A new method for prediction of cutting force considering the influence of machine tool system and tool wear

Xi Chen, Zhao Zhang, Qi Wang, Dinghua Zhang, Ming Luo

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Milling force can usually be predicted based on orthogonal cutting data by applying the classical oblique cutting transformation. However, the accuracy of the prediction is largely affected by the dynamic characteristics of the machine tool system and tool wear. This paper proposes a prediction method of cutting force considering the influence of machine tool system and tool wear to improve the accuracy of the conversion from orthogonal cutting to milling. First, the machine tool correction coefficients are used to introduce the influence of machine tool system into the orthogonal cutting force prediction model. Then, the influence of the tool wear is taken into account by defining the tool wear coefficients. Finally, the accuracy of the cutting force obtained by the proposed method is verified through experimental research. The results show that the prediction results are in good agreement with the experimental results.

Original languageEnglish
Pages (from-to)1843-1852
Number of pages10
JournalInternational Journal of Advanced Manufacturing Technology
Volume120
Issue number3-4
DOIs
StatePublished - May 2022

Keywords

  • Cutting force prediction
  • Data conversion
  • Milling
  • Tool wear

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