• DocumentCode
    170114
  • Title

    Diagnosis of multiple faults with highly compacted test responses

  • Author

    Cook, Alan ; Wunderlich, H.-J.

  • Author_Institution
    Inst. of Comput. Archit. & Comput. Eng., Univ. of Stuttgart, Stuttgart, Germany
  • fYear
    2014
  • fDate
    26-30 May 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Defects cluster, and the probability of a multiple fault is significantly higher than just the product of the single fault probabilities. While this observation is beneficial for high yield, it complicates fault diagnosis. Multiple faults will occur especially often during process learning, yield ramp-up and field return analysis. In this paper, a logic diagnosis algorithm is presented which is robust against multiple faults and which is able to diagnose multiple faults with high accuracy even on compressed test responses as they are produced in embedded test and built-in self-test. The developed solution takes advantage of the linear properties of a MISR compactor to identify a set of faults likely to produce the observed faulty signatures. Experimental results show an improvement in accuracy of up to 22 % over traditional logic diagnosis solutions suitable for comparable compaction ratios.
  • Keywords
    built-in self test; fault diagnosis; integrated circuit testing; integrated circuit yield; probability; MISR compactor; built-in self-test; compacted test responses; compressed test responses; defects cluster; embedded test; faulty signatures; field return analysis; linear properties; logic diagnosis; multiple fault diagnosis; multiple fault probability; process learning; yield ramp-up; Accuracy; Built-in self-test; Circuit faults; Compaction; Equations; Fault diagnosis; Mathematical model; Diagnosis; Multiple Faults; Response Compaction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Test Symposium (ETS), 2014 19th IEEE European
  • Conference_Location
    Paderborn
  • Type

    conf

  • DOI
    10.1109/ETS.2014.6847796
  • Filename
    6847796