Modelling the development of fluid dispensing for electronic packaging: Hybrid particle swarm optimization based-wavelet neural network approach

S. H. Ling, H. H C Iu, Hung Fat Frank Leung, K. Y. Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

An hybrid Particle Swarm Optimization PSO-based wavelet neural network for modelling the development of fluid dispensing for electronic packaging is presented in this paper. In modelling the fluid dispensing process, it is important to understand the process behaviour as well as determine optimum operating conditions of the process for a high-yield, low cost and robust operation. Modelling the fluid dispensing process is a complex non-linear problem. This kind of problem is suitable to be solved by neural network. Among different kinds of neural networks, the wavelet neural network is a good choice to solve the problem. In the proposed wavelet neural network, the translation parameters are variables depending on the network inputs. Thanks to the variable translation parameters, the network becomes an adaptive one. Thus, the proposed network provides better performance and increased learning ability than conventional wavelet neural networks. An improved hybrid PSO [1] is applied to train the parameters of the proposed wavelet neural network. A case study of modelling the fluid dispensing process on electronic packaging is employed to demonstrate the effectiveness of the proposed method.
Original languageEnglish
Title of host publication2008 International Joint Conference on Neural Networks, IJCNN 2008
Pages98-103
Number of pages6
DOIs
Publication statusPublished - 24 Nov 2008
Event2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, Hong Kong
Duration: 1 Jun 20088 Jun 2008

Conference

Conference2008 International Joint Conference on Neural Networks, IJCNN 2008
Country/TerritoryHong Kong
CityHong Kong
Period1/06/088/06/08

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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