Defects pattern recognition for flip-chip solder joint quality inspection with laser ultrasound and Interferometer

@article{Liu2004DefectsPR,
  title={Defects pattern recognition for flip-chip solder joint quality inspection with laser ultrasound and Interferometer},
  author={Sheng Liu and I. Charles Ume and Achyuta Achari},
  journal={IEEE Transactions on Electronics Packaging Manufacturing},
  year={2004},
  volume={27},
  pages={59-66}
}
A defects pattern recognition system has been developed for the flip-chip solder joint quality inspection by using laser ultrasound and interferometric techniques. This system extracts error ratio and dominant frequency as features from ultrasound waveforms. It also performs a cluster analysis of those feature vectors by applying probabilistic neural network classification algorithm. The system can automatically classify chips into different clusters and can, therefore, find differences between… CONTINUE READING
11 Extracted Citations
14 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 11 extracted citations

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 14 references

A novel method and device for solder joint quality inspection by using laser ultrasound

  • S. Liu, D. Erdahl, C. Ume
  • Conf. Proc. IEEE ECTC, Las Vegas, NV, May 24–26…
  • 2000
1 Excerpt

Vibration analysis based modeling and defects recognition for flip chip solder joint quality inspection

  • Conf. Proc. ASME IMEC, Orlando, FL, 2000.
  • 2000
1 Excerpt

Classification algorithm and optimal feature selection methodology for automated solder joint defect inspection

  • Oyeleye, Olagunju, Lehtihet, E. Amine
  • J. Manufact. Syst., vol. 17, no. 4, pp. 251–258…
  • 1998
1 Excerpt

Improvements to X-ray laminography for automated inspection of solder joints

  • Sankaran, Vijay, Kalukin, R. Andrew, Kraft, P. Russell
  • IEEE Trans. Comp., Packag., Manufact. Technol. C…
  • 1998
1 Excerpt

A neural network based classifier for ultrasonic raw data of the myocardium

  • L. Kahl, R. Orglmeister, K.J.G. Schmailzl
  • Conf. Proc. 1997 IEEE Ultrasonics Symposium, 1997…
  • 1997
1 Excerpt

Pattern Recognition and Prediction With Applications to Signal Characterization

  • D. Kil, F. Shin
  • XXXX: American Institute of Physics,
  • 1996
1 Excerpt

Waveform recognition and classification using and unsupervised network

  • C. K. Lee, K. F. Yeung
  • Proc. 1993 Int. Joint Conf. Neural Networks, 1993…
  • 1993
1 Excerpt

Similar Papers

Loading similar papers…