Process optimisation of transfer moulding for electronic packages using artificial neural networks and multlobjective optimisation techniques

K. W. Tong, Chun Kit Kwong, Kai Ming Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)

Abstract

Transfer moulding is the most common process for the encapsulation of electronic packages in semiconductor manufacturing. Quality of the moulding is affected by a large number of mould design parameters and process parameters. Currently, the parameters setting is performed by experienced engineers in a trial and error manner and often the optimal setting can not be obtained. In the face of global competition, the current practice is inadequate. In this research, a process optimisation system for transfer moulding of electronic packages is described which involves design of experiments (DOE) techniques, artificial neural networks (ANNs), multiple regression analysis and the minimax method. The system is aimed to determine the optimal mould design parameters and process parameter settings of transfer moulding of electronic packages for multiobjective problem. Implementation of the optimisation system has demonstrated that the time for the determination of optimal mould design parameters and process parameters setting can be greatly reduced and the parameters setting recommended by the system can contribute to the good quality of moulded packages without relying on experienced engineers.
Original languageEnglish
Pages (from-to)675-685
Number of pages11
JournalInternational Journal of Advanced Manufacturing Technology
Volume24
Issue number9-10
DOIs
Publication statusPublished - 1 Nov 2004

Keywords

  • Artificial neural networks
  • Electronic packages
  • Multiobjective optimisation
  • Transfer moulding

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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