Analysis and optimization of the stamping process with pretreated 7A09 aluminum alloy

Process parameters have a great impact on product quality in stamping. In the paper, in order to improve the formability of 7A09 aluminum alloy in stamping, the influence of different heat treatment schemes on the properties of 7A09 aluminum alloy is analyzed, and a pretreatment process suitable for 7A09 aluminum alloy stamping is formulated. At the same time, to optimize pretreated 7A09 aluminum alloy stamping parameters, an improved BP neural network and multi-objective particle swarm algorithm are proposed. Relevant tensile and bulging experiments of different shapes are carried out for the pretreated 7A09 aluminum alloy material. The Hockett-Sherby constitutive equation is established. Take a double-C part as an example, the stamping process is simulated by a finite element model, and the stamping process of the double-C part is optimized by means of the improved BP neural network and multi-objective particle swarm algorithm. The results show that the proposed methods can effectively improve the quality of the formed part.