Abstract
Outlier devices behave differently from the majority of the devices and are considered to be potentially defective. Identifying outliers has many applications in test, including defect filters for alternate test, and setting pass/fail limits for automotive domain. In previous work, outliers have been identified using single dimensional and/or static methods which does not exploit information efficiently. In this work, we propose an adaptive multidimensional outlier analysis method that combines the information of multiple measurement parameters and judiciously selects only information rich parameters to maximize detection probability. Furthermore, the proposed method continously updates to track process shift to enable adaptation to the evolving processes. The proposed method can be integrated within an existing test framework to improve test quality with little or no additional test time cost. In this context, we integrate our technique with an adaptive test framework and show that the method enables improved test quality.
Original language | English (US) |
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Title of host publication | Proceedings - International Test Conference |
DOIs | |
State | Published - 2011 |
Event | International Test Conference 2011, ITC 2011 - Anaheim, CA, United States Duration: Sep 18 2011 → Sep 23 2011 |
Other
Other | International Test Conference 2011, ITC 2011 |
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Country/Territory | United States |
City | Anaheim, CA |
Period | 9/18/11 → 9/23/11 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Applied Mathematics