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Optimization of Preform in Close Die Forging by Combination Of Neural Network and Genetic Algorithm

In this essay, a combination of neural network and genetic algorithm has been studied for optimization of the preform in close die forging. Finite Volume Method (FVM) is used as a simulation tool for forging processes. The simulation results have used in the neural network and the genetic algorithm has been employed to optimize the forging force. The neural network was used in three stages for modeling the system. Stage 1 stands for achieving preform shape by open die forging and in stage 2 it has been used to close die forging for attaining the force and in stage 3 for the filling of the die cavity. Geometrical parametric design was used for accelerating the operation. The guideline of simulating operation and optimization has been suggested in a flow chart. An aeronautical forging component has been selected as a case study. Results show a small difference (0.3%) between neural network and direct simulation results. A final reduction of forging force 50% was obtained by optimizing the preform shape.