• DocumentCode
    137492
  • Title

    Classification algorithms for virtual metrology

  • Author

    Tilouche, Shaima ; Bassetto, Samuel ; Nia, Vahid Partovi

  • Author_Institution
    Dept. of Math. & Ind. Eng., Ecole Polytech. de Montreal, Montreal, QC, Canada
  • fYear
    2014
  • fDate
    23-25 Sept. 2014
  • Firstpage
    495
  • Lastpage
    499
  • Abstract
    Virtual metrology in quality control deals with drifts in product quality that occur during non-sampling periods. This approach enables a hundred percent control and improves the precision of statistical control, specially while there is no sampling activity in manufacturing process. The main challenge in virtual metrology is inaccurate predictions. As such, the choice of an appropriate algorithm for prediction is crucial. We compare several algorithms that can be used for prediction in virtual metrology. The comparison over different prediction algorithms is made on a simulated data inspired from virtual metrology application.
  • Keywords
    manufacturing processes; measurement; product quality; quality control; classification algorithms; hundred percent control; manufacturing process; nonsampling periods; prediction algorithms; product quality; quality control; sampling activity; statistical control; virtual metrology application; Biological system modeling; Manufacturing; Metrology; Neural networks; Prediction algorithms; Semiconductor device modeling; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management of Innovation and Technology (ICMIT), 2014 IEEE International Conference on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/ICMIT.2014.6942477
  • Filename
    6942477