Intelligent evolution strategies for high-performance cutting tools: status, challenges, and trends

  • Traditional tools have limited adaptability in complex machining environments due to their lack of working-condition perception and autonomous regulation. With advances in sensors, materials, and data-processing technologies, tool design is shifting from a single-function ‘mechanical arm’ for cutting towards integrated intelligent terminals. This paper systematically reviews progress in intelligent tool technology from two perspectives: design and regulation. For intelligent design, the fundamental principles of condition-perception tools equipped with built-in multi-type sensors are discussed, enabling in situ, real-time monitoring of multidimensional parameters such as cutting force, temperature, and vibration. Force monitoring is achieved through elastic deformation or dynamic charge response, temperature monitoring through the thermoelectric effect, and vibration monitoring through micro-displacement and intensity detection. The design focus emphasises sensor miniaturisation and integration, balancing measurement accuracy with tool stiffness while minimising machining interference. In regulation, key technologies for constructing closed-loop control systems (CLCS) are summarised, which dynamically adjust cutting speed, feed rate, and other parameters based on sensed data, achieving precise control of force, temperature, and vibration via feedback mechanisms and driving units. Breakthroughs in tool wear compensation (TWC) mechanisms are introduced. Multi-source signal fusion combined with deep learning algorithms is further examined for improving monitoring accuracy and remaining useful life (RUL) prediction. Through model predictive control, intelligent regulation of cutting parameters within process flows is realised. Finally, challenges such as sensor reliability, multi-source coupling, and balancing cost with industrial applicability are analysed. Future directions highlight novel structural designs, high-performance material development, and multi-technology integration, aiming to establish a fully intelligent machining system through the integrated design of ‘perception-decision-execution’.
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Wan N, Wang Z H, Zhao B, Ding W F, Liu Q. 2026. Intelligent evolution strategies for high-performance cutting tools: status, challenges, and trends. Int. J. Extrem. Manuf. 8 022007.. DOI: 10.1088/2631-7990/ae24c2
Wan N, Wang Z H, Zhao B, Ding W F, Liu Q. 2026. Intelligent evolution strategies for high-performance cutting tools: status, challenges, and trends. Int. J. Extrem. Manuf. 8 022007.. DOI: 10.1088/2631-7990/ae24c2

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