Abstract
Accurate prediction of the mechanical properties in quenched steel parts has been considered by many recent researchers. For this purpose, different methods have been introduced. One of them is the quench factor analysis (QFA) which is based on continuous cooling rate during quenching. Another method for prediction of the mechanical properties in heat-treated alloys is artificial neural networks (ANNs). In the present research, QFA and ANN approaches have been used to predict the hardness of quenched steel parts in several different quench media. Then for the two methods, the predicted values have been compared with the experimental data. Results showed that the two methods are suitable in prediction of the hardness at different points of the quenched steel parts.
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