genetic Algorithm (GA) in solving the part build orientation optimization problem, considering the staircase effect, support area characteristics and the building time of four models. Preliminary experiments show that GA gives competitive results in solving the build orientation problem when compared with other metaheuristics.application/pdfpt_PTOn optimizing the build orientation problem using genetic algorithmMatos, Marina A.Rocha, Ana Maria A.C.PersonalPereira, Ana I.DSpacehttp://dspace.org/items/e9981d62-2a2b-4fef-b75e-c2a14b0e7846DSpacehttp://dspace.org/items/e9981d62-2a2b-4fef-b75e-c2a14b0e7846PereiraAna I.Ciência IDhttps://www.ciencia-id.pt0716-B7C2-93E4ORCIDhttp://orcid.org0000-0003-3803-2043Researcher IDhttps://www.researcherid.comF-3168-2010Scopus Author IDhttps://www.scopus.com15071961600HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptDOIIsPartOf10.1063/1.51142242020-04-08T10:58:12Z20192019-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/21611http://purl.org/coar/access_right/c_abf2open accessEvolutionary computationOptimization740110 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paper2019http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/249c9dec-4d59-48b4-b889-a35c68e91b16/downloadInternational Conference on Numerical Analysis and Applied Mathematics (ICNAAM)2133220006Grécia
spellingShingle On optimizing the build orientation problem using genetic algorithm
Matos, Marina A.
Evolutionary computation
Optimization
status SINGLETON
subject.fl_str_mv Evolutionary computation
Optimization
title On optimizing the build orientation problem using genetic algorithm
title_full On optimizing the build orientation problem using genetic algorithm
title_fullStr On optimizing the build orientation problem using genetic algorithm
title_full_unstemmed On optimizing the build orientation problem using genetic algorithm
title_short On optimizing the build orientation problem using genetic algorithm
title_sort On optimizing the build orientation problem using genetic algorithm
topic Evolutionary computation
Optimization
topic_facet Evolutionary computation
Optimization
url http://hdl.handle.net/10198/21611
visible 1