Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment

Bibliographic Details
Main Author: Fernandes, Célio Bruno Pinto
Publication Date: 2008
Other Authors: Viana, J. C., Pontes, A. J., Gaspar-Cunha, A.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/18983
Summary: The use of commercially available injection moulding simulation software’s allows us to predict the process response to the operating conditions defined. These codes can be used to define better injection conditions to use in specific situations, i.e., to optimize the process. Generally, this is an iterative procedure requiring the analysis of multiple outputs (pressures, temperatures, shear stresses profiles) supported by pre-established decision criteria. Most of the cases the taken options may lead to opposed results. In this sense the development of optimization methodologies are of paramount importance in order to facilitate the definition of processing windows in injection moulding. In this work the results obtained by the use of an automatic optimization methodology based on Multi-Objective Evolutionary Algorithms (EMOA), where an EMOA is linked to an injection moulding simulation code (CMOLD), will be assessed experimentally. For that purpose the processing conditions will be optimized for a desired process performance, where criteria, such as the evolution of the pressure inside the cavity, the maximum pressure level, the pressure work and the shrinkage, are taken into account. Some of the computational results obtained, selected from the set of optimized and non-optimized solutions, will be compared with the corresponding experimental results in order to validate the optimization approach used.
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spelling Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessmentInjection mouldingMulti-objective optimizationEvolutionary algorithmsThe use of commercially available injection moulding simulation software’s allows us to predict the process response to the operating conditions defined. These codes can be used to define better injection conditions to use in specific situations, i.e., to optimize the process. Generally, this is an iterative procedure requiring the analysis of multiple outputs (pressures, temperatures, shear stresses profiles) supported by pre-established decision criteria. Most of the cases the taken options may lead to opposed results. In this sense the development of optimization methodologies are of paramount importance in order to facilitate the definition of processing windows in injection moulding. In this work the results obtained by the use of an automatic optimization methodology based on Multi-Objective Evolutionary Algorithms (EMOA), where an EMOA is linked to an injection moulding simulation code (CMOLD), will be assessed experimentally. For that purpose the processing conditions will be optimized for a desired process performance, where criteria, such as the evolution of the pressure inside the cavity, the maximum pressure level, the pressure work and the shrinkage, are taken into account. Some of the computational results obtained, selected from the set of optimized and non-optimized solutions, will be compared with the corresponding experimental results in order to validate the optimization approach used.Universidade do MinhoFernandes, Célio Bruno PintoViana, J. C.Pontes, A. J.Gaspar-Cunha, A.20082008-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/18983enginfo: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:RCAAP2024-05-11T07:19:30Zoai:repositorium.sdum.uminho.pt:1822/18983Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:23:15.982499Repositórios 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 Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
title Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
spellingShingle Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
Fernandes, Célio Bruno Pinto
Injection moulding
Multi-objective optimization
Evolutionary algorithms
title_short Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
title_full Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
title_fullStr Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
title_full_unstemmed Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
title_sort Setting of the operative processing window in injection moulding using a multi-optimization approach: experimental assessment
author Fernandes, Célio Bruno Pinto
author_facet Fernandes, Célio Bruno Pinto
Viana, J. C.
Pontes, A. J.
Gaspar-Cunha, A.
author_role author
author2 Viana, J. C.
Pontes, A. J.
Gaspar-Cunha, A.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Fernandes, Célio Bruno Pinto
Viana, J. C.
Pontes, A. J.
Gaspar-Cunha, A.
dc.subject.por.fl_str_mv Injection moulding
Multi-objective optimization
Evolutionary algorithms
topic Injection moulding
Multi-objective optimization
Evolutionary algorithms
description The use of commercially available injection moulding simulation software’s allows us to predict the process response to the operating conditions defined. These codes can be used to define better injection conditions to use in specific situations, i.e., to optimize the process. Generally, this is an iterative procedure requiring the analysis of multiple outputs (pressures, temperatures, shear stresses profiles) supported by pre-established decision criteria. Most of the cases the taken options may lead to opposed results. In this sense the development of optimization methodologies are of paramount importance in order to facilitate the definition of processing windows in injection moulding. In this work the results obtained by the use of an automatic optimization methodology based on Multi-Objective Evolutionary Algorithms (EMOA), where an EMOA is linked to an injection moulding simulation code (CMOLD), will be assessed experimentally. For that purpose the processing conditions will be optimized for a desired process performance, where criteria, such as the evolution of the pressure inside the cavity, the maximum pressure level, the pressure work and the shrinkage, are taken into account. Some of the computational results obtained, selected from the set of optimized and non-optimized solutions, will be compared with the corresponding experimental results in order to validate the optimization approach used.
publishDate 2008
dc.date.none.fl_str_mv 2008
2008-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference object
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/18983
url http://hdl.handle.net/1822/18983
dc.language.iso.fl_str_mv eng
language eng
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