Skip to main content

Advertisement

SpringerLink
Log in

Effects of tailored residual stress on micro-end milling: numerical modelling and validation

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Precision components often require micro-milling, where burrs may occur as surface defects. Such defects are likely to be influenced by the stress state in the raw material prior to micro-milling. A pre-treatment on the surface is found to compensate for the formation of burrs and improve the finishing of the micro-milled component. A finite element model of the micro-milling process was developed in Abaqus. An enhanced flow algorithm based on strain gradient and dynamic recrystallization was used, along with a tool/workpiece friction model. This study revealed that compressive residual stress of about 613 MPa in Ti-6Al-4V can lower burr formation by up to 60%, cutting temperatures by 7% and contact forces by 15%. Additionally, surface residual stresses induced by micro-milling are predicted for compressively pre-stressed and as-received samples. The mechanism of burr formation, cutting forces and cut marks on the sidewall surface was reported. The simulated burr morphology, chip contact length, cutting forces and surface residual stresses after micro-milling were verified with experimental results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24

Similar content being viewed by others

Abbreviations

a p :

Axial depth of cut

A :

Yield strength constant

B :

Strain-dependent strength constant

C :

Strain hardening constant

D :

Damage evolution constant

D t :

Tool diameter

E :

Young’s modulus

f i :

Instantaneous chip thickness

ε, ε p, \({\varepsilon}_e^{pl}\) :

True, plastic strain, equivalent plastic strain

ε i, ε f, ε xy :

Initial, failure, shear strain

\(\dot{\varepsilon}\), \({\dot{\varepsilon}}_0\) :

True, reference strain rate

ε cr :

Critical strain

F x, y, z :

Transverse, feed, thrust force

γ, γ crit :

Elastic slip, critical elastic slip

ƺ :

Volume fraction of recrystallization

ρ w :

Density of workpiece

h burr :

Burr height

V c :

Cutting speed

r e :

Edge radius

k :

Material parameter

L :

Mesh element size

m :

Thermal softening exponent

μ s, μ k :

Static and kinematic coefficient of friction

n :

Strain hardening exponent

N :

Spindle speed

σ :

Flow stress

p, p s :

Normal, hydrostatic stress

σ v :

von Mises equivalent stress

σ y :

Yield strength

τ m,τ f :

Maximum and contact shear stress

T :

Machining temperature

T 0, T m :

Ambient, melting temperature

Q :

Activation energy

R :

Universal gas constants

u f :

Displacement at failure

Θ :

Shear stress ratio

V c :

Cutting velocity

W burr :

Burr width

ω :

Damage initiation parameter

ω 0 :

Angular frequency

η SGE :

Strain gradient constant

References

  1. Filiz S, Conley CM, Wasserman MB, Ozdoganlar OB (2007) An experimental investigation of micro-machinability of copper 101 using tungsten carbide micro-endmills. Int J Mach Tools Manuf 47:1088–1100. https://doi.org/10.1016/j.ijmachtools.2006.09.024

    Article  Google Scholar 

  2. Chae J, Park SS, Freiheit T (2006) Investigation of micro-cutting operations. Int J Mach Tools Manuf 46:313–332. https://doi.org/10.1016/j.ijmachtools.2005.05.015

    Article  Google Scholar 

  3. Kang YH, Zheng CM (2012) Fourier analysis for micro-end-milling mechanics. Int J Mech Sci 65:105–114. https://doi.org/10.1016/j.ijmecsci.2012.09.008

    Article  Google Scholar 

  4. Jing X, Lv R, Chen Y, Tian Y, Li H (2020) Modelling and experimental analysis of the effects of run out, minimum chip thickness and elastic recovery on the cutting force in micro-end-milling. Int J Mech Sci 176:105540. https://doi.org/10.1016/j.ijmecsci.2020.105540

    Article  Google Scholar 

  5. Sahoo P, Pratap T, Patra K (2019) A hybrid modelling approach towards prediction of cutting forces in micro end milling of Ti-6Al-4V titanium alloy. Int J Mech Sci 150:495–509. https://doi.org/10.1016/j.ijmecsci.2018.10.032

    Article  Google Scholar 

  6. De Oliveira FB, Rodrigues AR, Coelho RT, De Souza AF (2015) Size effect and minimum chip thickness in micromilling. Int J Mach Tools Manuf 89:39–54. https://doi.org/10.1016/j.ijmachtools.2014.11.001

