Title :
Defects pattern recognition for flip-chip solder joint quality inspection with laser ultrasound and Interferometer
Author :
Liu, Sheng ; Ume, Charles I. ; Achari, Achyuta
Author_Institution :
Sch. of Mech. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
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.
Keywords :
feature extraction; flip-chip devices; inspection; interferometers; neural nets; pattern classification; probability; soldering; ultrasonic measurement; cluster analysis; dominant frequency; error ratio; feature vectors; flip-chip solder joint; interferometer; laser ultrasound; neural network classification; pattern recognition; probabilistic neural network; quality inspection; ultrasound waveforms; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Flip chip solder joints; Frequency; Inspection; Neural networks; Pattern recognition; Performance analysis; Ultrasonic imaging;
Journal_Title :
Electronics Packaging Manufacturing, IEEE Transactions on
DOI :
10.1109/TEPM.2004.830515
