PARAMETER OPTIMIZATION OF THE FORGING AND FORMING PROCESS USING PARTICLE SWARM OPTIMIZATION

To find the best process parameters when forging blanks and improve the imperfections of the traditional numerical simulation method, particle swarm optimization (PSO) with excellent problem optimization ability will be used to optimize the parameters. From the perspective of the material itself and the energy saving of forging and forming, the most suitable parameter results can be found using this algorithm. The modeling and simulation of aluminum forging is carried out. The simulation software is used to summarize the action laws of the initial temperature of 440 °C, 460 °C, 500 °C and the forging speed of 3mm/s to 5mm/s. The simulation results are recorded and the standard deviation of the outlet surface temperature is calculated, which are used as the experimental data to establish a support vector machine (SVM) model for further fitting and calculation of the data. Then a multi-objective optimization model is established with the initial temperature and forging speed as variables and the goal of reducing the standard deviation of temperature and energy consumption. PSO is used to further solve the model to find the optimal combination of process parameters to reduce energy consumption and ensure material quality, to achieve the purpose of parameter optimization of forging and forming process. The results show that when the initial temperature is 450 °C and the forging speed is 4.4 mm/s, the material quality can be effectively improved while reducing energy consumption. Compared with the original scheme, the new scheme achieves the purpose of optimizing parameters. It has a great reference for the selection of parameter optimization of the forging and forming process and the application of PSO in the optimization process. © 2022, Cefin Publishing House. All rights reserved.