Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/42939
Title: A genetic algorithm based knowledge discovery system for the design of fluid dispensing processes for electronic packaging
Authors: Kwong, CK
Chan, KY
Tsim, YC
Keywords: Genetic algorithm
Knowledge discovery system
Fluid dispensing process
Electronics packaging
Issue Date: 2009
Publisher: Pergamon Press
Source: Expert systems with applications, 2009, v. 36, no. 2, p. 3829-3838 How to cite?
Journal: Expert systems with applications 
Abstract: In the semiconductor manufacturing industry, fluid dispensing is a very common process used for die-bonding and microchip encapsulation in electronics packaging. Understanding the process behaviour is important as it aids in determining appropriate settings of the process parameters for a high-yield, low cost and robust operation. In this paper, a genetic algorithm (GA) based knowledge discovery system is proposed to discover knowledge about the fluid dispensing process. This knowledge is expressed in the form of rules derived from experimental data sets. As a result, appropriate parameters can be set which will be more effective with respect to the required quality of encapsulation. Rules generated by the GA based knowledge discovery system have been validated using a computational system for process optimization of fluid dispensing. The results indicate that the rules generated are useful and promising in aiding optimization of the fluid dispensing process in terms of better optimization results and shorter computational time.
URI: http://hdl.handle.net/10397/42939
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2008.02.041
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