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Graphical IDDQ Signatures Reduce Defect Level and Yield Loss

By Lan Rao, Michael L. Bushnell, Senior Member and Vishwani D. Agrawal


Abstract—We propose a new DDQ testing signature, the graphical DDQ signature. We discovered that noise, in the entire set of current measurements for a chip, is a vastly superior feature for classifying chips as good or bad, compared to present methods. The measured DDQ current as a function of vectors is defined here as the signature. We examine the shape of the waveform defined by the total set of the DDQ measurements, to extract the number of bands that all of the current measurements cluster into, the width and separation of the bands and current glitches or noise among all DDQ measurements. We examined the DDQ signatures of all SEMATECH experiment chips that were classified as good or bad by a combination of functional, delay, and scan voltage tests. A single DDQ threshold, whether absolute or differential, cannot separate good/bad chips reliably. Good chip signatures contain discrete levels (or bands) of varying widths and separations. A faulty chip almost always displays noise and glitches in the band structure. The graphical DDQ classifier shows very high accuracy for SEMATECH test data with a test escape rate of 5.97%, compared with 7.5 % for the single threshold method, 7.6 % for current differences and 7.5 % for the 1 DDQ method. The graphical DDQ method had a 1.2 % test overkill, compared with 2.3% for the single threshold method, 6.1 % for current differences and 7.0 % for 1 DDQ. Index Terms — DDQ testing, current noise, current signatures, data mining, pattern recognition

Year: 2010
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