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Predictive cutting force model for a cryogenic machining process incorporating the phase transformation of Ti-6Al-4V

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Abstract

Titanium alloys have been attracting interest in aerospace industries because of their high strength-to-weight ratio. However, they are classified as difficult-to-machine materials due to poor tool life in machining processes. Cryogenic machining is a process that uses liquid nitrogen (LN2) as a coolant, and proposed as a method to enhance tool life in the present study. This paper presents a theoretical study to develop a predictive cutting force model for cryogenic machining of Ti-6Al-4V. A modified (in terms of cutting temperature) Johnson-Cook model that considers phase transformation, and a friction coefficient were used as input parameters for inclusion of the cryogenic cooling effect. The predictive cutting force model was validated based on an orthogonal cutting test. The predicted forces showed good agreement with the experimental data, with minimum and maximum error magnitudes of 1.9 and 17.7% for cutting force, and 0.3 and 32.8% for thrust force, respectively. Investigation of the effects of cryogenic cooling on the cutting force, micro-structure, surface integrity and burr height were conducted. The cutting force during cryogenic machining was increased compared to dry machining by a martensitic phase transformation of the work material. There was no effect of cooling condition on the surface roughness. The burr height under cryogenic conditions was decreased by 56.2 and 28.2% compared to the dry and wet conditions, respectively.

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References

  1. Castellani C, Lindtner RA, Hausbrandt P, Tschegg E, Stanzl-Tschegg SE, Zanoni G, Beck S, Weinberg AM (2011) Bone–implant interface strength and osseointegration: biodegradable magnesium alloy versus standard titanium control. Acta Biomater 7(1):432–440. https://doi.org/10.1016/j.actbio.2010.08.020

    Article  Google Scholar 

  2. Long M, Rack H (1998) Titanium alloys in total joint replacement—a materials science perspective. Biomaterials 19(18):1621–1639. https://doi.org/10.1016/S0142-9612(97)00146-4

    Article  Google Scholar 

  3. Che-Haron C (2001) Tool life and surface integrity in turning titanium alloy. J Mater Process Technol 118(1-3):231–237. https://doi.org/10.1016/S0924-0136(01)00926-8

    Article  Google Scholar 

  4. Shokrani A, Dhokia V, Newman ST (2012) Environmentally conscious machining of difficult-to-machine materials with regard to cutting fluids. Int J Mach Tools Manuf 57:83–101

    Article  Google Scholar 

  5. Hong SY, Ding Y (2001) Cooling approaches and cutting temperatures in cryogenic machining of Ti-6Al-4V. Int J Mach Tools Manuf 41(10):1417–1437. https://doi.org/10.1016/S0890-6955(01)00026-8

    Article  Google Scholar 

  6. Hong SY, Markus I, Jeong WC (2001) New cooling approach and tool life improvement in cryogenic machining of titanium alloy Ti-6Al-4V. Int J Mach Tools Manuf 41:2245–2260

    Article  Google Scholar 

  7. Hong SY, Ding Y, Jeong WC (2001) Friction and cutting forces in cryogenic machining of Ti–6Al–4V. Int J Mach Tools Manuf 41:2271–2285

    Article  Google Scholar 

  8. Sha W, Malinov S (2009) Titanium alloys: modelling of microstructure, properties and applications, Elsevier

  9. Malinov S, Guo Z, Sha W, Wilson A (2001) Differential scanning calorimetry study and computer modeling of β⇒ α phase transformation in a Ti-6Al-4V alloy. Metall Mater Trans A 32(4):879–887. https://doi.org/10.1007/s11661-001-0345-x

    Article  Google Scholar 

  10. Kherrouba N, Bouabdallah M, Badji R, Carron D, Amir M (2016) Beta to alpha transformation kinetics and microstructure of Ti-6Al-4V alloy during continuous cooling. Mater Chem Phys 181:462–469

    Article  Google Scholar 

  11. Ahmed T, Rack H (1998) Phase transformations during cooling in α+ β titanium alloys. Mater Sci Eng A 243(1-2):206–211. https://doi.org/10.1016/S0921-5093(97)00802-2

