Multi-Objective Optimization of the Loading Path in Tube Hydroforming Process Using NCGA

Abstract

According to the limitations of conventional method of optimization design for the process parameters in the hydroforming process, a new simulation method has been proposed for the optimization of the process parameters, which is the integration of the neighborhood cultivation genetic algorithm (NCGA) and the dynamic explicit algorithm based on finite element method (FEM). The new method has been adopted for the optimization of the hydroforming loading path of an instrument panel beam and the process parameters are the internal pressure vs. time and the axial feeding displacement vs. time. It is concluded that the acquired loading path through the new method is more optimal than the one through the trial and error method. In addition, the new method can simultaneously generate multiple Pareto-optimum solutions in one computation and provide more freedom for the designer's decision making of the process parameters.