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Finite element simulation of saw-tooth chip in high-speed machining based on multiresolution continuum theory

  • Guohe LiEmail author
  • Jacob Smith
  • Wing Kam LiuEmail author
ORIGINAL ARTICLE
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Abstract

Because the deformation is very large and highly localized in the adiabatic shear bands (ASB) of the saw-tooth chip in high-speed machining (HSM), the physical results of the width and spacing of ASB in saw-tooth chip cannot be given by the traditional finite element method (FEM) due to the mesh dependency. Therefore, a 3D finite element model of HSM based on multiresolution continuum theory (MCT) with a simple algorithm of hourglass control was brought out to predict the saw-tooth chip. The comparison between the simulation results and experimental ones of chip deformation and cutting forces shows the validity of the established model. The formation of saw-tooth chip is analyzed, and the changes of chip morphology with cutting parameters were given. The results show that the MCT model has the ability to capture the width and spacing of shear band of saw-tooth chip in HSM by using a length scale to build the relationship between the macro materials behavior and the microstructure. It can also clearly show the formation of saw-tooth chip. An interesting thing is that during the forming of two adjacent shear bands, there is a transition shear band. The stress of MCT model is slightly larger than that of traditional FEM, but the strain is little smaller and the temperature is little lower. For the cutting force, the simulation results of MCT model are more consistent with experimental ones than that of traditional FEM. The simulation results of chip morphology under the condition of different cutting parameter are consistent with that of experiment.

Keywords

Multiresolution continuum theory Saw-tooth chip High-speed machining Finite element simulation 

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Notes

Acknowledgements

We are grateful for the work of Miguel Bessa on the MCT code.

Funding information

This work is supported by the National Natural Science Foundation of China (Grant No. 51875409), CSC-funded Projects (Grant No. 201307760011), Innovation Team Training Plan of Tianjin Universities and Colleges (Grant No. TD13-5096), and Tianjin Major Special Project for Intelligent Manufacturing (Grant No. 17ZXZNGX00100). This work is also supported by National-Local Joint Engineering Laboratory of Intelligent Manufacturing Oriented Automobile Die and Mold.

