At this stage, the varieties and specifications of aluminum profiles continue to increase, and the scope of application continues to expand. The extrusion forming process is the key technology to realize the production of aluminum profiles, and its technological level determines the quality of the profile products and the service life of the mold. However, in actual production, the quality of the die is difficult to guarantee, and it takes multiple die trials and die repairs to produce qualified products. The numerical simulation technology is used to simulate the actual extrusion process, which can track and describe the flow behavior of the metal in real time, reveal the real flow law of the metal, predict the possible defects of the profile during the extrusion process, and adjust the mold structure and process parameters in time. It can not only improve the quality of extruded profiles, but also reduce production costs and shorten the mold production cycle. Based on this, this paper established an extrusion die optimization design model integrating finite element simulation technology and artificial intelligence algorithm. The prediction models were established with the mean square deviation of the section velocity, the maximum extrusion force and the maximum temperature of the section, respectively, and the optimal design of the structure was realized by using the particle swarm algorithm. The experimental results show that the model in this paper can realize the function well, which verifies the validity of the model.
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