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Prediction of PCBN tool life in hard turning process based on the three-dimensional tool wear parameter

  • Denis BoingEmail author
  • Fernando Luiz Castro
  • Rolf Bertrand Schroeter
ORIGINAL ARTICLE
  • 19 Downloads

Abstract

The ideal scenario for the implementation of a machining process is to be able to predict tool performance without the need to conduct practical experiments. However, in an industrial environment, each set of machining conditions is unique, since the machine-tool conditions, machined material, cutting tool, and fixture system can vary. This can lead to differences between the predicted values and practical results. In this context, the aim of this research was to show and discuss a tool performance test methodology and a tool-life prediction model using the three-dimensional (volumetric) wear parameter WRM (volume of material removed from the tool) applied to hard turning with PCBN tools. The wear parameter WRM is measured at the beginning of the tool life (up to 25%) by focus variation microscopy (FVM). The tool wear rate (WRRM) is then calculated based on the ordinary least squares (OLS) method, and the tool life is estimated (TWRM) adopting the volume of material removed from the tool (WRMmax) as the criteria for the end of tool life. The tool-life model developed was capable of predicting the tool life with errors below 4% at the higher values of cutting speed adopted (vc = 150–187.5 m/min), that is, the cutting speeds applied industrially. The methodology adopted and the model developed represent a significant time reduction in the experimental machining tests, streamlining the research and development of the cutting tool grades, as well as the machining process optimization.

Keywords

Hard turning PCBN tools Tool-life prediction Three-dimensional wear parameters 

Notes

Acknowledgements

The authors would like to thank Sandvik Coromant® for supplying the cutting tools, Alicona® for providing resources and discussions on the measurement methods, and Villares Metals® for supplying the steel alloys.

Funding information

The authors would like to thank CNPq (National Council for Scientific and Technological Development) for their financial support.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Denis Boing
    • 1
    Email author
  • Fernando Luiz Castro
    • 2
  • Rolf Bertrand Schroeter
    • 2
  1. 1.Department of Mechanical Engineering, Technology, Innovation, and Manufacturing CenterBrusque University CenterBrusqueBrazil
  2. 2.Department of Mechanical Engineering, Laboratory of Precision MechanicsFederal University of Santa CatarinaFlorianópolisBrazil

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