Artificial neural networks implementation in Ni-Cu-P ternary coating: Investigation of the effects of bath stabilizers

Artificial neural networks (ANN) were implemented to model a complex chemical reaction system: process of electroless plating of Ni-Cu-P alloys. This model was developed to simulate and predict plating rate as a function of amount of stabilizers added in the bath. The neural network was established with three layers and trained by the back propagation learning algorithm. The training and testing data were obtained by experiments. The simulation results of the neural network coincided well with the experimental value. Hence artificial neural network is a reliable method to optimize the process parameters of Ni-Cu-P coating.