3D FEM simulation of chip breakage in metal cutting

  • S. BuchkremerEmail author
  • F. Klocke
  • D. Veselovac


In metal cutting, unbroken chips may scratch the machined surface and hinder an efficient chip removal. Despite its relevance, the established methodologies of tool/process design with regard to chip breakage are still dominated by expensive empirical approaches. Valid predictive modeling helps to reduce the experimental effort and safe costs. Chip breakage initiates with ductile material fracture on the chip free surface. The fracture strain is influenced by the temperature and stress state, which is defined by the stress triaxiality and Lode angle. An introduction of fracture models considering these combined impacts to the finite element (FE) simulation of chip breakage is not available. In this work, a new model of final ductile fracture is proposed, calibrated, and applied for the 3D FE simulation of chip breakage in turning processes of AISI 1045 (C45E+N). The calculation of the fracture strain considers the stress triaxiality, Lode angle, and temperature. A new non-iterative calibration procedure is proposed, which describes the relationships between the chip geometry at breakage and the thermomechanical state variables on the chip free surface. By implementing experimentally obtained chip geometries into this methodology, the combinations of strain, stress triaxiality, Lode angle, and temperature are determined under which ductile fracture was observed in the cutting tests. Finally, a regression analysis delivers all material constants. The fracture model is implemented into a FE-chip formation model. The predicted locations of fracture are compared to high-speed videos of turning experiments while the direction of crack propagation is validated by scanning electron microscopical images of experimental chips.


