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

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 th...

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Bibliographic Details
Published in:IEEE transactions on electronics packaging manufacturing 2004-01, Vol.27 (1), p.59-66
Main Authors: Sheng Liu, Ume, I.C., Achari, A.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Applied sciences
Classification algorithms
Clustering algorithms
Electric, optical and optoelectronic circuits
Electronic equipment and fabrication. Passive components, printed wiring boards, connectics
Electronics
Exact sciences and technology
Flip chip solder joints
Frequency
Image processing
Information, signal and communications theory
Inspection
Neural networks
Pattern recognition
Performance analysis
Signal processing
Telecommunications and information theory
Testing, measurement, noise and reliability
Ultrasonic imaging
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Description
Summary: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 good and bad chips, as well as classifying the type of defect.
ISSN:1521-334X
1558-0822
DOI:10.1109/TEPM.2004.830515