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<p>Manufacturing industries' top priority in the current competitive environment is to increase productivity by reducing production costs. This can only be accomplished by improving Metal Removal Rate (MRR) while maintaining high tolerance and superior surface quality products. One issue that restricts the MRR in industries is tool chatter. In this paper, authors have compared two advanced computational methodology in order to predict stable machining zone during turning. Firstly, predict the stable machining zone using Local Mean Decomposition (LMD) for preprocessing of raw data and trained with Artificial Neural network. Further, compare this methodology with Wavelet Denoising and Local Mean Decomposition technique for preprocessing of data and trained with Adaptive Neuro-Fuzzy Inference System. From the analysis it has been found that, spindle speed can be raised to increase stability during machining. Nevertheless, significant chatter is seen when the depth of cut and feed rate are increased. Finally, additional experiments have been conducted to verify the validity of the suggested methodology.</p>

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Comparative Analysis Between LMD and WDLMD for Identifying Suitability in Measuring Chatter Features During Turning Operation on CNC Lathe

  • 期刊论文

  • 发表日期：

    2025年2月15日

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  • Pankaj Gupta,
  • Sunil Kumar,
  • Yogesh Shrivastava

摘要

Manufacturing industries' top priority in the current competitive environment is to increase productivity by reducing production costs. This can only be accomplished by improving Metal Removal Rate (MRR) while maintaining high tolerance and superior surface quality products. One issue that restricts the MRR in industries is tool chatter. In this paper, authors have compared two advanced computational methodology in order to predict stable machining zone during turning. Firstly, predict the stable machining zone using Local Mean Decomposition (LMD) for preprocessing of raw data and trained with Artificial Neural network. Further, compare this methodology with Wavelet Denoising and Local Mean Decomposition technique for preprocessing of data and trained with Adaptive Neuro-Fuzzy Inference System. From the analysis it has been found that, spindle speed can be raised to increase stability during machining. Nevertheless, significant chatter is seen when the depth of cut and feed rate are increased. Finally, additional experiments have been conducted to verify the validity of the suggested methodology.