Application of artificial neural network in predicting the thickness of chromizing coatings on P110 steel

Abstract

A series of rare earth (RE) dispersed chromizing coatings were produced on P110 steel by pack cementation. The orthogonal array design (OAD) was applied to set the experiments. An artificial neural network (ANN) approach is employed to predict the thickness values of the obtained chromizing coatings based on the OAD tests results. The results revealed that the built model was reliable, the thickness values of chromizing coatings were well predicted at selected process parameters, and the predicted error lied in rational range.