Optimization of Multilayer Metal Bellow Hydroforming Process with Response Surface Method and Genetic Algorithm

In this paper, an optimization strategy for the hydroforming process of bellows is proposed, based on finite element analysis, design of experiments, response surface methodology, and genetic algorithms. A numerical model of the bellows hydroforming process is developed using the finite element simulation code ABAQUS and validated experimentally. A combination of experimental design, numerical simulations, and regression analysis is employed to establish the mathematical models relating the objectives to the design variables. An analysis of variance (ANOVA) is conducted to evaluate the significance of each individual factor on the response variable. The main and interaction effects of the process parameters on the outer diameter and convolution pitch are illustrated and discussed. Furthermore, the response surface methodology and a Pareto-based multi-objective genetic algorithm (MOGA) are applied to determine optimal solutions within the given optimization criteria. The optimized results show good agreement with the experimental data, demonstrating that the optimization methodology is reliable.