Determination of process conditions of epoxy dispensing processes using a genetic algorithm based neural fuzzy networks

Chan, KY; Dillon, TS; Ling, SH; Kwong, CK

Determination of process conditions of epoxy dispensing processes using a genetic algorithm based neural fuzzy networks

Chan, KY Dillon, TS Ling, SH

Kwong, CK

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Fuzzy Systems, 2011, pp. 2253 - 2260
Issue Date:: 2011-09-27

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Field	Value	Language
dc.contributor.author	Chan, KY	en_US
dc.contributor.author	Dillon, TS	en_US
dc.contributor.author	Ling, SH https://orcid.org/0000-0003-0849-5098	en_US
dc.contributor.author	Kwong, CK	en_US
dc.date.issued	2011-09-27	en_US
dc.identifier.citation	IEEE International Conference on Fuzzy Systems, 2011, pp. 2253 - 2260	en_US
dc.identifier.isbn	9781424473175	en_US
dc.identifier.issn	1098-7584	en_US
dc.identifier.uri	http://hdl.handle.net/10453/29576
dc.description.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. © 2011 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Fuzzy Systems	en_US
dc.relation.isbasedon	10.1109/FUZZY.2011.6007321	en_US
dc.title	Determination of process conditions of epoxy dispensing processes using a genetic algorithm based neural fuzzy networks	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Taipei, Taiwan	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

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. © 2011 IEEE.

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http://hdl.handle.net/10453/29576