• DocumentCode
    3321957
  • Title

    Fault detection in reactive ion etching systems using one-class support vector machines

  • Author

    Sarmiento, Tomás ; Hong, Sang J. ; May, Gary S.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA
  • fYear
    2005
  • fDate
    11-12 April 2005
  • Firstpage
    139
  • Lastpage
    142
  • Abstract
    A robust method to detect faults in reactive ion etching systems using optical emission spectroscopy data is proposed. The approach is based on one-class support vector machines (SVMs). Unlike previously proposed fault detection methods, this approach only requires data collected during normal equipment operation to be trained. The results obtained suggest that this technique can detect equipment faults with exceptional accuracy. The SVM used detected all faults, yielding a detection accuracy of 100% with zero false alarms
  • Keywords
    fault diagnosis; integrated circuit manufacture; production engineering computing; sputter etching; support vector machines; ultraviolet spectra; visible spectra; equipment fault detection; equipment operation; one-class support vector machines; optical emission spectroscopy data; reactive ion etching systems; zero false alarms; Circuit faults; Electrical fault detection; Etching; Fault detection; Neural networks; Particle beam optics; Plasma applications; Stimulated emission; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Semiconductor Manufacturing Conference and Workshop, 2005 IEEE/SEMI
  • Conference_Location
    Munich
  • Print_ISBN
    0-7803-8997-2
  • Type

    conf

  • DOI
    10.1109/ASMC.2005.1438783
  • Filename
    1438783