Improving the useful life of tools using active vibration control through data-driven approaches: a systematic literature review

Vivek Warke, Satish Kumar, Arunkumar Bongale, Pooja Kamat, Ketan Kotecha, Ganeshsree Selvachandran, Ajith Abraham

Research output: Contribution to journalShort SurveyResearchpeer-review

1 Citation (Scopus)

Abstract

In the present era of sustainable smart manufacturing within the industry 4.0 framework, industries thrive to achieve sustainable development. Machining processes play a substantial role in smart manufacturing. At the same time, the cutting tool is the most significant element of any machining process. The excessive tool wear or sudden failure of the cutting tool causes unplanned downtime, and it also affects the quality of finished products, economics, and effectiveness of the process. Among all the aspects, the vibrations that occur during machining and cutting forces are the most critical parameters, which accelerates the rate of tool wear. Active Vibration Control (AVC) techniques have emerged as promising approaches for mitigating the detrimental effects of vibration on tool performance. To realise the maximum potential of AVC, however, requires a methodical and exhaustive understanding of the existing literature. This study demonstrates the significance of conducting a systematic literature review on improving the Useful Life of cutting tools employing AVC and estimating through data-driven methods. A systematic literature review on AVC and remaining useful life (RUL) estimation of a cutting tool is performed using the “Preferred Reporting Items for Systematic Reviews and Meta-Analysis” (PRISMA) methodology. However, the study primarily highlights the active vibration control through MR fluid and its characteristics, modelling, and control techniques. Moreover, the data-driven approach for the RUL prediction is discussed briefly through data acquisition, data processing, feature extraction and ranking techniques together with decision-making algorithms. This review presents a structured method for identifying, evaluating, and synthesising relevant studies, thus providing a comprehensive overview of the current state of research in the field. This review seeks to identify gaps, trends, and research directions in the application of AVC for tool longevity by analysing a wide variety of literature, including peer-reviewed journal articles, conference proceedings, and technical reports. Researchers, engineers, and practitioners engaged in tool design, maintenance, and optimization will benefit from the findings of this systematic literature review. The findings will provide a consolidated knowledge base for informed decision-making, allowing for the identification of knowledge deficits, research opportunities, and avenues for further study. The ultimate objective of this review is to contribute to the advancement of AVC techniques for extending the RUL of tools, nurturing innovation, and promoting sustainable and efficient practises across a variety of industrial sectors.

Original languageEnglish
Article number107367
Number of pages29
JournalEngineering Applications of Artificial Intelligence
Volume128
DOIs
Publication statusPublished - Feb 2024

Keywords

  • Active vibration control
  • Data-driven modelling
  • Magnetorheological fluid
  • Remaining useful life (RUL)
  • Smart manufacturing
  • Tool wear

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