Optimization of milling parameters for annular thin walled parts based on improved particle swarm optimization

Rui-li Chang; Jun Han

doi:10.1117/12.2681969

16 June 2023 Optimization of milling parameters for annular thin walled parts based on improved particle swarm optimization

Rui-li Chang, Jun Han

Author Affiliations +

Proceedings Volume 12639, Third International Conference on Mechanical Design and Simulation (MDS 2023); 126391U (2023) https://doi.org/10.1117/12.2681969
Event: Third International Conference on Mechanical Design and Simulation (MDS 2023), 2023, Xi'an, China

Abstract

Aiming at the problem that the local deformation of a ring thin-walled part is too large during machining, an improved particle swarm optimization method for milling parameters is proposed. The finite element software is used to simulate the area with large local deformation, and the simulated milling force is obtained. The objective function between machining parameters and milling force is established by orthogonal experimental response surface method. The improved particle swarm optimization algorithm is used to optimize the objective function. Finally, the optimized machining parameters are compared with the empirical machining parameters. The experimental results show that the improved particle swarm optimization algorithm can reduce the milling force in the area with large local deformation by 24.9% and effectively reduce the deformation of the annular thin-walled parts, providing a new reference scheme for technicians when selecting the milling parameters of the annular thin-walled parts.

Citation Download Citation

Rui-li Chang and Jun Han "Optimization of milling parameters for annular thin walled parts based on improved particle swarm optimization", Proc. SPIE 12639, Third International Conference on Mechanical Design and Simulation (MDS 2023), 126391U (16 June 2023); https://doi.org/10.1117/12.2681969

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