• DocumentCode
    2275668
  • Title

    Identifying systematic critical features using silicon diagnosis data

  • Author

    Schuermyer, Chris ; Malik, Shobhit ; Herrmann, Thomas

  • Author_Institution
    Silicon Test Solutions, Mentor Graphics Corp., Wilsonville, OR, USA
  • fYear
    2012
  • fDate
    15-17 May 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A production worthy methodology has been outlined that uses layout aware scan diagnosis data to validate whether certain topologies are design-process induced defects. The methodology uses pattern matching technology to generate a set of critical feature hypotheses and uses diagnosis-driven yield analysis to validate or refute the hypotheses. The methodology is demonstrated in a 28nm GLOBALFOUNDRIES yield ramp to uniquely identify systematic critical features in silicon and provide a best description of the surrounding topology which induces the defect, along with quantifying the yield impact.
  • Keywords
    elemental semiconductors; fault diagnosis; pattern matching; semiconductor device manufacture; silicon; GLOBALFOUNDRIES yield ramp; critical feature hypotheses; design-process induced defect; diagnosis-driven yield analysis; layout aware scan diagnosis; pattern matching technology; production worthy methodology; silicon diagnosis data; size 28 nm; systematic critical feature; Failure analysis; Feature extraction; Layout; Object recognition; Silicon; Systematics; Topology; critical feature; defects; design for manufacturing; diagnosis; failure analysis; systematic yield limiter; yield learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Semiconductor Manufacturing Conference (ASMC), 2012 23rd Annual SEMI
  • Conference_Location
    Saratoga Springs, NY
  • ISSN
    1078-8743
  • Print_ISBN
    978-1-4673-0350-7
  • Type

    conf

  • DOI
    10.1109/ASMC.2012.6212858
  • Filename
    6212858