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Trochoidal milling: investigation of a new approach on uncut chip thickness modeling and cutting force simulation in an alternative path planning strategy

  • Farbod Akhavan Niaki
  • Abram Pleta
  • Laine Mears
ORIGINAL ARTICLE
  • 116 Downloads

Abstract

Trochoidal milling is an alternative tool path strategy which has been shown to increase productivity, improve tooling life, and reduce resultant cutting forces. While the advantages of trochoidal milling over conventional slot or shoulder milling were previously reported, the complexity of trochoid tool path makes developing an analytical force model highly complicated. In this work, a numerical algorithm to construct the uncut chip thickness model in trochoidal milling is introduced, which is based on the geometrical relation of self-intersection and cross-intersection points of the tool path curve. In addition, an extensive series of experiments is carried out in slot and trochoidal-milling operations in order to investigate the dependency of cutting pressure coefficients on tool path parameters and to develop a model to relate the two. Furthermore, the performance of the developed model for uncut chip thickness and the cutting pressure coefficients are evaluated in predicting cutting forces; it is shown that the model predicts the maximum cutting force in the feed direction and between all the testing sets with 8% total average error, while 17% total average error is observed in predicting maximum cutting force in the lateral direction. This demonstrates the potential of the proposed approach in offline simulation of the cutting forces which is a critical step in selecting proper tooling and process parameters to increase productivity of the cut.

Keywords

Trochoidal milling Slot milling Uncut chip thickness Force modeling Alternative tool path 

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Notes

Acknowledgments

The authors would like to thank Mr. Douglas M. Schwarz of the University of Rochester for providing his source code for finding intersection points.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Farbod Akhavan Niaki
    • 1
  • Abram Pleta
    • 1
  • Laine Mears
    • 1
  1. 1.International Center for Automotive ResearchClemson UniversityGreenvilleUSA

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