References

  1. 1.
    Belhadi S, Mabrouki T, Rigal JF, Boulanouar L (2005) Experimental and numerical study of chip formation during straight turning of hardened AISI 4340 steel. Proc Inst Mech Eng B J Eng Manuf 219:515–524CrossRefGoogle Scholar
  2. 2.
    Sun S, Brandt M, Dargusch MS (2009) Characteristics of cutting forces and chip formation in machining of titanium alloys. Int J Mach Tools Manuf 49:561–568CrossRefGoogle Scholar
  3. 3.
    Davies MA, Chou Y, Evans CJ (1996) On chip morphology, tool wear and cutting mechanics in finish hard turning. Annals of the CIRP 45:77–82CrossRefGoogle Scholar
  4. 4.
    Molinari A, Musquar C, Sutter G (2002) Adiabatic shear banding in high speed machining of Ti-6AL-4V: experiments and modeling. Int J Plast 18:443–459CrossRefzbMATHGoogle Scholar
  5. 5.
    Shaw MC, Vyas A (1993) Chip formation in the machining of hardened steel. Annals of the CIRP 42:29–33CrossRefGoogle Scholar
  6. 6.
    Barry J, Byrne G (2002) The mechanisms of chip formation in machining hardened steel. J Manuf Sci Eng Trans ASME 124:528–535CrossRefGoogle Scholar
  7. 7.
    Guo YB, Yen DW (2004) A FEM study on mechanisms of discontinuous chip formation in hard machining. J Mater Process Technol 1350-1356:s155–s156Google Scholar
  8. 8.
    Uhlmann E, Schulenburg MGVD, Zettier R (2007) Finite element modeling and cutting simulation of Inconel 718. CIRP Annals-Manuf Technol 56:61–64CrossRefGoogle Scholar
  9. 9.
    Umbrello D (2008) Finite element simulation of conventional and high speed machining of Ti6Al4V alloy. J Mater Process Technol 196:79–87CrossRefGoogle Scholar
  10. 10.
    Calamaz M, Coupard D, Girot F (2008) A new material model for 2D numerical simulation of serrated chip formation when machining titanium alloy Ti-6Al-4V. Int J Mach Tools and Manuf 48:275–288CrossRefGoogle Scholar
  11. 11.
    Chen T, Liu XL, Luo GT (2009) Numerical simulation and experimental study on hard turning of hardened steel using PCBN cutting tool. J Sys Sim 21:5586–5593Google Scholar
  12. 12.
    Sima M, Özel T (2010) Modified material constitutive models for serrated chip formation simulations and experimental validation in machining of titanium alloy Ti-6Al-4V. Int J Mach Tools Manuf 50:943–960CrossRefGoogle Scholar
  13. 13.
    Chen G, Ren CZ, Yang XY, Jin XM, Guo T (2011) Finite element simulation of high-speed machining of titanium alloy (Ti-6Al-4V) based on ductile failure model. Int J Adv Manuf Technol 56:1027–1038CrossRefGoogle Scholar
  14. 14.
    Wang B, Liu ZQ (2014) Investigations on the chip formation mechanism and shear localization sensitivity of high speed machining Ti6Al4V. Int J Adv Manuf Technol 75:1065–1076CrossRefGoogle Scholar
  15. 15.
    Zhang L, Duan CZ (2013) A reliable method for predicting serrated chip formation in high-speed cutting: analysis and experimental verification. Int J Adv Manuf Technol 64:1587–1597CrossRefGoogle Scholar
  16. 16.
    Tang DW, Wang CY, Hu YN (2011) Finite-element simulation of conventional and high-speed peripheral milling of hardened mold steel. Metall Mater Trans A 40:3245–3257CrossRefGoogle Scholar
  17. 17.
    Issa M, Labergère C, Saanouni K, Rassineux A (2012) Numerical prediction of thermomechanical field localization in orthogonal cutting. CIRP J Manuf Sci Technol 5:175–195CrossRefGoogle Scholar
  18. 18.
    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
  19. 19.
    Li P, Qiu X, Tang S, Tang L (2016) Study on dynamic characteristics of serrated chip formation for orthogonal turning Ti6Al4V. Int J Adv Manuf Technol 86:3289–3296CrossRefGoogle Scholar
  20. 20.
    Yaich M, Ayed Y, Bouaziz Z, Germain G (2016) Numerical analysis of constitutive coefficients effects on FE simulation of the 2D orthogonal cutting process: application to the Ti6Al4V. Int J Adv Manuf Technol 86:1–21Google Scholar
  21. 21.
    Vernerey F, Liu WK, Moran B (2007) Multi-scale micromorphic theory for hierarchical materials. J Mech Phy Solids 55:2603–2651MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    Vernerey F, Liu WK, Moran B, Olson G (2008) A micromorphic model for the multiple scale failure of heterogeneous materials. J Mech Phys Solids 56:1320–1347MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    McVeigh C, Liu WK (2008) Multiresolution modeling of ductile reinforced brittle composites. J Mech Phys Solids 57:244–267CrossRefzbMATHGoogle Scholar
  24. 24.
    McVeigh C, Liu WK (2010) Multiresolution continuum modeling of micro-void assisted dynamic adiabatic shear band propagation. J Mech Phys Solids 58:187–205MathSciNetCrossRefzbMATHGoogle Scholar
  25. 25.
    Liu WK (2006) Multiresolution analysis for material design. Comput Methods Appl Mech Eng 195:5053–5076MathSciNetCrossRefzbMATHGoogle Scholar
  26. 26.
    Tang S, Kopacz AM, Keeffe SCO, Olson G, Liu WK (2013) Three-dimensional ductile fracture analysis with a hybrid multiresolution approach and microtomography. J Mech Phys Solids 61:2108–2124CrossRefGoogle Scholar
  27. 27.
    Li GH, Wang MJ (2010) Dynamic mechanical properties and constitutive relationship of hardened 45 steel (45HRC) under high temperature and high strain rate. Explos Shock Wav 30:433–438Google Scholar
  28. 28.
    Guo YB, Wen Q, Woodbury KA (2006) Dynamic material behavior modeling using internal state variable plasticity and its application in hard machining simulations. J Manuf Sci Eng 128:749–756CrossRefGoogle Scholar
  29. 29.
    Yen YC, Jain A, Altan T (2004) A finite element analysis of orthogonal machining using different tool edge geometries. J Mater Process Technol 146:72–81CrossRefGoogle Scholar
  30. 30.
    Rhim SH, Oh SI (2006) Prediction of serrated chip formation in metal cutting process with new flow stress model for AISI 1045 steel. J Mater Process Technol 171:417–422CrossRefGoogle Scholar
  31. 31.
    Barge M, Hamdi H, Rech J (2005) Numerical modeling of orthogonal cutting: influence of numerical parameters. J Mater Process Technol s164–165:1148–1153CrossRefGoogle Scholar
  32. 32.
    Bäker M (2006) Finite element simulation of high-speed cutting forces. J Mater Process Technol 176:117–126CrossRefGoogle Scholar
  33. 33.
    Childs THC (2006) Friction modeling in metal cutting. Wear 260:310–318CrossRefGoogle Scholar
  34. 34.
    Özel T (2006) The influence of friction models on finite element simulations of machining. Int J Mach Tools Manuf 46:518–530CrossRefGoogle Scholar
  35. 35.
    Filice L, Micari F, Rizzuti S, Umbrello D (2007) A critical analysis on the friction modeling in orthogonal machining. Int J Mach Tools Manuf 47:709–714CrossRefGoogle Scholar
  36. 36.
    Calamaz M, Coupard D, Nouari M, Girot F (2007) A finite element model of high speed machining of Ti6Al4V titanium alloy, in: Sixth International Conference on High Speed Machining (HSM), San Sebastian, Spain, 21–22 March (edited CD)Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Tianjin Key Laboratory of High Speed Cutting and Accurate Process TechnologyTianjinChina
  2. 2.Department of Mechanical EngineeringNorthwestern UniversityEvanstonUSA

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