Prediction of Mechanical Properties of Hot Rolled, Low-Carbon Steel Strips Using Artificial Neural Network

Abstract

Artificial intelligence (AI) has been used in many application areas of engineering. In the present work, an artificial neural network (ANN)-based model is developed to predict the mechanical properties such as yield strength (YS), ultimate tensile strength (UTS), and elongation (EL) of the hot rolled (HR) steel strips/coils. Different network topologies have been investigated to find the appropriate network to simulate the problem. Finally, the best network was chosen as the one with 7-19-3 topology-7 neurons in the input layer, 19 in the hidden layer, and 3 in the output layer. It has been shown that a single network with three output neurons is sufficient to address the problem. The model has been tested with 121 unknown patterns, and the match between the actual values and the simulated ones is found to be very good. The model has been implemented in the hot strip mill (HSM) of Tata Steel, India. This paper describes the methodology adopted to develop the model.