Metal cutting Chip breakage Finite element method Ductile fracture 


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  1. 1.
    Klocke F (2010) Manufacturing processes 1—cutting. Springer, Berlin HeidelbergGoogle Scholar
  2. 2.
    Choi JP, Lee SJ (2001) Efficient chip breaker design by predicting the chip breaking performance. Int J Adv Manuf Technol 17:489–497. doi: 10.1007/PL00003947 CrossRefGoogle Scholar
  3. 3.
    Balaji AK, Ghosh R, Fang XD, Stevenson R, Jawahir IS (2006) Performance-based predictive models and optimization methods for turning operations and applications: part 2-assessment of chip forms/chip breakability. J Manuf Process 8(2):144–158. doi: 10.1016/S1526-6125(06)80009-5 CrossRefGoogle Scholar
  4. 4.
    Altintas Y (2000) Manufacturing automation. Metal cutting mechanics, machine tool vibrations, and CNC design. Cambridge University Press, New YorkGoogle Scholar
  5. 5.
    Kim HG, Sim JH, Kweon HJ (2009) Performance evaluation of chip breaker utilizing neural network. J Mater Process Technol 209(2):647–656. doi: 10.1016/j.jmatprotec.2008.02.064 CrossRefGoogle Scholar
  6. 6.
    Astakhov VP (1999) Metal cutting mechanics. CRC Press LLC, Boca RatonGoogle Scholar
  7. 7.
    Klocke F, Lung D, Essig C (2011) 3D FEM model for the prediction of chip breakage. Adv Mater Res 223:142–151. doi: 10.4028/ CrossRefGoogle Scholar
  8. 8.
    Jawahir IS (1988) The tool restricted contact effect as a major influencing factor in chip breaking: an experimental analysis. CIRP J Manuf Sci Technol 37:121–126. doi: 10.1016/S0007-8506(07)61600-X CrossRefGoogle Scholar
  9. 9.
    Fang N (1998) Influence of the geometrical parameters of the chip groove on chip breaking performance using new-style chip formers. J Mater Process Technol 74(1–3):268–275. doi: 10.1016/S0924-0136(97)00282-3 CrossRefGoogle Scholar
  10. 10.
    Mesquita R, Soares F, Barata Marques M (1996) An experimental study of the effect of cutting speed on chip breaking. J Mater Process Technol 56:313–320. doi: 10.1016/0924-0136(95)01845-X CrossRefGoogle Scholar
  11. 11.
    Tikal F (1976) Beurteilung von Hartmetall-Wendeschneidplatten mit eingesinterten Spanleitstufen (in German). Maschinenmarkt 82(1):884–886Google Scholar
  12. 12.
    Zhou L (2001) Machining chip-breaking prediction with grooved inserts in steel turning. Dissertation, Worcester Polytechnic InstituteGoogle Scholar
  13. 13.
    Jawahir IS (1990) On the controllability of chip breaking cycles and modes of chip breaking in metal machining. CIRP J Manuf Sci Technol 39(1):47–51. doi: 10.1016/S0007-8506(07)61000-2 CrossRefGoogle Scholar
  14. 14.
    Nedeß C, Hintze W, van Luttervelt C (1989) Characteristic parameters of chip control in turning operations with indexable inserts and three-dimensionally shaped chip formers. CIRP J Manuf Sci Technol 38(1):75–79. doi: 10.1016/S0007-8506(07)62655-9 CrossRefGoogle Scholar
  15. 15.
    Hintze W (1990) Modellgestütze Spanbruchbeurteilung beim Drehen (in German). Dissertation, Hamburg University of TechnologyGoogle Scholar
  16. 16.
    Balaji A, Sreeram G, Jawahir IS, Lenz E (1999) The effects of cutting tool thermal conductivity on tool-chip contact length and cyclic chip formation in machining with grooved tools. CIRP Ann 48(1):33–38. doi: 10.1016/S0007-8506(07)63126-6 CrossRefGoogle Scholar
  17. 17.
    Friedman M, Lenz E (1970) Investigation of the tool-chip contact length in metal cutting. Int J Mach Tool Des Res 10(4):401–416. doi: 10.1016/0020-7357(70)90001-6 CrossRefGoogle Scholar
  18. 18.
    Nakayama K (1962) Chip curl in metal cutting process. Bulletin of the faculty of engineering, Yokohama National University 11Google Scholar
  19. 19.
    Rahman M, Seah K, Li X, Zhang X (1995) A three-dimensional model of chip flow, chip curl and chip breaking under the concept of equivalent parameters. Int J Mach Tools Manuf 35(7):1015–1031. doi: 10.1016/0890-6955(94)00042-I CrossRefGoogle Scholar
  20. 20.
    Buchkremer S, Klocke F, Lung D (2014) Analytical study on the relationship between chip geometry and equivalent strain distribution on the free surface of chips in metal cutting. Int J Mech Sci 85:88–103. doi: 10.1016/j.ijmecsci.2014.05.005 CrossRefGoogle Scholar
  21. 21.
    Joshi S, Ramakrishnan N, Ramakrishnan P (1999) Analysis of chip breaking during orthogonal machining of Al/SiCp composites. J Mater Process Technol 88(1–3):90–96. doi: 10.1016/S0924-0136(98)00379-3 CrossRefGoogle Scholar
  22. 22.
    Zhang Y, Peklenik J (1980) Chip curl, chip breaking and chip control of the difficult-to-cut materials. CIRP J Manuf Sci Technol 29(1):79–83. doi: 10.1016/S0007-8506(07)61299-2 CrossRefGoogle Scholar
  23. 23.
    Essig C (2010) Prediction of chip breakage in machining processes with geometrically defined cutting edges by damage mechanical approaches (in German). Dissertation, RWTH Aachen UniversityGoogle Scholar
  24. 24.
    Athavale SM, Strenkowski JS (1997) Material damage-based model for predicting chip-breakability. J Manuf Sci Eng 119(4B):675–680. doi: 10.1115/1.2836808 CrossRefGoogle Scholar
  25. 25.
    Rice JR, Tracey DM (1969) On the ductile enlargement of voids in triaxial stress fields. J Mech Phys Solids 17(3):201–217. doi: 10.1016/0022-5096(69)90033-7 CrossRefGoogle Scholar
  26. 26.
    Johnson GR, Cook WH (1985) Fracture characteristics of three metals subjected to various strains, strain rates, temperatures and pressures. Eng Fract Mech 21(1):31–48. doi: 10.1016/0013-7944(85)90052-9 CrossRefGoogle Scholar
