• DocumentCode
    623234
  • Title

    Performance comparison of artificial neural network and expert system in prediction of flow stress

  • Author

    Iqbal, Azlan

  • Author_Institution
    Sch. of Mech. Eng., Dalian Univ. of Technol., Dalian, China
  • fYear
    2013
  • fDate
    19-21 June 2013
  • Firstpage
    555
  • Lastpage
    561
  • Abstract
    Modeling of various manufacturing processes, including force and power requirements, depends on accurate estimation of a material´s flow stress. The paper presents a mutual comparison between rule-based expert system and artificial neural network in predicting flow stress of a commonly used type of steel. The prediction processes take microstructure, applied temperature, strain, and strain rate as process parameters. The prediction results of both the systems show a good deal of match with the actual values.
  • Keywords
    crystal microstructure; expert systems; manufacturing processes; materials science computing; neural nets; plastic flow; steel; artificial neural network; flow stress prediction; force requirements; manufacturing processes; material flow stress estimation; microstructure; power requirements; process parameters; rule-based expert system; steel; strain rate; temperature; Artificial neural networks; Expert systems; Materials; Microstructure; Steel; Strain; Stress; AISI 4340; fuzzy reasoning; properties estimation; rule-based system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4673-6320-4
  • Type

    conf

  • DOI
    10.1109/ICIEA.2013.6566431
  • Filename
    6566431