Advertisement

An inverse-identification-based finite element simulation of orthogonal cutting tungsten carbide

  • Wei ZhaoEmail author
  • Qi Yang
  • Aqib Mashood Khan
  • Ning He
  • Anshun Zhang
Technical Paper
  • 45 Downloads

Abstract

Modeling and simulation using finite element method (FEM) is a powerful estimation tool and has been greatly helpful to study the metal cutting process, such as investigation of cutting mechanism, optimization of cutting parameters, and design of cutting tools. Thereinto, an effective material model and its parameters are still key problems in the FEM-modeling of metal cutting. In this paper, a 2D FE model for simulating the orthogonal cutting of tungsten carbide WC-17.5Co is developed, in which an inverse identification approach is used to identify the parameters of material model based on orthogonal cutting experiments. The commercially available software DEFORM V11.0 is utilized to develop the FE model, whereas the Johnson–Cook model and Brozzo model are selected as the constitutive model and the fracture model of the work material, respectively. Continuous serrated chip formation is obtained in experiments as well as in FE simulations. The simulated chip morphology, cutting force, and specific cutting force are compared with the experimental results to identify the parameters of the material model. It is found that the chip morphology is more difficult to be used to identify inversely the material model parameters than the cutting force and specific cutting force. The material model parameters are derived, and the verification tests show that there is a close agreement between the simulated and experimental results through comparisons of cutting force and specific cutting force. It indicates that the inversely identified parameters of the Johnson–Cook model and the Brozzo model can be used to describe the mechanical property of tungsten carbide.

Keywords

Tungsten carbide Finite element simulation Inverse identification Johnson–Cook model Orthogonal cutting 

Notes

Acknowledgements

This research is financially supported by the National Natural Science Foundation of China under the Contract No. 51475234. What’s more, the authors would like to thank the High-performance Cutting Group in Fraunhofer IPT for the sharing experiment data.

