On optimizing the build orientation problem using genetic algorithm

Bibliographic Details
Main Author: Matos, Marina A.
Publication Date: 2019
Other Authors: Rocha, Ana Maria A.C., Pereira, Ana I.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10198/21611
Summary: 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.
id RCAP_c3a9f4a8428c497145a42835d76e7f9f
oai_identifier_str oai:bibliotecadigital.ipb.pt:10198/21611
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling On optimizing the build orientation problem using genetic algorithmEvolutionary computationOptimizationBuild 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.Biblioteca Digital do IPBMatos, Marina A.Rocha, Ana Maria A.C.Pereira, Ana I.2020-04-08T10:58:12Z20192019-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10198/21611engMatos, Marina A.; Rocha, Ana Maria A.C.; Pereira, Ana I. (2019). On optimizing the build orientation problem using genetic algorithm. In International Conference on Numerical Analysis and Applied Mathematics (ICNAAM). Grécia10.1063/1.5114224info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T12:11:57Zoai:bibliotecadigital.ipb.pt:10198/21611Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:39:06.830886Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv On optimizing the build orientation problem using genetic algorithm
title On optimizing the build orientation problem using genetic algorithm
spellingShingle On optimizing the build orientation problem using genetic algorithm
Matos, Marina A.
Evolutionary computation
Optimization
title_short 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_sort On optimizing the build orientation problem using genetic algorithm
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 Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Matos, Marina A.
Rocha, Ana Maria A.C.
Pereira, Ana I.
dc.subject.por.fl_str_mv Evolutionary computation
Optimization
topic Evolutionary computation
Optimization
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.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01T00:00:00Z
2020-04-08T10:58:12Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/21611
url http://hdl.handle.net/10198/21611
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Matos, Marina A.; Rocha, Ana Maria A.C.; Pereira, Ana I. (2019). On optimizing the build orientation problem using genetic algorithm. In International Conference on Numerical Analysis and Applied Mathematics (ICNAAM). Grécia
10.1063/1.5114224
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.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833592111650308096