  27. 27.
    Abushawashi Y, Xiao X, Astakhov VP (2011) Modeling of serrated chip formation with a fracture locus approach. Proc ASME 2011 Int Mech Eng Congr Expo IMECE. pp. 373–384. doi: 10.1115/IMECE2011-63918
  28. 28.
    Singh KN, Sievert R, Noack HD, Clos R, Schreppel U, Veit P, Hamann A, Klingbeil D (2003) Simulation of fracture under dynamic leading at different states of triaxiality for a nickel-base superalloy. J Phys IV 110:275–280. doi: 10.1051/jp4:20020706 Google Scholar
  29. 29.
    Sievert R, Noack H, Hamann A, Löwe P, Singh K, Künecke G, Clos R, Schreppel U, Veit P, Uhlmann E, Zettier R (2003) Simulation der Spansegmentierung beim Hochgeschwindigkeits-Zerpsanen unter Berücksichtigung duktiler Schädigung (in German). Tech Mech 23(2–4):216–233Google Scholar
  30. 30.
    Zhang X, Shivpuri R, Srivastava AK (2014) Stress triaxiality in chip segmentation during high speed machining of titanium alloy. Proceedings of the 2014 ASME International Manufacturing Science and Engineering ConferenceGoogle Scholar
  31. 31.
    Vaziri MR, Salimi M, Mashayekhi M (2010) A new calibration method for ductile fracture models as chip separation criteria in machining. Simul Model Pract 18(9):1286–1296. doi: 10.1016/j.simpat.2010.05.003 CrossRefGoogle Scholar
  32. 32.
    Bai Y, Wierzbicki T (2008) A new model of metal plasticity and fracture with pressure and Lode dependence. Int J Plast 24(6):1071–1096. doi: 10.1016/j.ijplas.2007.09.004 zbMATHCrossRefGoogle Scholar
  33. 33.
    Bai Y (2008) Effect of loading history on necking and fracture. Dissertation, Massachusetts Institute of TechnologyGoogle Scholar
  34. 34.
    Jaspers SPFC (1999) Metal cutting mechanics and material behaviour. Technische Universität EindhovenGoogle Scholar
  35. 35.
    Autenrieth H, Schulze V, Herzig N, Meyer LW (2009) Ductile fracture model for the description of AISI 1045 behavior under different loading conditions. Mech Time-Depend Mater 13(3):215–231. doi: 10.1007/s11043-009-9084-y CrossRefGoogle Scholar
  36. 36.
    Rohr I, Nahme H, Thoma K (2004) Charakterisierung des Schädigungsverhaltens von duktilem Stahl (in German). In: Pohl (ed) Proceedings der Tagung Werkstoffprüfung. Konstruktion, Qualitätssicherung und Schadensanalyse. MAT-INFO, Werkstoff-Informationsgesellschaft, Frankfurt, Germany. pp 143–148Google Scholar
  37. 37.
    Klocke F, Lung D, Veselovac D, Buchkremer S (2015) An analytical model of the temperature distribution in the chip breakage location of metal cutting operations. Procedia CIRP 31C:240–245. doi: 10.1016/j.procir.2015.03.090 CrossRefGoogle Scholar
  38. 38.
    Buchkremer S, Klocke F, Lung D (2015) Finite-element-analysis of the relationship between chip geometry and stress triaxiality distribution in the chip breakage location of metal cutting operations. Simul Model Pract Theory 55:10–26. doi: 10.1016/j.simpat.2015.03.009 CrossRefGoogle Scholar
  39. 39.
    Buchkremer S, Wu B, Lung D, Münstermann S, Klocke F, Bleck W (2014) FE-simulation of machining processes with a new material model. J Mater Process Technol 214(3):599–611. doi: 10.1016/j.jmatprotec.2013.10.014 CrossRefGoogle Scholar
  40. 40.
    Özel T, Zeren E (2006) A methodology to determine work material flow stress and tool-chip interfacial friction properties by using analysis of machining. J Manuf Sci Eng 128(1):119–129. doi: 10.1115/1.2118767 CrossRefGoogle Scholar
  41. 41.
    Shatla M, Kerk C, Altan T (2001) Process modeling in machining. Part 1: determination of flow stress data. Int J Mach Tool Manuf 41:1511–1534. doi: 10.1016/S0890-6955(01)00016-5 CrossRefGoogle Scholar
  42. 42.
    Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. Proc 7th Int Symp Ballistics 21:541–547Google Scholar
  43. 43.
    Klocke F, Lung D, Buchkremer S (2013) Inverse identification of the constitutive equation of Inconel 718 and AISI 1045 from FE machining simulations. Procedia CIRP 8:212–217. doi: 10.1016/j.procir.2013.06.091 CrossRefGoogle Scholar
  44. 44.
    Spittel M, Spittel T (2009) Steel symbol/number: C45/1.0503. In: Martienssen W, Warlimont H (eds) Metal forming data of ferrous alloys—deformation behavior. Springer, Berlin, pp 210–215CrossRefGoogle Scholar
  45. 45.
    Spriggs GE (2002) Properties of hardmetals and cermets. In: Beiss P, Ruthardt R, Warlimont H (eds) Powder metallurgy data. Refractory, hard and intermetallic materials. Springer, Berlin, pp 86–117CrossRefGoogle Scholar
  46. 46.
    Zorev N (1963) Inter-relationship between shear processes occurring along tool face and shear plane in metal cutting. International Research in Production Engineering, ASME, New York, pp 42–49Google Scholar
  47. 47.
    Puls H, Klocke F, Lung D (2012) A new experimental methodology to analyse the friction behaviour at the tool-chip interface in metal cutting. Prod Eng 6(4–5):349–354. doi: 10.1007/s11740-012-0386-6 CrossRefGoogle Scholar
  48. 48.
    Astakhov VP (2006) Tribology in metal cutting. Elsevier Ltd., AmsterdamGoogle Scholar
  49. 49.
    Bao Y, Wierzbicki T (2005) On the cut-off value of negative triaxiality for fracture. Eng Fract Mech 72(7):1049–1069. doi: 10.1016/j.engfracmech.2004.07.011 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen UniversityAachenGermany

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