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

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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.

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References

  1. Arrazola PJ, Özel T, Umbrello D, Davies M, Jawahir IS (2013) Recent advances in modelling of metal machining processes. CIRP Ann - Manuf Technol 62:695–718. https://doi.org/10.1016/j.cirp.2013.05.006

    Article  Google Scholar 

  2. Melkote SN, Grzesik W, Outeiro J, Rech J, Schulze V, Attia H, Arrazola PJ, M’Saoubi R, Saldana C (2017) Advances in material and friction data for modelling of metal machining. CIRP Ann - Manuf Technol 66:731–754. https://doi.org/10.1016/j.cirp.2017.05.002

    Article  Google Scholar 

  3. Malakizadi A, Hosseinkhani K, Mariano E, Ng E, Del Prete A, Nyborg L (2017) Influence of friction models on FE simulation results of orthogonal cutting process. Int J Adv Manuf Technol 88:3217–3232. https://doi.org/10.1007/s00170-016-9023-4

    Article  Google Scholar 

  4. Johansson D, Hägglund S, Bushlya V, Ståhl JE (2017) Assessment of commonly used tool life models in metal cutting. Procedia Manuf 11:602–609. https://doi.org/10.1016/j.promfg.2017.07.154

    Article  Google Scholar 

  5. Usui E, Hirota A, Masuko M (1978) Analytical prediction of three dimensional cutting process—part 1: basic cutting model and energy approach. J Eng Ind 100:222. https://doi.org/10.1115/1.3439413

    Article  Google Scholar 

  6. Usui E, Shirakashi T, Kitagawa T (1984) Analytical prediction of cutting tool wear. Wear. 100:129–151. https://doi.org/10.1016/0043-1648(84)90010-3

    Article  Google Scholar 

  7. Binder M, Klocke F, Lung D (2015) Tool wear simulation of complex shaped coated cutting tools. Wear. 330–331:600–607. https://doi.org/10.1016/j.wear.2015.01.015

    Article  Google Scholar 

  8. Malakizadi A, Gruber H, Sadik I, Nyborg L (2016) An FEM-based approach for tool wear estimation in machining. Wear. 368–369:10–24. https://doi.org/10.1016/j.wear.2016.08.007

    Article  Google Scholar 

  9. Pálmai Z (2013) Proposal for a new theoretical model of the cutting tool’s flank wear. Wear. 303:437–445. https://doi.org/10.1016/j.wear.2013.03.025

    Article  Google Scholar 

  10. Attanasio A, Ceretti E, Fiorentino A, Cappellini C, Giardini C (2010) Investigation and FEM-based simulation of tool wear in turning operations with uncoated carbide tools. Wear. 269:344–350. https://doi.org/10.1016/j.wear.2010.04.013

    Article  Google Scholar 

  11. Takeyama H, Murata R (1963) Basic investigation of tool Wear. J Eng Ind 85:33. https://doi.org/10.1115/1.3667575

    Article  Google Scholar 

  12. F. Ramírez P, Soldani X, Loya J, Miguélez H (2017) A new approach for time-space wear modeling applied to machining tool wear. Wear 390–391:125–134. https://doi.org/10.1016/j.wear.2017.07.015

    Article  Google Scholar 

  13. Matsumoto Y, Barash MM, Liu CR (1987) Cutting mechanism during machining of hardened steel. Mater Sci Technol 3:299–305. https://doi.org/10.1179/026708387790122756

    Article  Google Scholar 

  14. König W, Berktold A, Koch K-F (1993) Turning versus grinding – a comparison of surface integrity aspects and attainable accuracies. CIRP Ann - Manuf Technol 42:39–43. https://doi.org/10.1016/S0007-8506(07)62387-7

    Article  Google Scholar 

  15. Koch K-F (1996) Technologie des Hochpräzisions-Hartdrehens, RWTH-Aachen

  16. Poulachon G, Moisan A, Jawahir IS (2001) Tool-wear mechanisms in hard turning with polycrystalline cubic boron nitride tools. Wear 250:576–586. https://doi.org/10.1016/S0043-1648(01)00609-3

    Article  Google Scholar 

  17. Huang Y, Liang SY (2004) Modeling of CBN tool flank wear progression in finish hard turning. J Manuf Sci Eng 126:98. https://doi.org/10.1115/1.1644543

    Article  Google Scholar 

  18. Boing D, Schroeter RB, de Oliveira AJ (2018) Three-dimensional wear parameters and wear mechanisms in turning hardened steels with PCBN tools. Wear. 398–399:69–78. https://doi.org/10.1016/j.wear.2017.11.017

    Article  Google Scholar 

  19. ISO 3685:1993 (1993) Tool life testing with single-point turning tools. International Organization for Standardization ISO 3685

  20. Boing D (2016) Transição da aplicação do metal-duro revestido e do PCBN no torneamento de aços endurecidos em função da dureza e do teor de carbonetos, Universidade Federal de Santa Catarina – UFSC. http://www.bu.ufsc.br/teses/PEMC1752-T.pdf

  21. Brecher C, Esser M, Witt S (2009) Interaction of manufacturing process and machine tool. CIRP Ann 58:588–607. https://doi.org/10.1016/j.cirp.2009.09.005

    Article  Google Scholar 

  22. Klocke F (2010) Manufacturing processes 1: cutting. https://doi.org/10.1007/978-3-642-11979-8

    Book  Google Scholar 

  23. Danzl R, Helmli F, Scherer S (2009) Focus variation - a new technology for high resolution optical 3D surface metrology. In: 10th Int. Conf. Slov. Soc. Non-Destructive Test, pp 1–10. https://doi.org/10.5545/sv-jme.2010.175

    Article  Google Scholar 

  24. Boing D, de Oliveira AJ, Schroeter RB (2018) Limiting conditions for application of PVD (TiAlN) and CVD (TiCN/Al2O3/TiN) coated cemented carbide grades in the turning of hardened steels. Wear. 416–417:54–61. https://doi.org/10.1016/j.wear.2018.10.007

    Article  Google Scholar 

  25. Castro FL, Boing D, Schroeter RB (2018) Tool performance assessment based on three-dimensional tool wear rate. Procedia CIRP 77:638–641. https://doi.org/10.1016/j.procir.2018.08.188

    Article  Google Scholar 

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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

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

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Authors and Affiliations

  1. Department of Mechanical Engineering, Technology, Innovation, and Manufacturing Center, Brusque University Center, 123 Dorval Luz St., Santa Terezinha, Brusque, SC, 88352-400, Brazil

    Denis Boing

  2. Department of Mechanical Engineering, Laboratory of Precision Mechanics, Federal University of Santa Catarina, Florianópolis, SC, Brazil

    Fernando Luiz Castro & Rolf Bertrand Schroeter

Authors
  1. Denis Boing
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  2. Fernando Luiz Castro
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  3. Rolf Bertrand Schroeter
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Correspondence to Denis Boing.

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Boing, D., Castro, F.L. & Schroeter, R.B. Prediction of PCBN tool life in hard turning process based on the three-dimensional tool wear parameter. Int J Adv Manuf Technol 106, 779–790 (2020). https://doi.org/10.1007/s00170-019-04509-0

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