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IDDQ Outlier Screening through Two-Phase Approach: Clustering-Based Filtering and Estimation-Based Current-Threshold Determination
Michihiro SHINTANI Takashi SATO
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2014/08/01
Online ISSN: 1745-1361
Type of Manuscript: PAPER
Category: Dependable Computing
IDDQ testing, k-means clustering, statistical leakage current analysis, Bayes' theorem, simulated annealing,
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We propose a novel IDDQ outlier screening flow through a two-phase approach: a clustering-based filtering and an estimation-based current-threshold determination. In the proposed flow, a clustering technique first filters out chips that have high IDDQ current. Then, in the current-threshold determination phase, device-parameters of the unfiltered chips are estimated based on measured IDDQ currents through Bayesian inference. The estimated device-parameters will further be used to determine a statistical leakage current distribution for each test pattern and to calculate a and suitable current-threshold. Numerical experiments using a virtual wafer show that our proposed technique is 14 times more accurate than the neighbor nearest residual (NNR) method and can achieve 80% of the test escape in the case of small leakage faults whose ratios of leakage fault sizes to the nominal IDDQ current are above 40%.