The Accurate Prediction & Optimization Technique Of The Springback Based On The Genetic Algorithm In 2D Sheet Metal Forming

The sheet metal forming is a very important technique and it is widely applied in many engineering fields such as automobile etc. One of the key problems in sheet metal forming is the accurate prediction of the springback. If the springback of the part can't be predicted accurately or differs largely from the actual case, trial and error process must be used in the design and manufacturing of the mould which will increase the cost.The accurate prediction of springback is a challenge problem world wide till now. In this paper, the implicit FEM software for 2D sheet forming was developed. The involved theories and methods include: the non-linear two-dimensional(2D) sheet element put forward by T J R Hughes and W K Liu, master-slave contact searching algorithm, penalty contact force algorithm, Coulomb friction principle, Hill anisotropic yielding principle, power-law hardening and non-mould springback-computing algorithm. The numerical examples indicate that the present method is very accurate in the prediction of springback.Furthermore, some factors that affected the magnitude of the springback were also analyzed and several useful conclusions had been drawn. The large binder force is most effective to restrain springback among the concerning factors that influence the magnitude of springback.After analyzing the influencing factors of springback, one VBF pattern based on the modified micro genetic algorithm to control the springback was proposed in this paper. The computation examples indicated that the springback could be controlled in a small range through the present method.