Optimisation of shape and process parameters in metal forging using genetic algorithms

An approach to optimal design in forging is presented in this paper. The design problem is formulated as an inverse problem incorporating a finite element thermal analysis model and an optimisation technique conducted on the basis of an evolutionary strategy. A rigid viscoplastic flow-type formulation was adopted, valid for both hot and cold processes. In industrial forming processes most of the deformation energy is transformed into thermal energy. The generated heat causes the increase in temperature. External friction losses raise the temperature at the die–work-piece interface. Optimal solutions are obtained using a developed numerical algorithm based on a genetic search supported by an elitist strategy. The chosen design variables are work-piece preform shape and work-piece temperature. In order to demonstrate the efficiency of the inverse evolutionary search, specific forging cases are presented, considering the optimisation of the process parameters aiming the reduction of the difference between the realised and the prescribed final forged shape under minimal energy consumption and restricting the maximum temperature.