Prediction of surface hardness after ferritic nitrocarburising of steels using artificial neural networks

Abstract

A model for prediction of the surface hardness of structural steels after nitrocarburising has been designed. The model is based on a backpropagation feedforward artificial neural network. The performance of the model was checked, using data from the published literature. Good correspondence between predicted from the artificial neural network (ANN) and experimental data was observed. The effects of the chromium, manganese, and nickel contents in the steels on the hardness were studied. Using the model the surface hardnesses after nitrocarburising for some commonly used steels are also predicted. The ANN model has been designed with the aim of optimising the application of nitrocarburising technology.