• DocumentCode
    694080
  • Title

    A study of semiconductor industry accidents: Making predictions based on BP artificial neural networks

  • Author

    Liu Chao ; Hsuan Peichen ; Wu Jianping

  • Author_Institution
    ESH Dept., Semicond. Manuf. Int. Corp., Shanghai, China
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    492
  • Lastpage
    496
  • Abstract
    This paper puts forward using BP artificial neural network to forecast semiconductor industry accidents, using optimized and quantifiable impact factors of accidents as input nodes and accident quantity as the output node. The established predictive model has 7 input parameters and 1 output parameter. This paper uses this model to predict and validate the accident occurrence circumstances of a semiconductor company and gets accurate results.
  • Keywords
    accidents; backpropagation; neural nets; production engineering computing; semiconductor industry; BP artificial neural networks; accident occurrence; semiconductor company; semiconductor industry accidents; semiconductor industry accidents forecasting; Accidents; Neural networks; Personnel; Predictive models; Safety; Semiconductor device modeling; Training; BP Artificial Neural Network; Impact Factors; Prediction; Semiconductor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2013 IEEE International Conference on
  • Conference_Location
    Bangkok
  • Type

    conf

  • DOI
    10.1109/IEEM.2013.6962460
  • Filename
    6962460