    Article  Google Scholar 

  7. Chern GL (2006) Experimental observation and analysis of burr formation mechanisms in face milling of aluminum alloys. Int J Mach Tools Manuf 46:1517–1525. https://doi.org/10.1016/j.ijmachtools.2005.09.006

    Article  Google Scholar 

  8. Zhang X, Yu T, Wang W, Zhao J (2019) Improved analytical prediction of burr formation in micro end milling. Int J Mech Sci 151:461–470. https://doi.org/10.1016/j.ijmecsci.2018.12.005

    Article  Google Scholar 

  9. Chen MJ, Ni HB, Wang ZJ, Jiang Y (2012) Research on the modeling of burr formation process in micro-ball end milling operation on Ti-6Al-4V. Int J Adv Manuf Technol 62:901–912. https://doi.org/10.1007/s00170-011-3865-6

    Article  Google Scholar 

  10. Chen W, Teng X, Zheng L, Xie W, Huo D (2018) Burr reduction mechanism in vibration-assisted micro milling. Manuf Lett 16:6–9. https://doi.org/10.1016/j.mfglet.2018.02.015

    Article  Google Scholar 

  11. Zhang X, Chen N (2021) Study on the burr formation process in micro-milling of high aspect ratio structures. Int J Adv Manuf Technol 115:433–447

    Article  Google Scholar 

  12. Davoudinejad A, Parenti P, Annoni M (2017) 3D finite element prediction of chip flow, burr formation, and cutting forces in micro end-milling of aluminum 6061-T6. Front Mech Eng 12:203–214. https://doi.org/10.1007/s11465-017-0421-6

    Article  Google Scholar 

  13. Özel T, Olleak A, Thepsonthi T (2017) Micro milling of titanium alloy Ti-6Al-4V: 3-D finite element modeling for prediction of chip flow and burr formation. Prod Eng 11:435–444. https://doi.org/10.1007/s11740-017-0761-4

    Article  Google Scholar 

  14. Liang YC, Yang K, Bai QS, Chen JX, Wang B (2009) Modeling and experimental analysis of microburr formation considering tool edge radius and tool-tip breakage in microend milling. J Vac Sci Technol B Microelectron Nanom Struct 27:1531. https://doi.org/10.1116/1.3046147

    Article  Google Scholar 

  15. Yadav AK, Bajpai V, Singh NK, Singh RK (2017) FE modeling of burr size in high- speed micro-milling of Ti6Al4V. Precis Eng 49:287–292. https://doi.org/10.1016/j.precisioneng.2017.02.017

    Article  Google Scholar 

  16. Saha S, Deb S, Bandyopadhyay PP (2020) An analytical approach to assess the variation of lubricant supply to the cutting tool during MQL assisted high speed micromilling. J Mater Process Technol 285(February):116783. https://doi.org/10.1016/j.jmatprotec.2020.116783

    Article  Google Scholar 

  17. Fang B, Yuan Z, Li D, Gao L (2021) Effect of ultrasonic vibration on finished quality in ultrasonic vibration assisted micromilling of Inconel718. Chinese J Aeronaut 34(6):209–219. https://doi.org/10.1016/j.cja.2020.09.021

    Article  Google Scholar 

  18. Malayath G, Jayachandran KN, Sidpara AM, Deb S (2019) Experimental and theoretical investigation into simultaneous deburring of microchannel and cleaning of the cutting tool in micromilling. Proc Inst Mech Eng, Part B 233(7):1761–1771. https://doi.org/10.1177/0954405418798864

    Article  Google Scholar 

  19. Wu X, Li L, He N, Yao C, Zhao M (2016) Influence of the cutting edge radius and the material grain size on the cutting force in micro cutting. Precis Eng 45:359–364. https://doi.org/10.1016/j.precisioneng.2016.03.012

    Article  Google Scholar 

  20. Komatsu T, Musha Y, Yoshino T, Matsumura T (2015) Surface finish and affected layer in milling of fine crystal grained stainless steel. J Manuf Process 19:148–154. https://doi.org/10.1016/j.jmapro.2015.06.003

    Article  Google Scholar 

  21. Peng FY, Dong Q, Yan R, Zhou L, Zhan C (2016) Analytical modeling and experimental validation of residual stress in micro-end-milling. Int J Adv Manuf Technol 87:3411–3424. https://doi.org/10.1007/s00170-016-8697-y

