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Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error

The characteristics of fused deposition 3D printing lead to the inevitable step effect of surface contour in the process of forming and manufacturing, which affects molding accuracy. Traditional layering algorithms cannot take into account both printing time and molding accuracy. In this paper, an a...

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Detalles Bibliográficos
Autores principales: Lv, Ning, Ouyang, Xuefeng, Qiao, Yujing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9231067/
https://www.ncbi.nlm.nih.gov/pubmed/35744450
http://dx.doi.org/10.3390/mi13060836
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author Lv, Ning
Ouyang, Xuefeng
Qiao, Yujing
author_facet Lv, Ning
Ouyang, Xuefeng
Qiao, Yujing
author_sort Lv, Ning
collection PubMed
description The characteristics of fused deposition 3D printing lead to the inevitable step effect of surface contour in the process of forming and manufacturing, which affects molding accuracy. Traditional layering algorithms cannot take into account both printing time and molding accuracy. In this paper, an adaptive layering algorithm based on the optimal volume error is proposed. The angle between the normal vector and the layering direction is used for data optimization. The layer thickness is determined by calculating the volume error, and based on the principle of the optimal volume error, the unequal thickness adaptive layering of each printing layer of the model is realized. The experimental results show that the self-adaptive layering algorithm based on the optimal volume error has a better layering effect, greatly improves the forming efficiency and surface forming accuracy, and has a good adaptability to models with complex surfaces.
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spelling pubmed-92310672022-06-25 Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error Lv, Ning Ouyang, Xuefeng Qiao, Yujing Micromachines (Basel) Article The characteristics of fused deposition 3D printing lead to the inevitable step effect of surface contour in the process of forming and manufacturing, which affects molding accuracy. Traditional layering algorithms cannot take into account both printing time and molding accuracy. In this paper, an adaptive layering algorithm based on the optimal volume error is proposed. The angle between the normal vector and the layering direction is used for data optimization. The layer thickness is determined by calculating the volume error, and based on the principle of the optimal volume error, the unequal thickness adaptive layering of each printing layer of the model is realized. The experimental results show that the self-adaptive layering algorithm based on the optimal volume error has a better layering effect, greatly improves the forming efficiency and surface forming accuracy, and has a good adaptability to models with complex surfaces. MDPI 2022-05-26 /pmc/articles/PMC9231067/ /pubmed/35744450 http://dx.doi.org/10.3390/mi13060836 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
Lv, Ning
Ouyang, Xuefeng
Qiao, Yujing
Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error
title Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error
title_full Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error
title_fullStr Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error
title_full_unstemmed Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error
title_short Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error
title_sort adaptive layering algorithm for fdm-3d printing based on optimal volume error
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9231067/
https://www.ncbi.nlm.nih.gov/pubmed/35744450
http://dx.doi.org/10.3390/mi13060836
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