Using GA-ANN to Optimize Heat Treatment Technological Parameters of Super-Martensitic Stainless Steel

In this investigation a theoretical model based on artificial neural network (ANN) and genetic algorithm (GA) have been developed to optimize the heat treatment technological parameters for achieving the excellent mechanical property of super-martensitic stainless steel (SMSS). The ANN was used to correlate the heat treatment technological conditions to the mechanical property. The GA and ANN were incorporated to find the optimal technological parameters. The result shows that the most optimal heat treatment technological is 1003.9 degrees Cx0.5h (air cooling) +629.75 degrees C+2.06h (air cooling). By comparing the prediction values with the experimental data it is demonstrated that the combined GA-ANN algorithm is efficient and strong method to find the optimum heat treatment technological for producing super-martensitic stainless steel.