A Robust Metric for Screening Outliers from Analogue Product Manufacturing Tests Responses

Shaji Krishnan, Shaji Krishnan, Hans G. Kerkhoff

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    4 Citations (Scopus)


    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 product.
    Original languageUndefined
    Title of host publicationProceedings 16th IEEE European Test Symposium, ETS 2011
    Place of PublicationUSA
    PublisherIEEE Computer Society
    Number of pages6
    ISBN (Print)978-1-4577-0483-3
    Publication statusPublished - 23 May 2011
    Event16th IEEE European Test Symposium, ETS 2011 - Trondheim, Norway
    Duration: 23 May 201127 May 2011
    Conference number: 16

    Publication series

    PublisherIEEE Computer Society
    ISSN (Print)1530-1877


    Conference16th IEEE European Test Symposium, ETS 2011
    Abbreviated titleETS


    • METIS-284958
    • IR-79215
    • manufacturing test
    • EWI-21152
    • Metrics
    • CAES-TDT: Testable Design and Test
    • Outliers

    Cite this