Title: An optimisation of 3D printing parameters of nanocomposites based on improved particle swarm optimisation algorithm

Authors: Jianing Zhang; Yanhong Yang

Addresses: School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan, 114051, China ' School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan, 114051, China

Abstract: In order to overcome the problems of low accuracy, long optimisation time and high printing error of traditional 3D printing parameter optimisation methods, a optimisation method of 3D printing parameters of nanocomposites based on improved particle swarm optimisation (PSO) algorithm was proposed. The 3D mechanism model of nanocomposites 3D printer was constructed, the kinematics of the model was solved, and the calculation results of 3D printing parameters were obtained. The fundamental PSO algorithm is improved by introducing potential drop and contraction expansion factor. The objective function of 3D printing parameter optimisation was constructed, and the improved PSO algorithm was used to solve the function to realise 3D printing parameter optimisation. The test results show that the calculation accuracy of 3D printing parameters of nanocomposites is always higher than 92%, the average optimisation time is 0.72 s, and the maximum 3D printing error is 0.2 mm.

Keywords: improved PSO algorithm; nanocomposites; 3D printing parameters; parameter optimisation; contraction expansion factor.

DOI: 10.1504/IJMMP.2023.128418

International Journal of Microstructure and Materials Properties, 2023 Vol.16 No.4, pp.266 - 277

Received: 12 Apr 2022
Accepted: 07 Oct 2022
Published online: 20 Jan 2023 *