    Article  Google Scholar 

  12. Jovanović M, Tadić S, Zec S, Mišković Z, Bobić I (2006) The effect of annealing temperatures and cooling rates on microstructure and mechanical properties of investment cast Ti–6Al–4V alloy. Mater Des 27(3):192–199. https://doi.org/10.1016/j.matdes.2004.10.017

    Article  Google Scholar 

  13. Bermingham M, Kirsch J, Sun S, Palanisamy S, Dargusch M (2011) New observations on tool life, cutting forces and chip morphology in cryogenic machining Ti-6Al-4V. Int J Mach Tools Manuf 51:500–511

    Article  Google Scholar 

  14. Outeiro J, Rossi F, Fromentin G, Poulachon G, Germain G, Batista A (2013) Process mechanics and surface integrity induced by dry and cryogenic machining of AZ31B-O magnesium alloy. Procedia CIRP 8:487–492. https://doi.org/10.1016/j.procir.2013.06.138

    Article  Google Scholar 

  15. Rotella G, Umbrello D (2014) Numerical simulation of surface modification in dry and cryogenic machining of AA7075 alloy. Procedia CIRP 13:327–332. https://doi.org/10.1016/j.procir.2014.04.055

    Article  Google Scholar 

  16. Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. Proceedings of the 7th international symposium on ballistics, Netherlands. 541-547

  17. Lesuer D (1999) Experimental investigation of material models for Ti-6Al-4V and 2024-T3. Livermore: University of California, Lawrence Livermore National Laboratory 1–36

  18. Nemat-Nasser S, Guo WG, Nesterenko VF, Indrakanti S, Gu YB (2001) Dynamic response of conventional and hot isostatically pressed Ti–6Al–4V alloys: experiments and modeling. Mech Mater 33(8):425–439. https://doi.org/10.1016/S0167-6636(01)00063-1

    Article  Google Scholar 

  19. Johnson G, Holmquist T (1989) Test data and computational strength and fracture model constants for 23 materials subjected to large strains, high strain rates, and high temperatures. Los Alamos National Laboratory, Los Alamos, NM, report no. LA-11463-MS

  20. Shen N, Ding H, Gao J (2015) Cryogenic cutting of AZ31B-O Mg alloy for improved surface integrity–part II: physics-based process modeling of surface microstructural alteration. Proc of ASME 2015 International Manufacturing Science and Engineering Conference

  21. Bajpai V, Lee I, Park HW (2014) Finite element modeling of three-dimensional milling process of Ti–6Al–4V. Mater Manuf Process 29(5):564–571. https://doi.org/10.1080/10426914.2014.892618

    Article  Google Scholar 

  22. Vyas A, Shaw M (1999) Mechanics of saw-tooth chip formation in metal cutting. J Manuf Sci Eng Trans ASME 121(2):163–172. https://doi.org/10.1115/1.2831200

    Article  Google Scholar 

  23. Stephenson D, Agapiou J (2005) Metal cutting theory and practice. Taylor & Francis, New York

    Google Scholar 

  24. Kim DM, Lee I, Kim SK, Kim BH, Park HW (2016) Influence of a micropatterned insert on characteristics of the tool–workpiece interface in a hard turning process. J Mater Process Technol 229:160–171. https://doi.org/10.1016/j.jmatprotec.2015.09.018

    Article  Google Scholar 

  25. Seo S, Min O, Yang H (2005) Constitutive equation for Ti–6Al–4V at high temperatures measured using the SHPB technique. Int J Impac Eng 31:735–754

    Article  Google Scholar 

  26. Johnson WA (1939) Reaction kinetics in process of nucleation and growth. Trans AIME 135:416–458

    Google Scholar 

  27. Malinov S, Markovsky P, Sha W, Guo Z (2001) Resistivity study and computer modelling of the isothermal transformation kinetics of Ti–6Al–4V and Ti–6Al–2Sn–4Zr–2Mo–0.08 Si alloys. J Alloys Compd 314(1-2):181–192. https://doi.org/10.1016/S0925-8388(00)01227-5

    Article  Google Scholar 

  28. Mur FG, Rodriguez D, Planell J (1996) Influence of tempering temperature and time on the α′-Ti-6Al-4V martensite. J Alloys Compd 234:287–289

