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February 2, 2026The International Journal of Advanced Manufacturing Technology4 citations

Wear and wear suppression of carbide tool in intermittent cutting: a review

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ZLZ. LiPZPengyuan ZhangFZFei Zhou

Key Points

  • This review examines wear mechanisms and suppression strategies for carbide tools in intermittent cutting.
  • Systematic review of studies on tool wear mechanisms and suppression techniques.
  • Analysis of both uncoated and coated cemented carbide tools under impact loads.
  • Discussion of physical suppression strategies including cryogenic cutting and ultrasonic vibration-assisted machining.
  • Identified key wear mechanisms associated with impact loads.
  • Highlighted surface micro-texturing and tool matrix optimization as effective strategies.
  • Demonstrated the role of machine learning and digital twin in real-time monitoring and adaptive control for cutting tools.

Abstract

Intermittent cutting is characterized by high-frequency impact loads, which often lead to accelerated tool wear and premature failure. Carbide tools play a crucial role in intermittent cutting due to their superior physical and mechanical properties and cost efficiency. However, the repeated impacts inherent in this machining mode significantly exacerbate tool wear. This paper systematically reviews recent research advances regarding the wear mechanisms of cemented carbide tools and comprehensive suppression strategies for this domain. First, the key physical and chemical mechanisms of tool wear under cyclic impact loads are thoroughly examined, considering both uncoated and commonly used coated cemented carbide tools. Second, physical suppression strategies to extend tool life are discussed, including the optimization of the tool matrix, the application of surface micro-texturing, and the control of interface interactions through approaches such as cryogenic cutting, ultrasonic vibration-assisted machining, and plasma-assisted machining. Furthermore, reflecting the shift toward intelligent manufacturing, this review critically analyzes data-driven strategies utilizing machine learning and digital twin. These technologies enable real-time wear monitoring, precise life prediction, and adaptive process control, complementing traditional physical approaches. Finally, future research directions emphasizing the synergy between physical suppression and digital intelligence are proposed, guiding the development of more durable cutting tools and advanced machining techniques.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69800910aa6434d8c2036d6bhttps://doi.org/10.1007/s00170-026-17527-6
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