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Lightweight design of two-level supports for extrusion-based additive manufacturing based on metaheuristic algorithms

Ruiliang Feng (School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China)
Jingchao Jiang (Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, Republic of Korea)
Atul Thakur (Department of Mechanical Engineering, Indian Institute of Technology Patna, Patna, India)
Xiangzhi Wei (International Digital Economy Academy, Shenzhen, China)

Rapid Prototyping Journal

ISSN: 1355-2546

Article publication date: 11 November 2022

Issue publication date: 4 April 2023

144

Abstract

Purpose

Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.

Design/methodology/approach

To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.

Findings

Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.

Research limitations/implications

The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.

Practical implications

The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.

Originality/value

The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.

Keywords

Acknowledgements

This work was supported in part by the Science and Technology Commission of Shanghai Municipality Fund No. 18510745700.

Citation

Feng, R., Jiang, J., Thakur, A. and Wei, X. (2023), "Lightweight design of two-level supports for extrusion-based additive manufacturing based on metaheuristic algorithms", Rapid Prototyping Journal, Vol. 29 No. 4, pp. 850-866. https://doi.org/10.1108/RPJ-01-2022-0038

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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