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Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone
Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104100/ https://www.ncbi.nlm.nih.gov/pubmed/35591657 http://dx.doi.org/10.3390/ma15093323 |
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author | Solheid, Juliana S. Elkaseer, Ahmed Wunsch, Torsten Scholz, Steffen Seifert, Hans J. Pfleging, Wilhelm |
author_facet | Solheid, Juliana S. Elkaseer, Ahmed Wunsch, Torsten Scholz, Steffen Seifert, Hans J. Pfleging, Wilhelm |
author_sort | Solheid, Juliana S. |
collection | PubMed |
description | Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving to be a great asset in improving the surface quality of parts in a relatively short time. For process development, experimental analysis can be extensive and expensive regarding the time requirement and laboratory facilities, while computational simulations demand the development of numerical models that, once validated, provide valuable tools for parameter optimization. In this work, experiments and simulations are performed based on the design of experiments to assess the effects of the parametric inputs on the resulting surface roughness and heat-affected zone depths. The data obtained are used to create both linear regression and artificial neural network models for each variable. The models with the best performance are then used in a multiobjective genetic algorithm optimization to establish combinations of parameters. The proposed approach successfully identifies an acceptable range of values for the given input parameters (laser power, focal offset, axial feed rate, number of repetitions, and scanning speed) to produce satisfactory values of Ra and HAZ simultaneously. |
format | Online Article Text |
id | pubmed-9104100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91041002022-05-14 Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone Solheid, Juliana S. Elkaseer, Ahmed Wunsch, Torsten Scholz, Steffen Seifert, Hans J. Pfleging, Wilhelm Materials (Basel) Article Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving to be a great asset in improving the surface quality of parts in a relatively short time. For process development, experimental analysis can be extensive and expensive regarding the time requirement and laboratory facilities, while computational simulations demand the development of numerical models that, once validated, provide valuable tools for parameter optimization. In this work, experiments and simulations are performed based on the design of experiments to assess the effects of the parametric inputs on the resulting surface roughness and heat-affected zone depths. The data obtained are used to create both linear regression and artificial neural network models for each variable. The models with the best performance are then used in a multiobjective genetic algorithm optimization to establish combinations of parameters. The proposed approach successfully identifies an acceptable range of values for the given input parameters (laser power, focal offset, axial feed rate, number of repetitions, and scanning speed) to produce satisfactory values of Ra and HAZ simultaneously. MDPI 2022-05-05 /pmc/articles/PMC9104100/ /pubmed/35591657 http://dx.doi.org/10.3390/ma15093323 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Solheid, Juliana S. Elkaseer, Ahmed Wunsch, Torsten Scholz, Steffen Seifert, Hans J. Pfleging, Wilhelm Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone |
title | Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone |
title_full | Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone |
title_fullStr | Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone |
title_full_unstemmed | Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone |
title_short | Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone |
title_sort | multiobjective optimization of laser polishing of additively manufactured ti-6al-4v parts for minimum surface roughness and heat-affected zone |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104100/ https://www.ncbi.nlm.nih.gov/pubmed/35591657 http://dx.doi.org/10.3390/ma15093323 |
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