Multi-objective optimization of the loading path for tube hydroforming process based on NSGA- II

The loading paths are very important for hydroforming results in tube hydroforming, and need to be designed carefully. But the optimal loading paths are difficultly obtained by using empirical, analytical and experimental methods. FE simulation is perceived by the industry to be a cost-effective process analysis tool compared to the conventional hard tooling prototyping. Unfortunately, the prevalent trial-and-error based simulation method becomes very costly when the process analyzed is complex. More powerful design methods are needed to help the engineers design better THF loading paths, thus reducing lead times and costs. A new optimum design method for loading paths in THF, which integrates dynamic explicit FEM procedure into multiple-objective genetic algorithms based on elitist nodominated sorting genetic algorithm (NSGA-II), is brought forward in this paper. Using the method, a case study is carried out for the hydroforming of an instrument panel beam. The results show that the loading paths obtained by the method are better than the loading paths obtained by the trial and error. In addition, some results are obtained by running simulation program at a time, and which offers a wider choice for process parameters and designer's decision-making.