Skip to main content
SpringerLink
Log in

Dynamic simulation of milling operations with small diameter milling cutters: effect of material heterogeneity on the cutting force model

  • Published:
Meccanica Aims and scope Submit manuscript

Abstract

Simulation of manufacturing processes (also called virtual manufacturing) is an important research topic in order to optimize the added value of the manufacturing chain. The mastering of these techniques allows companies to remain competitive on the market. Machining operations are very complex to simulate numerically due to the severe conditions undergone by the material (high strain, very high strain rates, high temperature,...). In addition, the rising need of micro-manufacturing techniques creates new challenges in numerical simulation. Indeed, some physical phenomena neglected for traditional machining simulation need to be taken into account for accurate simulation when the feedrate is fairly low (size effect, minimum chip thickness, material heterogeneity,...). New developments are thus needed to unlock the full benefits of these techniques. The aim of this paper is to enhance the classical mechanistic cutting force model for milling operations with small diameter tool by considering the effect of the heterogeneity of the material. The variability of the response during a test on fixed conditions (cutting tool, machined material and cutting parameters) is taken into account to develop a model whose parameters can evolve during a given operation. The statistical dispersion of cutting forces observed during experimental test is measured and modeled as a random perturbation of the force. The effects of this perturbation on the stability of milling operations are then demonstrated by means of numerical simulation.

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

Similar content being viewed by others

References

  1. Chae J, Park S, Freiheit T (2006) Investigation of micro-cutting operations. Int J Mach Tools Manuf 45:313–332

    Article  Google Scholar 

  2. Dornfeld D, Min S, Takeuchi Y (2006) Recent advances in mechanical micromachining. Ann CIRP 55:745–768

    Article  Google Scholar 

  3. Liu X, DeVor R, Kapoor S, Ehman K (2004) The mechanics of machining at the micro scale: assessment of the current state of the science. J Manuf Sci Eng 126:666–678

    Article  Google Scholar 

  4. Camara MA, Campos Rubio JC, Abrao AM, Davim JP (2012) State of the art on micromilling of materials, a review. J Mater Sci Technol 28(8):673–685

    Article  Google Scholar 

  5. Weule H, Huntrup V, Trischler H (2001) Micro-cutting of steel to meet new requirements in miniaturization. Ann CIRP 50:61–64

    Article  Google Scholar 

  6. Ducobu F, Rivière-Lorphèvre E, Filippi E (2011) A lagrangian fem model to produce saw-toothed macro-chip and to study the depth of cut influence on its formation in orthogonal cutting of ti6al4v. Adv Mater Res 223:1–11

    Article  Google Scholar 

  7. de Oliveira FB, Rodriguez AR, Coelho RT, de Souza AF (2015) Size effect and minimum chip thickness in micromilling. Int J Mach Tools Manuf 89:39–54

    Article  Google Scholar 

  8. Ljustina G, Larsson R, Mn Fagerstrom (2014) A fe based machining simulation methodology accounting for cast iron microstructure. Finite Elem Anal Des 80:1–10

    Article  Google Scholar 

  9. Simoneau A, Ng E, Elbestawi MA (2006) The effect of microstructure on chip formation and surface defects in micro-scale, mesoscale, and macroscale cutting of steel. Ann CIRP 55:97–102

    Article  Google Scholar 

  10. Altan T, Vazquez V (1997) Numerical process simulation for tool and process design in bulk metal forming (keynote paper). Ann CIRP 45(2):599–615

    Article  Google Scholar 

  11. Brecher C, Esser M, Witt S (2009) Interaction of manufacturing process and machine tool. CIRP Ann Manuf Technol 58:588–607

    Article  Google Scholar 

  12. Thepsonthi T, Özel T (2012) Multi-objective process optimization for micro-end milling of ti-6al- 4v titanium alloy. Int J Adv Manuf Technol 63:903–914

    Article  Google Scholar 

  13. Thepsonthi T, Özel T (2013) Experimental and finite element simulation based investigations on micro-milling ti-6al-4v titanium alloy: effects of cbn coating on tool wear. J Mater Process Technol 213:532–542

    Article  Google Scholar 

  14. Pratap T, Patra K, Dyakonov AA (2015) Modeling cutting force in micro-milling of ti-6al-4v titanium alloy. Proc Eng 129:134–139

    Article  Google Scholar 

  15. Rivière-Lorphèvre E, Letot C, Ducobu F, Filippi E (2015) Uncertainty management of cutting forces parameters and its effects on machining stability. Key Eng Mater 651–653:1165–1170

    Article  Google Scholar 

  16. Attanasio A, Ceretti E, Rizzuti S, Umbrello D, Micari F (2008) 3d Finite element analysis of tool wear in machining. CIRP Ann Manuf Technol 57:61–64

