ISSN:
1662-9752
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
The aging process of lead frame Cu-Cr-Sn-Zn alloy has only been studied empirically by trial-and-error method so far. This paper builds up the prediction model of the aging properties via a supervised artificial neural network(ANN) to model the non-linear relationship between parameters of aging process with respect to hardness and electrical conductivity properties of the alloy. The improved model is developed by the Levenberg- Marquardt training algorithm. The predictedvalues of the ANN coincide with the tested data. So the ANN system is effective and successful for predicting and analyzing the properties of Cu-Cr-Sn-Zn alloy. The optimized processing parameters are available at 475 C ° -520 C ° aging for 2h-1h
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/02/09/transtech_doi~10.4028%252Fwww.scientific.net%252FMSF.475-479.3331.pdf