• DocumentCode
    2400892
  • Title

    Virtual Metrology models for predicting physical measurement in semiconductor manufacturing

  • Author

    Ferreira, A. ; Roussy, A. ; Conde, L.

  • Author_Institution
    Center for Microelectron. of Provence Georges Charpak, Ecole Nat. Super. des Mines de St.-Etienne, Gardanne, France
  • fYear
    2009
  • fDate
    10-12 May 2009
  • Firstpage
    149
  • Lastpage
    154
  • Abstract
    The semiconductor manufacturing industry has a large-volume multistage manufacturing system. To insure the high stability and the production yield on-line a reliable wafer monitoring is required. The approach, called Virtual Metrology (VM) is defined as the prediction of metrology variables (either measurable or non measurable) using process and wafer state information. It consists in the definition and the application of some predictive and corrective models for metrology outputs (physical measurements) in function of the previous metrology outputs and of the equipment parameters of current and previous steps of fabrication. The goals of this paper are to present a methodology for VM module for individual process applications in semiconductor manufacturing and to present a case study based on industrial data.
  • Keywords
    integrated circuit manufacture; semiconductor device manufacture; individual process applications; industrial data; large-volume multistage manufacturing system; physical measurement prediction; semiconductor manufacturing industry; virtual metrology models; wafer monitoring; wafer state information; Current measurement; Manufacturing industries; Manufacturing systems; Metrology; Predictive models; Production; Semiconductor device manufacture; Semiconductor device modeling; Stability; Virtual manufacturing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Semiconductor Manufacturing Conference, 2009. ASMC '09. IEEE/SEMI
  • Conference_Location
    Berlin
  • ISSN
    1078-8743
  • Print_ISBN
    978-1-4244-3614-9
  • Electronic_ISBN
    1078-8743
  • Type

    conf

  • DOI
    10.1109/ASMC.2009.5155973
  • Filename
    5155973