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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      Volume 37 Issue 4, 2022   
    Article

    SURFACE ROUGHNESS OPTIMIZATION IN LASER BEAM MACHINING BY USING ANN ( ARTIFICIAL NEURAL NETWORK )
    Gourav Purohit, Dr. Vinay Chandra Jha
    Journal of Data Acquisition and Processing, 2022, 37 (4): 2623-2637. 

    Abstract

    Machining modern materials with traditional techniques results in an increase in the high cutting temperature, high cutting force magnitudes, tool wear, reduced tool life, and a poor quality machined surface. The machining of these materials using traditional methods is initially going to result in a loss of profitability. Among the many unconventional approaches to machining, laser beam machining, also known as LBM, is garnering the most attention from researchers. In this work, we focus on the possible applications of LBM for the machining of a variety of materials, as well as recent developments, advantages and difficulties associated with machining, process parameters and performance characteristics, modelling, and optimisation. It is necessary to have process parameters that have been conscientiously designed and are suitable for LBM. To produce a model that delivers extremely good fitting with tests while determining the effects of many process parameters, it is unquestionable that investigationally based modelling and optimisation approaches are necessary components.

    Keyword

    non-ferrous, laser beam machining, ferrous material


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ISSN 1004-9037

         

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