Optimization Methodology for Additive Manufacturing Parameter by Fused Deposition Modeling (FDM) Based on RSM-RVEA

doi:10.3901/JME.2024.19.277

Abstract

Abstract: Compared to the efficiency of traditional manufacturing, the production efficiency of current 3D printing is still relatively low.Therefore, it is crucial that process parameters are optimized to enhance the performance of printed parts, shorten printing time, and reduce material costs, in order to lower printing costs.Addressing this issue, an optimization method for process parameters in fused deposition modeling (FDM) is proposed, drawing from traditional multi-objective optimization approaches and incorporating numerical analysis.Specifically, the Response Surface Methodology is used by this method to guide and reduce the number of numerical analyses.The regression equation that is obtained employs the reference vector guided evolutionary algorithm (RVEA) to find the Pareto optimal solutions for process parameters.Additionally, an angle penalty technique is introduced, focusing on convergence in the early stages of evolution and on diversity in the later stages, effectively balancing the iterative calculations.Upon comparison with other process parameter optimization methods, this approach is found to better enhance printing efficiency and reduce manufacturing costs.

Key words: fused deposition molding, parameter optimization, finite element analysis, 3D printing

CLC Number:

TH112

ZHAO Xin, HUANG Jinjie. Optimization Methodology for Additive Manufacturing Parameter by Fused Deposition Modeling (FDM) Based on RSM-RVEA[J]. Journal of Mechanical Engineering, 2024, 60(19): 277-297.

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