Predictive modeling of deposition rate in electro-deposition of copper-tin using regression and artificial neural network

被引：11

作者：

Subramanian, K. ^{[1
]}

Periasamy, V. M. ^{[2
]}

Pushpavanam, Malathy ^{[3
]}

Ramasamy, K. ^{[4
]}

机构：

[1] AC Coll Engn & Technol, Dept Mech Engn, Karaikkudi 630004, Tamil Nadu, India

[2] BSAR Crescent Engn Coll, Madras 600048, Tamil Nadu, India

[3] Cent Electro Chem Res Inst, Karaikkudi 630006, Tamil Nadu, India

[4] Shanmuganathan Engn Coll, Dept Mech Engn, Arasampatti 622507, TN, India

来源：

JOURNAL OF ELECTROANALYTICAL CHEMISTRY | 2009年 / 636卷 / 1-2期

关键词：

Electroplating; Deposition rate; Regression; Anova; Neural network; WEAR; TOOL;

D O I：

10.1016/j.jelechem.2009.09.003

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

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. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：30 / 35

页数：6

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