    Article  Google Scholar 

  22. Rahul Y, Vipindas K, Mathew J (2021) Methodology for prediction of sub-surface residual stress in micro end milling of Ti-6Al-4V alloy. J Manuf Process 62(April 2020):600–612. https://doi.org/10.1016/j.jmapro.2020.12.031

    Article  Google Scholar 

  23. Zeng HH, Yan R, Peng FY, Zhou L, Deng B (2017) An investigation of residual stresses in micro-end-milling considering sequential cuts effect. Int J Adv Manuf Technol 91:3619–3634. https://doi.org/10.1007/s00170-017-0088-5

    Article  Google Scholar 

  24. Lazoglu I, Mamedov A (2016) Deformation of thin parts in micromilling. CIRP Ann - Manuf Technol 65:117–120. https://doi.org/10.1016/j.cirp.2016.04.077

    Article  Google Scholar 

  25. Fergani O, Lazoglu I, Mkaddem A, El Mansori M, Liang SY (2014) Analytical modeling of residual stress and the induced deflection of a milled thin plate. Int J Adv Manuf Technol 75:455–463. https://doi.org/10.1007/s00170-014-6146-3

    Article  Google Scholar 

  26. Ruitao P, Linfeng Z, Jiawei T, Xiuli F, Meiliang C (2021) Application of pre-stressed cutting to aviation alloy: the effect on residual stress and surface roughness. J Manuf Process 62:501–512. https://doi.org/10.1016/j.jmapro.2020.12.021

    Article  Google Scholar 

  27. Deng Y, Xiu S, Shi X, Sun C, Wang Y (2017) Study on the effect mechanisms of pre-stress on residual stress and surface roughness in PSHG. Int J Adv Manuf Technol 88:3243–3256. https://doi.org/10.1007/s00170-016-9033-2Ji

    Article  Google Scholar 

  28. Hadad M, Sadeghi B (2012) Thermal analysis of minimum quantity lubrication-MQL grinding process. Int J Mach Tools Manuf 63:1–15. https://doi.org/10.1016/j.ijmachtools.2012.07.003

    Article  Google Scholar 

  29. Lu X, Lin X, Chiumenti M, Cervera M, Hu Y, Ji X, Ma L, Yang H, Huang W (2019) Residual stress and distortion of rectangular and S-shaped Ti-6Al-4V parts by directed energy deposition: modelling and experimental calibration. Addit Manuf 26:166–179. https://doi.org/10.1016/j.addma.2019.02.001

    Article  Google Scholar 

  30. Yadav R, Chakladar ND, Paul S (2022) A dynamic recrystallization based constitutive flow model for micro-machining of Ti-6Al-4V. J Manuf Process 77:463–484. https://doi.org/10.1016/j.jmapro.2022.03.040

    Article  Google Scholar 

  31. Arisoy YM, Özel T (2015) Prediction of machining induced microstructure in Ti-6Al-4V alloy using 3-D FE-based simulations: effects of tool micro-geometry, coating and cutting conditions. J Mater Process Technol 220:1–26. https://doi.org/10.1016/j.jmatprotec.2014.11.002

    Article  Google Scholar 

  32. Joshi SS, Melkote SN (2004) An explanation for the size-effect in machining using strain gradient plasticity. J Manuf Sci Eng Trans ASME 126:679–684. https://doi.org/10.1115/1.1688375

    Article  Google Scholar 

  33. Lai X, Li H, Li C, Lin Z, Ni J (2008) Modelling and analysis of micro scale milling considering size effect, micro cutter edge radius and minimum chip thickness. Int J Mach Tools Manuf 48:1–14. https://doi.org/10.1016/j.ijmachtools.2007.08.011

    Article  Google Scholar 

  34. Mabrouki T, Courbon C, Zhang Y, Rech J, Nélias D, Asad M, Hamdi H, Belhadi S, Salvatore F (2016) Some insights on the modelling of chip formation and its morphology during metal cutting operations. Comptes Rendus Mecanique 344(4–5):335–354. https://doi.org/10.1016/j.crme.2016.02.003

    Article  Google Scholar 

  35. Yameogo D, Haddag B, Makich H, Nouari M (2019) A physical behavior model including dynamic recrystallization and damage mechanisms for cutting process simulation of the titanium alloy Ti-6Al-4V. Int J Adv Manuf Technol 100:333–347. https://doi.org/10.1007/s00170-018-2663-9

