Optimization in deep drawing process

This paper presents an optimization method applied to deep drawing in sheet metal processes. The method couples the artificial neural network, with an evolutionary genetic algorithm searching the optimal process parameters. Finite element analyses are conducted for combination of process parameters designed, using statistical full factorial experimental design to find wall thickness as an objective function. Applications are presented to demonstrate the applicability of the proposed method considering several relevant parameters including punch and die radii, blankholder force and friction in all contact surfaces.

کلیدواژه ها:

sheet metal forming ، full factorial ، Finite element method ، Artificial neural network ، Optimization ، Genetic algorithm