Volume 2, Issue 5 (May 2005)

    Determining Nitriding Parameters with Neural Networks

    (Received 6 October 2003; accepted 16 February 2005)

    Published Online: 2005

    CODEN: JAIOAD

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    Abstract

    The choice of correct plasma nitriding parameters is usually experience-based. There are no successful mathematical models for the nitriding process simulation. An attempt has been made to accurately determine required nitriding time for the specified effective nitriding layer thickness, sum of weight contents of nitride forming elements in steel, and nitriding temperature. Two methods were used to solve this problem: the statistical multiple regression and the artificial neural network. It is not possible to find a regression model that would relate the three variables to nitriding time, whereas good results were achieved with neural networks. The second problem that was investigated was the determination of post-nitriding surface hardness on the basis of three known parameters: nitriding time and temperature, and the sum of weight contents of nitride forming elements in steel. Again, a general regression model was not found, and the neural networks produced very good results.


    Author Information:

    Filetin, T
    University of Zagreb,

    Žmak, I
    University of Zagreb,

    Novak, D
    University of Zagreb,


    Stock #: JAI12213

    ISSN: 1546-962X

    DOI: 10.1520/JAI12213

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    Author
    Title Determining Nitriding Parameters with Neural Networks
    Symposium , 0000-00-00
    Committee D20