References

  1. 1.
    Yaguchi H (2004) The influence of built-up edges on machined surface roughness in low-carbon resulfurized free-machining steel. R&D Res Dev Kobe Steel Eng Rep 54(3):11–15MathSciNetGoogle Scholar
  2. 2.
    Liu K, Li XP (2001) Ductile cutting of tungsten carbide. J Mater Process Technol 113(1–3):348–354CrossRefGoogle Scholar
  3. 3.
    Liu K, Li XP, Rahman M (2003) CBN tool wear in ductile cutting of tungsten carbide. Wear 255:1344–1351CrossRefGoogle Scholar
  4. 4.
    Liu K, Li XP, Rahman M (2003) Characteristics of high speed micro cutting of tungsten carbide. J Mater Process Technol 140:352–357CrossRefGoogle Scholar
  5. 5.
    Nakamoto K, Katahira K, Ohmori H et al (2012) A study on the quality of micro-machined surfaces on tungsten carbide generated by PCD micro end-milling. CIRP Ann Manuf Technol 61(1):567–570CrossRefGoogle Scholar
  6. 6.
    Arif M, Rahman M, San WY (2012) Analytical model to determine the critical conditions for the modes of material removal in the milling process of brittle material. J Mater Process Technol 212(9):1925–1933CrossRefGoogle Scholar
  7. 7.
    Arif M, Rahman M, San WY (2013) A study on the effect of tool-edge radius on critical machining characteristics in ultra-precision milling of tungsten carbide. Int J Adv Manuf Technol 67(5–8):1257–1265CrossRefGoogle Scholar
  8. 8.
    Zhan Z, He N, Li L et al (2015) Precision milling of tungsten carbide with micro PCD milling tool. Int J Adv Manuf Technol 77:2095–2103CrossRefGoogle Scholar
  9. 9.
    Ottersbach M, Zhao W (2016) Experimental investigations on the machinability of tungsten carbides in orthogonal cutting with diamond-coated tools. Proc CIRP 46:416–419CrossRefGoogle Scholar
  10. 10.
    Hintze W, Steinbach S, Susemihl C et al (2018) HPC-milling of WC–Co cemented carbides with PCD. Int J Refract Metal Hard Mater 72:126–134CrossRefGoogle Scholar
  11. 11.
    Ma L, Li C, Chen J et al (2017) Prediction model and simulation of cutting force in turning hard-brittle materials. Int J Adv Manuf Technol 91(1–4):165–174CrossRefGoogle Scholar
  12. 12.
    Ceretti E, Fallböhmer P, Wu WT et al (1996) Application of 2D FEM to chip formation in orthogonal cutting. J Mater Process Technol 59(1–2):169–180CrossRefGoogle Scholar
  13. 13.
    Wan L, Wang D, Gao Y (2016) The investigation of mechanism of serrated chip formation under different cutting speeds. Int J Adv Manuf Technol 82(5–8):951–959CrossRefGoogle Scholar
  14. 14.
    Yaich M, Ayed Y, Bouaziz Z et al (2017) Numerical analysis of constitutive coefficients effects on FE simulation of the 2D orthogonal cutting process: application to the Ti6Al4V. Int J Adv Manuf Technol 93(1–4):283–303CrossRefGoogle Scholar
  15. 15.
    Woolmore NJ (2010) The failure of a tungsten carbide–cobalt cored projectile penetrating a hard target. Cranfield University, CranfieldGoogle Scholar
  16. 16.
    Hazell PJ, Appleby-Thomas GJ, Herlaar K et al (2010) Inelastic deformation and failure of tungsten carbide under ballistic-loading conditions. Mater Sci Eng A 527(29–30):7638–7645CrossRefGoogle Scholar
  17. 17.
    Moxnes JF, Teland JA, Skriudalen S et al (2010) Development of material models for semi-brittle materials like tungsten carbide. Norwegian Defence Research Establishment (FFI), FFI-rapport 2010/02225Google Scholar
  18. 18.
    Klocke F, Lung D, Buchkremer S (2013) Inverse identification of the constitutive equation of Inconel 718 and AISI 1045 from FE machining simulations. Proc CIRP 8:212–217CrossRefGoogle Scholar
  19. 19.
    Umbrello D, Hua J, Shivpuri R (2004) Hardness-based flow stress and fracture models for numerical simulation of hard machining AISI 52100 bearing steel. Mater Sci Eng A 374(1):90–100CrossRefGoogle Scholar
  20. 20.
    Yang SB, Xu J, Fu Y et al (2012) Finite element modeling of machining of hydrogenated Ti–6Al–4V alloy. Int J Adv Manuf Technol 59(1):253–261CrossRefGoogle Scholar
  21. 21.
    Warnecke G, Oh JD (2002) A new thermo-viscoplastic material model for finite-element-analysis of the chip formation process. CIRP Ann Manuf Technol 51(1):79–82CrossRefGoogle Scholar
  22. 22.
    Wang Y, Zhou Y, Xia Y (2004) A constitutive description of tensile behavior for brass over a wide range of strain rates. Mater Sci Eng A 372(1–2):186–190CrossRefGoogle Scholar
  23. 23.
    Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. In: Proceedings of the 7th international symposium on ballistics, Hague, pp 1–7Google Scholar
  24. 24.
    Brozzo P, Deluca B, Rendina R (1972) A new method for the prediction of formability limits in metal sheets–sheet metal forming and formability. In: Proceedings of the 7th biennial conference of the international deep drawing research group, Ohio, pp 18–36Google Scholar
  25. 25.
    Zhang YC, Mabrouki T, Nelias D et al (2011) Chip formation in orthogonal cutting considering interface limiting shear stress and damage evolution based on fracture energy approach. Finite Elem Anal Des 47(7):850–863CrossRefGoogle Scholar
  26. 26.
    Cheng X, Wang Z, Nakamoto K et al (2011) A study on the micro tooling for micro/nano milling. Int J Adv Manuf Technol 53(5):523–533CrossRefGoogle Scholar
  27. 27.
    Filiz S, Conley C, Wasserman M et al (2007) An experimental investigation of micro-machinability of copper 101 using tungsten carbide micro-endmills. Int J Mach Tools Manuf 47:1088–1100CrossRefGoogle Scholar

Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  1. 1.College of Mechanical and Electrical EngineeringNanjing University of Aeronautics and AstronauticsNanjingPeople’s Republic of China
  2. 2.AVIC Chengdu Aircraft Industrial (Group) Co., Ltd.ChengduPeople’s Republic of China

Personalised recommendations