Parameters Optimization of Plasma Hardening Process Using Genetic Algorithm and Neural Network

Abstract

Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel. Experiments were carried out to characterize the hardening qualities. A predicting and optimizing model using genetic algorithm-back propagation neural network (GA-BP) was developed based on the experimental results. The non-linear relationship between properties of hardening layers and process parameters was established. The results show that the GA-BP predicting model is reliable since prediction results are in rather good agreement with measured results. The optimal properties of the hardened layer were deduced from GA. And through multi optimizations, the optimum comprehensive performances of the hardened layer were as follows: plasma arc current is 90 A, hardening speed is 2.2 m/min, plasma gas flow rate is 6. 0 L/min and hardening distance is 4. 3 mm. It concludes that GA-BP mode developed in this study provides a promising method for plasma hardening parameters prediction and optimization.