Title :
Determination of process conditions of epoxy dispensing processes using a genetic algorithm based neural fuzzy networks
Author :
Chan, K.Y. ; Dillon, T.S. ; Ling, S.H. ; Kwong, C.K.
Author_Institution :
Digital Ecosyst. & Bus. Intell. Inst., Curtin Univ. of Technol., Perth, WA, Australia
Abstract :
In this paper, process conditions of epoxy dispensing processes are determined by the proposed genetic algorithm based neural fuzzy networks, which consists of two tasks: a) the approach of neural fuzzy networks, which was shown to be better than the other existing approaches, is proposed to develop models in relating between process parameters and quality characteristics for the epoxy dispensing processes; b) the approach of genetic algorithm is used to determine process parameters with respect to pre-defined quality requirements based on the developed neural fuzzy network models. The results indicate that, based on the proposed genetic algorithm based neural fuzzy network, estimated process parameters can achieve specified requirements of microchip encapsulations with high and robust qualities.
Keywords :
chip-on-board packaging; encapsulation; fuzzy neural nets; genetic algorithms; parameter estimation; epoxy dispensing process; genetic algorithm; microchip encapsulations; neural fuzzy network models; process conditions; process parameter estimation; Biological system modeling; Encapsulation; Genetic algorithms; Mathematical model; Modeling; Neural networks; Optimization; Epoxy dispensing process; microchip encapsulation; neural fuzzy networks;
Conference_Titel :
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7315-1
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2011.6007321