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A new multiobjective optimization adaptive layering algorithm for 3D printing based on demand-oriented

Xiaoqi Wang (State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China)
Jianfu Cao (State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China)
Ye Cao (State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China)

Rapid Prototyping Journal

ISSN: 1355-2546

Article publication date: 11 August 2022

Issue publication date: 27 January 2023

219

Abstract

Purpose

Adaptive slicing is a key step in 3D printing as it is closely related to the building time and the surface quality. This study aims to develop an adaptive layering algorithm that can coordinate the optimization of printing quality and efficiency to meet different printing needs.

Design/methodology/approach

A multiobjective optimization model is established for printing quality, printing time and layer height based on the variation of surface features, profile slope and curvature of the model. The optimal solution is found by an improved method combining Newton's method and gradient method and adapts to different printing requirements by adjusting the parameter thresholds.

Findings

Several benchmarks are applied to verify this new method. The proposed method has also been compared with the uniform layering method, it reduces the volume error by 46.4% and shortens the printing time by 28.1% and is compared with five existing adaptive layering methods to demonstrate its superior performance.

Originality/value

Compared with other methods with only one layered result, this method is a demand-oriented algorithm that can obtain different results according to different needs and it can reach a trade-off between the building time and the surface quality.

Keywords

Acknowledgements

Funding: NSFC-Shenzhen United Fund (U1913603), Key industrial chain project of Shaanxi Province (2021ZDLGY12-02), National Key Research and Development Plan (2018YFB1306901), China Scholarship Council (202006280332), National Natural Science Foundation of China (62103322), China Postdoctoral Science Foundation (2021M692567), GuangDong Basic and Applied Basic Research Foundation (2020A1515111187).

Citation

Wang, X., Cao, J. and Cao, Y. (2023), "A new multiobjective optimization adaptive layering algorithm for 3D printing based on demand-oriented", Rapid Prototyping Journal, Vol. 29 No. 2, pp. 246-258. https://doi.org/10.1108/RPJ-02-2022-0061

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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