Krishnan, S. and Kerkhoff, H.G.
A Robust Metric for Screening Outliers from Analogue Product Manufacturing Tests Responses.
In: Proceedings 16th IEEE European Test Symposium, ETS 2011, 23 May - 27 May 2011, Trondheim, Norway.
IEEE Computer Society.
Full text available as:
PDF - Univ. of Twente only
Official URL: http://dx.doi.org/10.1109/ETS.2011.31
Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with
this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the presence of outliers to test-response measurements, and only a sub-sample from the population is available, the distance metric becomes unreliable. To circumvent this problem, multiple Mahalanobis
distances are calculated from selected sets of test-response measurements. They are then suitably formulated to derive a metric that has a reduced variance and robust to shifts or deviations in measurements. In this paper, such a formulation is proposed to qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones. The application of method is exemplified over a test set of an industrial automobile
|Item Type:||Conference or Workshop Paper (Full Paper, Talk)|
|Research Group:||EWI-CAES: Computer Architecture for Embedded Systems|
|Research Program:||CTIT-DSN: Dependable Systems and Networks, CTIT-WiSe: Wireless and Sensor Systems|
|Research Project:||TOETS: Towards One European Test Solution|
|Additional Information:||Best paper award ETS 2011
|Uncontrolled Keywords:||outliers, metrics, manufacturing test|
|Deposited On:||09 January 2012|
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