• DocumentCode
    2018282
  • Title

    Review of ANN Technique for Modeling Surface Roughness Performance Measure in Machining Process

  • Author

    Zain, Azlan Mohd ; Haron, Habibollah ; Sharif, Safian

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Skudai
  • fYear
    2009
  • fDate
    25-29 May 2009
  • Firstpage
    35
  • Lastpage
    39
  • Abstract
    The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as statistical regression technique, explicit models are developed that required complex physical understanding of the modeling process. With non conventional approaches or artificial intelligence techniques such as artificial neural network, fuzzy logic and genetic algorithm based modeling, implicit model are created within the weight matrices of the net, rules and genes that is easier to be implemented. With the focus on surface roughness performance measure, this paper outlines and discusses the concept, application, abilities and limitations of artificial neural network in the machining process modeling. Subsequently the future trend of artificial neural network in modeling machining process is reported.
  • Keywords
    fuzzy logic; genetic algorithms; machining; neural nets; production engineering computing; regression analysis; surface roughness; ANN technique; artificial intelligence technique; artificial neural network; fuzzy logic; genetic algorithm; machining process modeling; mathematical model; statistical regression technique; surface roughness performance measure; weight matrix; Analytical models; Artificial intelligence; Artificial neural networks; Fuzzy logic; Machining; Mathematical model; Predictive models; Response surface methodology; Rough surfaces; Surface roughness; ANN; machining; modeling; surface roughness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling & Simulation, 2009. AMS '09. Third Asia International Conference on
  • Conference_Location
    Bali
  • Print_ISBN
    978-1-4244-4154-9
  • Electronic_ISBN
    978-0-7695-3648-4
  • Type

    conf

  • DOI
    10.1109/AMS.2009.78
  • Filename
    5071954