Prediction of ductile cast iron quality by artificial neural networks

The prediction of ductile cast iron properties by an analysis of physical and chemical phenomena occurring during melting process is discussed. Characterisation of the problem from the standpoint of artificial neural network (ANN) modelling is presented and the network input parameters are defined, based on their significance and availability in industrial practice. A large number of different networks have been constructed and trained using about 700 melts results recorded in a typical foundry. A comprehensive analysis of the prediction errors of tensile strength, elongation and hardness made by the networks is presented. It is concluded that ANNs can be used as a valuable tool for the on-line production control in the melt shops.