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
收藏
页码：30 / 35
页数：6
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