Abstract
This paper presents the application of artificial neural network (ANN) in the foundry process. Two-layer feedforward neural network which is trained using backpropagation algorithm that updates weights and biases values according to gradient descent momentum and an adaptive learning rate (Backpropagation Neural Network – BPNN) has been established to predict the as-cast impact toughness of spheroidal graphite cast iron (SGI) using the thermal analysis (TA) parameters as inputs. Generalization property of the developed ANN is very good, which is confirmed by a very good accordance between the predicted and the targeted values of as-cast impact toughness on a new data set that was not included in the training data set.

Key words
spheroidal graphite cast iron, impact toughness, artificial neural networks, thermal analysis

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