    Article  Google Scholar 

  17. Axinte DA, Dewes RC (2002) Tool wear and workpiece surface integrity when high speed ball nose end milling hardened AISI h13. In: Metal cutting and high speed machining. Kluwer Academic/ Plenum publishers, pp 171–179

  18. Denkena B, Hollman F (2013) Process machine interactions: prediction and manipulation of interactions between manufacturing processes and machine tool structure. Springer lecture notes in production engineering

  19. Altintas Y (2000) Manufacturing automation, metal cutting. Cambridge university press, New York

    Google Scholar 

  20. Rivière-Lorphèvre E, Filippi E (2009) Mechanistic cutting force model parameters evaluation in milling taking cutter radial runout into account. Int J Adv Manuf Technol 45(8):8–15

    Article  Google Scholar 

  21. Engin S, Altintas Y (2001) Mechanics and dynamics of general milling cutters. Part I. Int J Mach Tools Manuf 41:2195–2212

    Article  Google Scholar 

  22. Kline WA, DeVor RE, Lindberg JR (1982) The prediction of cutting forces in end milling with application to cornering cuts. Int J Mach Tool Des Res 22:7–22

    Article  Google Scholar 

  23. Budak E, Altinta Y, Armarego EJA (1996) Prediction of milling force coefficients from orthogonal cutting data. ASME J Manuf Sci Eng 118:216–224

    Article  Google Scholar 

  24. Ko JH, Cho DW (2005) Detremination of cutting-condition-independent coefficients and runout parameters in ball-end milling. Int J Adv Manuf Technol 26:1211–1221

    Article  Google Scholar 

  25. Sun S, Brandt M, Dargusch M (2009) Characteristics of cutting forces and chip formation in machining of titanium alloys. Int J Mach Tools Manuf 49:561–568

    Article  Google Scholar 

  26. Ducobu F, Rivière-Lorphèvre E, Filippi E (2014) Numerical contribution to the comprehension of saw-toothed ti-6al-4v chip formation in orthogonal cutting. Int J Mech Sci 81:77–87

    Article  Google Scholar 

  27. Rivière-Lorphèvre E, Filippi E, Dehombreux P (2011) Experimental investigation of parameter-dependent analytical cutting force models for the simulation of the milling process. In: Proceeding of ESAFORM2011

  28. Schmitz TL, Karandikar J, Kim NH, Abbas A (2011) Uncertainty in machining: workshop summary and contributions. J Manuf Sci Eng 133(5):051009

    Article  Google Scholar 

  29. Duncan GS, Kurdi M, Schmitz T (2005) Stability lobe uncertainty. In: Proceedings of American society for precision engineering annual meeting

  30. Wasserman G (2002) Reliability verification, testing and analysis in engineering design. CRC Press, Boca Raton

    Book  Google Scholar 

  31. Afazov SM, Ratchev SM, Segal J, Popov AA (2012) Chatter modelling in micro-milling by considering process nonlinearities. Int J Mach Tools Manuf 56:28–38

    Article  Google Scholar 

  32. Altintas Y, Budak E (1995) Analytical prediction of stability lobes in milling. Ann CIRP 44:357–362

    Article  Google Scholar 

  33. Insperger T, Mann BP, Stepan G, Bayly PV (2003) Stability of up-milling and down-milling, part 1: alternative analytical methods. Int J Mach Tools Manuf 43:25–34

    Article  Google Scholar 

  34. Campomanes ML, Altintas Y (2003) An improved time domain simulation for dynamic milling at small radial immersion. Trans ASME 125:416–422

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge competence center ‘Technocampus’ in Gosselies (Belgium) for their help during the experimental tests and the provision of their machine tools.

Author information

Authors and Affiliations

  1. Machine Design and Production Engineering Laboratory, Faculty of Engineering (FPMs), University of Mons (UMONS), 20 Place du Parc, 7000, Mons, Belgium

    Edouard Rivière-Lorphèvre, Christophe Letot, François Ducobu, Pierre Dehombreux & Enrico Filippi

Authors
  1. Edouard Rivière-Lorphèvre
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christophe Letot
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. François Ducobu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pierre Dehombreux
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Enrico Filippi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Edouard Rivière-Lorphèvre.

Appendix: complete results

Appendix: complete results

See Table 1.

Table 1 Summary of the results obtained with all experimental tests
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rivière-Lorphèvre, E., Letot, C., Ducobu, F. et al. Dynamic simulation of milling operations with small diameter milling cutters: effect of material heterogeneity on the cutting force model. Meccanica 52, 35–44 (2017). https://doi.org/10.1007/s11012-016-0398-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11012-016-0398-y

Keywords

Search

Navigation