• DocumentCode
    2144681
  • Title

    Neural networks and search for minimum defectiveness in molding operation in ceramic industry

  • Author

    Kumru, M.

  • Author_Institution
    Dept. of Ind. Eng., Dogus. Univ., İstanbul, Turkey
  • fYear
    2011
  • fDate
    15-18 June 2011
  • Firstpage
    335
  • Lastpage
    339
  • Abstract
    This study is to be conducted in a ceramics production plant where the highest product defectiveness occurs in the molding shop of the plant. There are a number of factors that affect the amount of product defectiveness. The purpose is to search for a set of factor treatment conditions which provide the minimum defectiveness performance in the shop. Artificial Neural Network (ANN) method was used to realize the purpose. Based on the statistical analysis, the ANN approach is found to be reliable in predicting the amount of defectiveness that depends on various factors.
  • Keywords
    ceramic industry; moulding; neural nets; production engineering computing; statistical analysis; artificial neural network method; ceramic industry; ceramics production plant; minimum defectiveness performance; molding operation; molding shop; product defectiveness; statistical analysis; Artificial neural networks; Biological neural networks; Ceramics; Forecasting; Predictive models; Production; Training; artificial neural networks; ceramic molding process; experiment design; metaheuristics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-61284-919-5
  • Type

    conf

  • DOI
    10.1109/INISTA.2011.5946140
  • Filename
    5946140