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    ARTICLE

    Application of Machine Learning for Tool Condition Monitoring in Turning

    A. D. Patange1,2, R. Jegadeeshwaran1,*, N. S. Bajaj2, A. N. Khairnar2, N. A. Gavade2

    Sound & Vibration, Vol.56, No.2, pp. 127-145, 2022, DOI:10.32604/sv.2022.014910 - 25 March 2022

    Abstract

    The machining process is primarily used to remove material using cutting tools. Any variation in tool state affects the quality of a finished job and causes disturbances. So, a tool monitoring scheme (TMS) for categorization and supervision of failures has become the utmost priority. To respond, traditional TMS followed by the machine learning (ML) analysis is advocated in this paper. Classification in ML is supervised based learning method wherein the ML algorithm learn from the training data input fed to it and then employ this model to categorize the new datasets for precise prediction of

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