Subramanian, K. and Periasamy, V.M. and Malathy, P. and Ramasamy, K. (2009) Predictive modeling of deposition rate in electro-deposition of copper–tin using regression and artificial neural network. Journal of Electroanalytical Chemistry, 636 (1-2). pp. 30-35.

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Abstract

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. Copper–tin alloy was electrodeposited from a cyanide bath. The coating composition was determined using X-ray fluorescence spectroscopy. The deposition rate was calculated from the mass, composition and area of the deposit and its approximate density. The results were used to create a model for the plating characteristics using ANN. The ANN model was compared with the regression model for analysis.

Item Type:	Article
Uncontrolled Keywords:	Electroplating; Deposition rate; Regression; Anova; Neural network
Subjects:	Industrial Metal Finishing
Divisions:	UNSPECIFIED
Depositing User:	TTBD CECRI
Date Deposited:	08 Apr 2012 14:39
Last Modified:	08 Apr 2012 14:39
URI:	http://cecri.csircentral.net/id/eprint/499

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