• DocumentCode
    1101879
  • Title

    IC manufacturing diagnosis based on statistical analysis techniques

  • Author

    Kibarian, John K. ; Strojwas, Andrzej J.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    15
  • Issue
    3
  • fYear
    1992
  • fDate
    6/1/1992 12:00:00 AM
  • Firstpage
    317
  • Lastpage
    321
  • Abstract
    During the production of integrated circuits, variations in the production environment can cause significant drops in yield. Since large amounts of data may have to be processed to diagnose the process conditions, the application of computer tools could greatly aid the engineer responsible for this task. In this paper the authors present a methodology for diagnosis, describe the algorithms, and illustrate applications with results from industrial data. More specifically, this paper presents the algorithms for the analysis of intrawafer variability. Measurements are made on many individual devices or circuits across an entire wafer. This information is used as the input to the diagnosis system. The system uses process, device, and circuit simulators to model the fabrication process. The results of the data analysis are lists of faults that may have caused the variability of measured performances. These faults are represented in terms of the inputs to the process simulator
  • Keywords
    circuit analysis computing; integrated circuit manufacture; process control; statistical analysis; IC manufacturing diagnosis; circuit simulators; device simulators; intrawafer variability; parametric process diagnosis system; process conditions diagnosis; process simulators; statistical analysis techniques; Algorithm design and analysis; Application software; Circuit faults; Circuit simulation; Computer applications; Data engineering; Integrated circuit yield; Manufacturing; Production; Statistical analysis;
  • fLanguage
    English
  • Journal_Title
    Components, Hybrids, and Manufacturing Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0148-6411
  • Type

    jour

  • DOI
    10.1109/33.148497
  • Filename
    148497