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Sequential process optimization for a digital light processing system to minimize trial and error
In additive manufacturing, logical and efficient workflow optimization enables successful production and reduces cost and time. These attempts are essential for preventing fabrication problems from various causes. However, quantitative analysis and integrated management studies of fabrication issues...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9360010/ https://www.ncbi.nlm.nih.gov/pubmed/35941282 http://dx.doi.org/10.1038/s41598-022-17841-5 |
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author | Choi, Jae Won Kim, Gyeong-Ji Hong, Sukjoon An, Jeung Hee Kim, Baek-Jin Ha, Cheol Woo |
author_facet | Choi, Jae Won Kim, Gyeong-Ji Hong, Sukjoon An, Jeung Hee Kim, Baek-Jin Ha, Cheol Woo |
author_sort | Choi, Jae Won |
collection | PubMed |
description | In additive manufacturing, logical and efficient workflow optimization enables successful production and reduces cost and time. These attempts are essential for preventing fabrication problems from various causes. However, quantitative analysis and integrated management studies of fabrication issues using a digital light processing (DLP) system are insufficient. Therefore, an efficient optimization method is required to apply several materials and extend the application of the DLP system. This study proposes a sequential process optimization (SPO) to manage the initial adhesion, recoating, and exposure energy. The photopolymerization characteristics and viscosity of the photocurable resin were quantitatively analyzed through process conditions such as build plate speed, layer thickness, and exposure time. The ability of the proposed SPO was confirmed by fabricating an evaluation model using a biocompatible resin. Furthermore, the biocompatibility of the developed resin was verified through experiments. The existing DLP process requires several trials and errors in process optimization. Therefore, the fabrication results are different depending on the operator’s know-how. The use of the proposed SPO enables a systematic approach for optimizing the process conditions of a DLP system. As a result, the DLP system is expected to be more utilized. |
format | Online Article Text |
id | pubmed-9360010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93600102022-08-10 Sequential process optimization for a digital light processing system to minimize trial and error Choi, Jae Won Kim, Gyeong-Ji Hong, Sukjoon An, Jeung Hee Kim, Baek-Jin Ha, Cheol Woo Sci Rep Article In additive manufacturing, logical and efficient workflow optimization enables successful production and reduces cost and time. These attempts are essential for preventing fabrication problems from various causes. However, quantitative analysis and integrated management studies of fabrication issues using a digital light processing (DLP) system are insufficient. Therefore, an efficient optimization method is required to apply several materials and extend the application of the DLP system. This study proposes a sequential process optimization (SPO) to manage the initial adhesion, recoating, and exposure energy. The photopolymerization characteristics and viscosity of the photocurable resin were quantitatively analyzed through process conditions such as build plate speed, layer thickness, and exposure time. The ability of the proposed SPO was confirmed by fabricating an evaluation model using a biocompatible resin. Furthermore, the biocompatibility of the developed resin was verified through experiments. The existing DLP process requires several trials and errors in process optimization. Therefore, the fabrication results are different depending on the operator’s know-how. The use of the proposed SPO enables a systematic approach for optimizing the process conditions of a DLP system. As a result, the DLP system is expected to be more utilized. Nature Publishing Group UK 2022-08-08 /pmc/articles/PMC9360010/ /pubmed/35941282 http://dx.doi.org/10.1038/s41598-022-17841-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Choi, Jae Won Kim, Gyeong-Ji Hong, Sukjoon An, Jeung Hee Kim, Baek-Jin Ha, Cheol Woo Sequential process optimization for a digital light processing system to minimize trial and error |
title | Sequential process optimization for a digital light processing system to minimize trial and error |
title_full | Sequential process optimization for a digital light processing system to minimize trial and error |
title_fullStr | Sequential process optimization for a digital light processing system to minimize trial and error |
title_full_unstemmed | Sequential process optimization for a digital light processing system to minimize trial and error |
title_short | Sequential process optimization for a digital light processing system to minimize trial and error |
title_sort | sequential process optimization for a digital light processing system to minimize trial and error |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9360010/ https://www.ncbi.nlm.nih.gov/pubmed/35941282 http://dx.doi.org/10.1038/s41598-022-17841-5 |
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