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<p>In precision engineering and machining industries, multi-edged cutting tools are used as these tools increase tool life. However, in most machining processes, these tools are changed before all their cutting edges are used because of the unskilled labour and less knowledge about tool wear. This means a few cutting edges are not used in a multi cutting edge insert like TNMG, CNMG. These used tools are not classified and not stored in appropriately in MSME which leads difficulties to identify and reuse the unused cutting-edge inserts. This practice results in unnecessary increases tooling costs for machining industries. This practice can be improved to increase efficiency in utilizing these partialized used cutting edge tools. With recent developments in automation and machine vision systems can be used for tool wear detection and reuse the partially used cutting tools towards a sustainable manufacturing. This paper presents a case study report on cutting tool inserts utilization and cost analysis to understand the effect of premature disposal of carbide inserts in the tooling cost. To propose a sustainable solution for this problem a detailed review is made on tool wear classifications, wear measurement techniques, image processing in wear measurements. Also, this review is extended on automation techniques to design an automation system in future for sorting the classified inserts and store them appropriately for reuse. Several research briefed about wear mechanisms such as abrasive, adhesive, oxidational, and diffusional wear and its contribution individually or collectively to tool degradation. Also this research extended on the wear study about the flank wear and crater wear of carbide inserts. Experimental method of wear measurements using camera-based Image processing technology is illustrated in comprehensive. Artificial intelligent techniques such as ANN, CNN is discussed for tool wear classification. Conveyor based automation for sorting and collecting system is also proposed in few articles. Recycled carbide material is now used for cutting tool manufacturing. Currently, recycled carbide material contributes to 20% of the world’s cutting tool manufacturing. This contribution is expected to increase from 20% (currently) to nearly 35% by 2030. This shows the importance of sustainability in machining industries [53]. The findings from this review will contribute to the development of an intelligent integrated system for the classification and sorting of cutting tool inserts. This intelligent system combined with recycling can boost more efficient and sustainable manufacturing systems. These practices are important in reducing unnecessary tool waste and promoting efficient use of resources in machining processes.</p>

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Towards sustainable manufacturing: a review of intelligent cutting tool wear detection and reuse through machine vision and automation

  • 期刊论文

  • 发表日期：

    2026年6月30日

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  • Sangeetha N,
  • Prasin S.,
  • Rohith Dharshan B.,
  • Sanjay S.,
  • Santhiya S.,
  • Kavin Mathi K.

摘要

In precision engineering and machining industries, multi-edged cutting tools are used as these tools increase tool life. However, in most machining processes, these tools are changed before all their cutting edges are used because of the unskilled labour and less knowledge about tool wear. This means a few cutting edges are not used in a multi cutting edge insert like TNMG, CNMG. These used tools are not classified and not stored in appropriately in MSME which leads difficulties to identify and reuse the unused cutting-edge inserts. This practice results in unnecessary increases tooling costs for machining industries. This practice can be improved to increase efficiency in utilizing these partialized used cutting edge tools. With recent developments in automation and machine vision systems can be used for tool wear detection and reuse the partially used cutting tools towards a sustainable manufacturing. This paper presents a case study report on cutting tool inserts utilization and cost analysis to understand the effect of premature disposal of carbide inserts in the tooling cost. To propose a sustainable solution for this problem a detailed review is made on tool wear classifications, wear measurement techniques, image processing in wear measurements. Also, this review is extended on automation techniques to design an automation system in future for sorting the classified inserts and store them appropriately for reuse. Several research briefed about wear mechanisms such as abrasive, adhesive, oxidational, and diffusional wear and its contribution individually or collectively to tool degradation. Also this research extended on the wear study about the flank wear and crater wear of carbide inserts. Experimental method of wear measurements using camera-based Image processing technology is illustrated in comprehensive. Artificial intelligent techniques such as ANN, CNN is discussed for tool wear classification. Conveyor based automation for sorting and collecting system is also proposed in few articles. Recycled carbide material is now used for cutting tool manufacturing. Currently, recycled carbide material contributes to 20% of the world’s cutting tool manufacturing. This contribution is expected to increase from 20% (currently) to nearly 35% by 2030. This shows the importance of sustainability in machining industries [53]. The findings from this review will contribute to the development of an intelligent integrated system for the classification and sorting of cutting tool inserts. This intelligent system combined with recycling can boost more efficient and sustainable manufacturing systems. These practices are important in reducing unnecessary tool waste and promoting efficient use of resources in machining processes.