    Article  Google Scholar 

  29. Baldissera P, Delprete C (2009) Effects of deep cryogenic treatment on static mechanical properties of 18NiCrMo5 carburized steel. Mater Des 30(5):1435–1440. https://doi.org/10.1016/j.matdes.2008.08.015

    Article  Google Scholar 

  30. Yan D, Hilditch T, Kishawy H, Littlefair G (2013) On quantifying the strain rate during chip formation when machining aerospace alloy Ti-5553. Procedia CIRP 8:123–128. https://doi.org/10.1016/j.procir.2013.06.076

    Article  Google Scholar 

  31. Filip R, Kubiak K, Ziaja W, Sieniawski J (2003) The effect of microstructure on the mechanical properties of two-phase titanium alloys. J Mater Process Technol 133(1-2):84–89. https://doi.org/10.1016/S0924-0136(02)00248-0

    Article  Google Scholar 

  32. Oxley PLB, Young HT (1990) The mechanics of machining: an analytical approach to assessing machinability. Ellis Horwood Publisher, Chichester

    Google Scholar 

  33. Waldorf DJ, DeVor RE, Kapoor SG (1998) A slip-line field for ploughing during orthogonal cutting. J Manuf Sci Eng 120(4):693–699. https://doi.org/10.1115/1.2830208

    Article  Google Scholar 

  34. Shaw M, Vyas A (1993) Chip formation in the machining of hardened steel. CIRP ANN-Manuf Technol 42(1):29–33. https://doi.org/10.1016/S0007-8506(07)62385-3

    Article  Google Scholar 

  35. Wang B, Liu Z (2014) Investigations on the chip formation mechanism and shear localization sensitivity of high-speed machining Ti6Al4V. Int J Adv Manuf Technol 75(5-8):1065–1076. https://doi.org/10.1007/s00170-014-6191-y

    Article  Google Scholar 

  36. Hua J, Shivpuri R (2004) Prediction of chip morphology and segmentation during the machining of titanium alloys. J Mater Process Technol 150(1-2):124–133. https://doi.org/10.1016/j.jmatprotec.2004.01.028

    Article  Google Scholar 

  37. Yildiz Y, Nalbant M (2008) A review of cryogenic cooling in machining processes. Int J Mach Tools Manuf 48(9):947–964. https://doi.org/10.1016/j.ijmachtools.2008.01.008

    Article  Google Scholar 

  38. Özel T, Karpat Y (2005) Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks. Int J Mach Tools Manuf 45(4-5):467–479. https://doi.org/10.1016/j.ijmachtools.2004.09.007

    Article  Google Scholar 

  39. Nakayama K, Arai M (1987) Burr formation in metal cutting. CIRP ANN-Manuf Technol 36(1):33–36. https://doi.org/10.1016/S0007-8506(07)62547-5

    Article  Google Scholar 

  40. Gaitonde V, Karnik S, Achyutha B, Siddeswarappa B (2008) Genetic algorithm-based burr size minimization in drilling of AISI 316L stainless steel. J Mater Process Technol 197(1-3):225–236. https://doi.org/10.1016/j.jmatprotec.2007.06.029

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the development of liquid nitrogen-based cryogenic machining technology and system for titanium and CGI machining funded by the Ministry of Trade, Industry & Energy (MOTIE) of Korea (No. 10048871) and the National Research Foundation of Korea (NRF) Grant funded by the Ministry of Science and ICT (NRF-2017R1A5A1015311).

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Correspondence to Hyung Wook Park.

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Research highlights

We developed the predictive model of cryogenic machining with the phase transformation.

Experimental validations of FEM simulation and cutting forces were performed.

Martensitic phase transformation increases cutting forces at high cutting speed.

Cryogenic machining can improve the productivity by decreasing the burr height.

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Kim, D.Y., Kim, D.M. & Park, H.W. Predictive cutting force model for a cryogenic machining process incorporating the phase transformation of Ti-6Al-4V. Int J Adv Manuf Technol 96, 1293–1304 (2018). https://doi.org/10.1007/s00170-018-1606-9

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