Predictive modelling and optimisation of tin in electro-deposition of bronze using response surface methodology

The aim of this research is to obtain electrodeposits of copper-tin over mild steel substrate. The plating parameters were studied and a model is developed using artificial neural networks (ANN). The electrodeposition of copper-tin was carried out from an alkaline cyanide bath. Tin content of coatings in alloy deposition was determined by using X-ray fluorescence spectroscopy. The results were used to create a model for the plating characteristics and also for studies using ANN. The ANN model is compared with the conventional mathematical regression model for analysis. Response surface methodology was applied for experimental investigation of the various process parametric effects on tin content in the alloy deposit.

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