The Prediction of Sn-Ag Solder Properties Based on BP Algorithm of Artificial Neutral Network

Author

Sun, Li ; Qi, Fangjuan ; Zhezhe Hon ; Xiao, Yuehua

Author_Institution

Shijiazhuang Railway Inst., Shijiazhuang

fYear

2007

fDate

14-17 Aug. 2007

Firstpage

1

Lastpage

4

Abstract

In this paper, the prediction of properties of the lead-free solders were focused on by using the BP neural network. Then different algorithm and parameter of BP neural network has been used in the training process, and the results have been analyzed for obtaining the optimum algorithm and parameter. The influence of adding In. Bi. Sb. RE Cu to Sn- Ag alloy to tensile strength, shear strength and the solidification temperature of Sn-Ag alloy was discussed in this paper. So the input variables are the contents of In. Bi, Sb. RE. Sn. Ag. Cu. and the output variable the tensile strength, shear strength and the solidification temperature of Sn-Ag alloy respectively. 15 groups of data were chosen for training of the model and 3 groups of data for prediction. The results show that the predicted data are good agreement with ones for the given experimental conditions. The accuracy and applicability for the present neural network modeling are thus verified.

Keywords

backpropagation; electronic engineering computing; shear strength; silver alloys; solders; solidification; tensile strength; tin alloys; BP neural network; SnAg; artificial neutral network; lead-free solders properties; shear strength; solidification temperature; tensile strength; Algorithm design and analysis; Artificial neural networks; Bismuth; Copper alloys; Environmentally friendly manufacturing techniques; Input variables; Lead; Solid modeling; Temperature; Tin alloys;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Packaging Technology, 2007. ICEPT 2007. 8th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-1392-8

Electronic_ISBN

978-1-4244-1392-8

Type

conf

DOI

10.1109/ICEPT.2007.4441529

Filename

4441529