    Article  Google Scholar 

  36. Avrami M (1940) Kinetics of phase change. II Transformation-time relations for random distribution of nuclei. J Chem Phys 8(2):212–224. https://doi.org/10.1063/1.1750631

    Article  Google Scholar 

  37. Calamaz M, Coupard D, Girot F (2010) Numerical simulation of titanium alloy dry machining with a strain softening constitutive law. Mach Sci Technol 14:244–257. https://doi.org/10.1080/10910344.2010.500957

    Article  Google Scholar 

  38. Johnson GR, Cook WH (1983) A computational constitutive model and data for metals subjected to large strain, high strain rates and high pressures. In: The Seventh International Symposium on Ballistics, pp 541–547

    Google Scholar 

  39. 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 50:943–960. https://doi.org/10.1016/j.ijmachtools.2010.08.004

    Article  Google Scholar 

  40. Leseur D (1999) Experimental investigations of material models for Ti-6a1-4v and 2024-t3. Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States). https://doi.org/10.2172/11977

    Book  Google Scholar 

  41. Hooputra H, Gese H, Dell H, Werner H (2004) A comprehensive failure model for crashworthiness simulation of aluminium extrusions. Int J Crashworthiness 9:449–464. https://doi.org/10.1533/ijcr.2004.0289

    Article  Google Scholar 

  42. Harzallah M, Pottier T, Senatore J, Mousseigne M, Germain G, Landon Y (2017) Numerical and experimental investigations of Ti-6Al-4V chip generation and thermo-mechanical couplings in orthogonal cutting. Int J Mech Sci 134:189–202. https://doi.org/10.1016/j.ijmecsci.2017.10.017

    Article  Google Scholar 

  43. Yadav R, Chakladar ND, Paul S (2022) Micro-milling of Ti-6Al-4V with controlled burr formation. Int J Mech Sci 231:107582. https://doi.org/10.1016/j.ijmecsci.2022.107582

    Article  Google Scholar 

  44. Childs THC (2006) Friction modelling in metal cutting. Wear 260:310–318. https://doi.org/10.1016/j.wear.2005.01.052

    Article  Google Scholar 

  45. Chakladar ND, Mandal P, Potluri P (2014) Effects of inter-tow angle and tow size on carbon fibre friction. Compos Part A Appl Sci Manuf 65:115–124. https://doi.org/10.1016/j.compositesa.2014.06.002

    Article  Google Scholar 

  46. Ahmadi M, Karpat Y, Acar O, Kalay YE (2018) Microstructure effects on process outputs in micro-scale milling of heat-treated Ti6Al4V titanium alloys. J Mater Process Technol 252:333–347. https://doi.org/10.1016/j.jmatprotec.2017.09.042

    Article  Google Scholar 

  47. Xu X, Zhang J, Outeiro J, Xu B, Zhao W (2020) Multiscale simulation of grain refinement induced by dynamic recrystallization of Ti6Al4V alloy during high-speed machining. J Mater Process Technol 286:116834. https://doi.org/10.1016/j.jmatprotec.2020.116834

    Article  Google Scholar 

Download references

Funding

The authors acknowledge the financial support of this research by the Indian Institute of Technology Kharagpur doctoral scheme.

Author information

Authors and Affiliations

  1. Mechanical Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

    Rahul Yadav, Nilanjan Das Chakladar & Soumitra Paul

Authors
  1. Rahul Yadav
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nilanjan Das Chakladar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Soumitra Paul
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Rahul Yadav: conceptualization, methodology, software, writing—original draft and visualisation

Nilanjan Das Chakladar: methodology, numerical model, supervision and writing—review and editing

Soumitra Paul: supervision, writing—review and editing and project administration

Corresponding author

Correspondence to Nilanjan Das Chakladar.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Fig. 25.

Fig. 25
figure 25

Algorithm of material flow and friction model used in proposed work

Full size image

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yadav, R., Chakladar, N.D. & Paul, S. Effects of tailored residual stress on micro-end milling: numerical modelling and validation. Int J Adv Manuf Technol 127, 5449–5470 (2023). https://doi.org/10.1007/s00170-023-11780-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-023-11780-9

Keywords

Search

Navigation