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Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components

Rapid investment casting is a casting process in which the sacrificial patterns are fabricated using additive manufacturing techniques, making the creation of advanced designs possible. One of the popular 3D printing methods applied in rapid investment casting is stereolithography because of its hig...

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Autores principales: Mukhangaliyeva, Aishabibi, Dairabayeva, Damira, Perveen, Asma, Talamona, Didier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10609965/
https://www.ncbi.nlm.nih.gov/pubmed/37896281
http://dx.doi.org/10.3390/polym15204038
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author Mukhangaliyeva, Aishabibi
Dairabayeva, Damira
Perveen, Asma
Talamona, Didier
author_facet Mukhangaliyeva, Aishabibi
Dairabayeva, Damira
Perveen, Asma
Talamona, Didier
author_sort Mukhangaliyeva, Aishabibi
collection PubMed
description Rapid investment casting is a casting process in which the sacrificial patterns are fabricated using additive manufacturing techniques, making the creation of advanced designs possible. One of the popular 3D printing methods applied in rapid investment casting is stereolithography because of its high dimensional precision and surface quality. Printing parameters of the used additive manufacturing method can influence the surface quality and accuracy of the rapid investment cast geometries. Hence, this study aims to investigate the effect of stereolithography printing parameters on the dimensional accuracy and surface roughness of printed patterns and investment cast parts. Castable wax material was used to print the sacrificial patterns for casting. A small-scale prosthetic biomedical implant for total hip replacement was selected to be the benchmark model due to its practical significance. The main results indicate that the most significant stereolithography printing parameter affecting surface roughness is build angle, followed by layer thickness. The optimum parameters that minimize the surface roughness are 0.025 mm layer thickness, 0° build angle, 1.0 support density index, and across the front base orientation. As for the dimensional accuracy, the optimum stereolithography parameters are 0.025 mm layer thickness, 30° build angle, 0.6 support density index, and diagonal to the front base orientation. The optimal printing parameters to obtain superior dimensional accuracy of the cast parts are 0.05 mm layer thickness, 45° build angle, 0.8 support density index, and diagonal to the front model base orientation. With respect to the surface roughness, lower values were obtained at 0.025 mm layer thickness, 0° build angle, 1.0 support density index, and parallel to the front base orientation.
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spelling pubmed-106099652023-10-28 Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components Mukhangaliyeva, Aishabibi Dairabayeva, Damira Perveen, Asma Talamona, Didier Polymers (Basel) Article Rapid investment casting is a casting process in which the sacrificial patterns are fabricated using additive manufacturing techniques, making the creation of advanced designs possible. One of the popular 3D printing methods applied in rapid investment casting is stereolithography because of its high dimensional precision and surface quality. Printing parameters of the used additive manufacturing method can influence the surface quality and accuracy of the rapid investment cast geometries. Hence, this study aims to investigate the effect of stereolithography printing parameters on the dimensional accuracy and surface roughness of printed patterns and investment cast parts. Castable wax material was used to print the sacrificial patterns for casting. A small-scale prosthetic biomedical implant for total hip replacement was selected to be the benchmark model due to its practical significance. The main results indicate that the most significant stereolithography printing parameter affecting surface roughness is build angle, followed by layer thickness. The optimum parameters that minimize the surface roughness are 0.025 mm layer thickness, 0° build angle, 1.0 support density index, and across the front base orientation. As for the dimensional accuracy, the optimum stereolithography parameters are 0.025 mm layer thickness, 30° build angle, 0.6 support density index, and diagonal to the front base orientation. The optimal printing parameters to obtain superior dimensional accuracy of the cast parts are 0.05 mm layer thickness, 45° build angle, 0.8 support density index, and diagonal to the front model base orientation. With respect to the surface roughness, lower values were obtained at 0.025 mm layer thickness, 0° build angle, 1.0 support density index, and parallel to the front base orientation. MDPI 2023-10-10 /pmc/articles/PMC10609965/ /pubmed/37896281 http://dx.doi.org/10.3390/polym15204038 Text en © 2023 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
Mukhangaliyeva, Aishabibi
Dairabayeva, Damira
Perveen, Asma
Talamona, Didier
Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components
title Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components
title_full Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components
title_fullStr Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components
title_full_unstemmed Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components
title_short Optimization of Dimensional Accuracy and Surface Roughness of SLA Patterns and SLA-Based IC Components
title_sort optimization of dimensional accuracy and surface roughness of sla patterns and sla-based ic components
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10609965/
https://www.ncbi.nlm.nih.gov/pubmed/37896281
http://dx.doi.org/10.3390/polym15204038
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