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Review of tool condition monitoring methods in milling processes

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Abstract

Accurate tool condition monitoring (TCM) is essential for the development of fully automated milling processes. However, while considerable research has been conducted in industrial and academic settings, the complexity of milling processes continues to complicate the implementation of TCM. This paper presents a review of the state-of-the-art methods employed for conducting TCM in milling processes. The review includes three key components: (1) sensors, (2) feature extraction, and (3) monitoring models for the categorization of cutting tool states in the decision-making process. In addition, the primary strengths and weaknesses of current practices are presented for these three components. Finally, this paper concludes with a list of recommendations for future research.

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Acknowledgments

The authors are grateful for support from the National Science Foundation of China (Grant No. 51405346), the Zhejiang Provincial Natural Science Foundation of China (Grant No. LY17E050005), and the Wenzhou City Public Industrial Science and Technology Project of China (Grant Nos. G20160015 and G20170009). We also thank LetPub (www.LetPub.com) for its linguistic assistance during the preparation of this manuscript.

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  1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, China

    Yuqing Zhou

  2. College of Mechanical Engineering, Wenzhou University, Wenzhou, China

    Yuqing Zhou & Wei Xue

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Zhou, Y., Xue, W. Review of tool condition monitoring methods in milling processes. Int J Adv Manuf Technol 96, 2509–2523 (2018). https://doi.org/10.1007/s00170-018-1768-5

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