Abstract
Cold rolling is often carried out between the solid solution treatment and aging to assist in the aging hardening of Cu-Cr-Zr lead frame alloys. This paper presents the use of an artificial neural network(ANN) to model the non-linear relationship between parameters of rolling and aging with respect to hardness properties of Cu-Cr-Zr alloy. Based on the Gauss-Newton algorithm, Levenberg-Marquardt algorithm with high stability is deduced. High precision of the model is demonstrated as well as good generalization performance. The results show that the Levenberg-Marquardt(L-M) backpropagation(BP) algorithm of ANN system is effective for predicting and analyzing the hardness properties of Cu-Cr-Zr lead frame alloy.
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