Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Optimal process parameters design for a wire bonding of ultra‐thin CSP package based on hybrid methods of artificial intelligence

Optimal process parameters design for a wire bonding of ultra‐thin CSP package based on hybrid... Purpose – The aim of this research is to combine the Taguchi method and hybrid methods of artificial intelligence, to use them as the optimal tool in wire bond designing parameters for an ultra‐thin chip scale package (CSP) package, and then construct a set of the optimal parameter analysis flow and steps. Design/methodology/approach – The hybrid methodology of artificial Intelligence was used in order to identify the optimum parameters design for a wire bonding of ultra‐thin CSP package. This paper employed desirability function to integrate two quality characteristics (loop height and wire pull strength) into a single quality indicator to construct a well‐trained neural network prediction system with hybrid genetic algorithm. Findings – The processes parameters of low‐loop of micro HDD driver IC were optimized with GA, thereby achieving the objective of improving process yield and robustness design of micro HDD driver IC. Practical implications – The engineers could quickly obtain the optimal production process parameter with the demand of multi‐quality characteristics, and enhance the assembly quality and yield of driver IC of micro HDD. Originality/value – This paper applies the design of experiments approach to a lower wire loop processes parameters design, and improves the process yield and robustness design of micro HDD driver IC. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Microelectronics International Emerald Publishing

Optimal process parameters design for a wire bonding of ultra‐thin CSP package based on hybrid methods of artificial intelligence

Yung‐Hsiang Hung
Microelectronics International , Volume 24 (3): 8 – Jul 31, 2007
Download PDF
8 pages

Loading next page...
 
/lp/emerald-publishing/optimal-process-parameters-design-for-a-wire-bonding-of-ultra-thin-csp-Nz0xGqp87g
Publisher
Emerald Publishing
Copyright
Copyright © 2007 Emerald Group Publishing Limited. All rights reserved.
ISSN
1356-5362
DOI
10.1108/13565360710779136
Publisher site
See Article on Publisher Site

Abstract

Purpose – The aim of this research is to combine the Taguchi method and hybrid methods of artificial intelligence, to use them as the optimal tool in wire bond designing parameters for an ultra‐thin chip scale package (CSP) package, and then construct a set of the optimal parameter analysis flow and steps. Design/methodology/approach – The hybrid methodology of artificial Intelligence was used in order to identify the optimum parameters design for a wire bonding of ultra‐thin CSP package. This paper employed desirability function to integrate two quality characteristics (loop height and wire pull strength) into a single quality indicator to construct a well‐trained neural network prediction system with hybrid genetic algorithm. Findings – The processes parameters of low‐loop of micro HDD driver IC were optimized with GA, thereby achieving the objective of improving process yield and robustness design of micro HDD driver IC. Practical implications – The engineers could quickly obtain the optimal production process parameter with the demand of multi‐quality characteristics, and enhance the assembly quality and yield of driver IC of micro HDD. Originality/value – This paper applies the design of experiments approach to a lower wire loop processes parameters design, and improves the process yield and robustness design of micro HDD driver IC.

Journal

Microelectronics International – Emerald Publishing

Published: Jul 31, 2007

Keywords: Artificial intelligence; Programming and algorithm theory; Surface mount technology

References

  • Making room for more performance with chip scale packages
    Baliga, J.
  • Optimization of wire loop height for a cavity down plastic pin gird array package
    Chaudhry, I.; Barez, F.
  • Study on wire bonding process for chip scale packaging
    Chen, H.C.
  • A new approach in free air ball formation process parameters analysis
    Chen, J.L.; Lin, Y.C.
  • Simultaneous optimization of several response variables
    Derringer, G.; Suich, R.
  • Neural Networks, Algorithms, Applications, and Programming Techniques
    Freeman, J.; Skapura, D.
  • Genetic Algorithms in Search, Optimization, and Machine Learning
    Goldberg, D.E.
  • Optimization of control parameters for genetic algorithms
    Grefenstrtte, J.J.
  • Wire bond loop profile development for find pitch‐long wire assembly
    Groover, R.; Shu, W.K.; Lee, S.S.
  • Adaptation in Natural and Artificial Systems
    Holland, J.H.
  • Gold wire weakening in the thermosonic bonding of the first bond
    Hu, S.J.; Lim, K.S.; Sou, G.Y.
  • Pattern recognition of gas sensor array using characteristics of impedance
    Joo, B.S.; Choi, N.J.; Lee, Y.S.; Lim, J.W.; Kang, B.H.; Lee, D.D.
  • An optimal neural network plasma model: a casy study
    Kim, B.; Park, S.
  • Prediction of plasma‐induced DC bias using polynomial neural network
    Kim, B.; Kim, D.W.; Park, G.T.
  • Process optimization of gold stud bump manufacturing using artificial neural networks
    Liau, L.C.K.; Chen, B.S.C.
  • Study of wire bonding looping formation in the electronic packaging process using the three‐dimensional finite element method
    Liu, D.S.; Chao, Y.C.; Wang, C.H.
  • Integrated Taguchi method and neural network analysis of physical profiling in the wirebonding process
    Lo, Y.L.; Tsao, C.C.
  • In search of optimal clusters using genetic algorithms
    Murthy, C.A.; Chowdhury, N.
  • Development of ultra‐fine wire for fine pitch bonding
    Ohno, Y.; Ohzeki, Y.; Yamashita, T.; Iguchi, Y.; Katsumata, T.; Arao, Y.
  • Quality Engineering Using Robust De‐Sign
    Phadke, M.S.
  • Simultaneous determination of relative humidity and ammonia in air employing an optical fibre sensor and artificial neural network
    Raimundo, I.M.; Narayanaswamy, R.
  • Feedforward neural networks for principal components extraction
    Sandro, N.
  • Artificial Neural Networks
    Schalkoff, R.J.
  • Wire bond development for high‐pincount surface‐mount
    Shu, B.
  • Optimizing the IC wire bonding process using a neural networks/genetic algorithms approach
    Su, C.T.; Chiang, T.L.
  • The optimization of multi‐response problems in Taguchi method
    Tong, L.I.; Su, C.T.; Wang, C.H.
  • The Taguchi method and neural network analysis in a loop of wire bonding profile for IC packaging
    Tsao, C.C.
  • Neural network applications in business: a review and analysis of the literature (1988‐95)
    Wong, B.K.; Bonovich, T.A.; Selvi, Y.