Prediction of cathode efficiency in electro-deposition of copper–tin using regression and artificial neural network model

The aim of this paper is to develop a model using artificial neural network for the electro-deposition of copper–tin alloy (bronze) based on the experimentally obtained data. The electro-deposition of copper–tin was carried out using an alkaline cyanide bath. Copper and tin contents of coatings were determined using X-ray fluorescence spectroscopy. Cathode efficiencies were determined from the actual and theoretical masses of the deposits. The results were used to create a model for the plating characteristics and also for studies using ANN. The ANN model was compared with the regression model for analysis.