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Investigation of Tool Chatter Features at Higher Metal Removal Rate Using Sound Signals

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Abstract

Chatter-free turning has been a matter of concern for engineers. Improper selection of cutting parameters leads to regenerative chatter and loss of productivity. In the present work, a methodology has been proposed to select an appropriate combination of input cutting parameters for stable turning with improved metal removal rate (MRR). Chatter signals generated during the turning of Al 6061 are acquired using a microphone and processed using local mean decomposition signal processing technique. Thereafter, these decomposed signals have been analyzed in order to extract tool chatter features. Prediction models of chatter indices and MRR have been developed using response surface methodology. Moreover, these prediction models have been optimized using multi-objective genetic algorithm for ascertaining the optimal range of cutting parameters for stable turning with higher MRR. Finally, obtained stable range has been validated by performing more experiments.

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The present work has received no funds in any manner from any organization.

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  1. Jaypee University of Engineering and Technology, Guna, M.P., India

    Pankaj Gupta & Bhagat Singh

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  1. Pankaj Gupta
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  2. Bhagat Singh
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Correspondence to Bhagat Singh.

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Gupta, P., Singh, B. Investigation of Tool Chatter Features at Higher Metal Removal Rate Using Sound Signals. Acoust Aust 48, 141–148 (2020). https://doi.org/10.1007/s40857-020-00180-8

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