• DocumentCode
    27391
  • Title

    Per-Device Adaptive Test for Analog/RF Circuits Using Entropy-Based Process Monitoring

  • Author

    Yilmaz, Ender ; Ozev, Sule ; Butler, Kenneth M.

  • Author_Institution
    Arizona State Univ., Tempe, AZ, USA
  • Volume
    21
  • Issue
    6
  • fYear
    2013
  • fDate
    Jun-13
  • Firstpage
    1116
  • Lastpage
    1128
  • Abstract
    We present an adaptive test flow for mixed-signal circuits that aims at optimizing the test set on a per-device basis so that more test resources can be devoted to marginal devices while passing devices that are not marginal with less testing. Cumulative statistics of the process are monitored using a differential entropy-based approach and updated only when necessary. Thus, process shift is captured and continuously incorporated into the analysis. We also include provisions to identify potentially defective devices and test them more extensively since these devices do not conform to learned collective information. We conduct experiments on an low-noise amplifier circuit in simulations, and apply our techniques to production data of two distinct industrial circuits. Both the simulation results and the results on large-scale production data show that adaptive test provides the best tradeoff between test time and test quality as measured in terms of defective parts per million.
  • Keywords
    analogue circuits; entropy; integrated circuit testing; low noise amplifiers; mixed analogue-digital integrated circuits; statistical analysis; RF circuit; adaptive test flow; analog circuit; cumulative statistics; defective device identification; differential entropy-based approach; entropy-based process monitoring; industrial circuit; low-noise amplifier circuit; marginal device; mixed-signal circuit; per-device adaptive test; Compaction; Correlation; Joints; Kernel; Object recognition; Testing; Training; Adaptive test; device level test adaptation; growing neural networks; nonlinear filtering; process monitoring; support vector machine (SVM);
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2012.2205027
  • Filename
    6248732