Modeling of Face Milling Operation for Assessing Cutter Trajectory and Cutting Forces

  • Mintu Karmakar
  • Santanu DasEmail author
Original Contribution


Simulation is essential to help designing a cutting tool or selection of a milling cutter. This paper presents an approach of detailed modeling of face milling operation. Theoretical cutter trajectory has been considered. Cutting force components and cutting power consumption of face milling for linear path of cutter have also been modeled. An algorithm for this purpose has been evolved in this work. Validation of angle relationship previously investigated in machining has been shown. Detail plots of dynamic rake angle, instantaneous feed, cutting force components, cutting power with respect to time are established theoretically. Some relevant data have been assumed like material property, cutting tool nomenclature, etc., for showing graphical presentations. Simulation results obtained in this work have been compared with the experimental data available in a published literature. Simulated results from the proposed model using Oxley angle relationship are found to be quite close to the experimental results already reported.


Face milling Machining Modeling Tool path Trajectory Force 



  1. 1.
    G. Albert, R. Laheurte, J.Y. K’Nevez, P. Darnis, O. Cahuc, Experimental milling moment model in orthogonal cutting condition: to an accurate energy balance. Int. J. Adv. Manuf. Technol. 55, 843–854 (2011)CrossRefGoogle Scholar
  2. 2.
    S.B. Raja, N. Baskar, Optimization techniques for machining operations: a retrospective research based on various mathematical models. Int. J. Adv. Manuf. Technol. 48, 1075–1090 (2010)CrossRefGoogle Scholar
  3. 3.
    W. Baohai, Y. Xue, L. Ming, G. Ge, Cutting force prediction for circular end milling process. Chin. J. Aeronaut. 26(4), 1057–1063 (2013)CrossRefGoogle Scholar
  4. 4.
    O.E.E.K. Omar, T.E. Wardany, E. Ng, M.A. Elbestawi, An improved cutting force and surface topography prediction model in end milling. Int. J. Mach. Tools Manuf 47, 1263–1275 (2007)CrossRefGoogle Scholar
  5. 5.
    M. Randovanovic, Determination of theoretical roughness profile height by peripheral milling. The analsdunarea de jos university of galati 5, 32–35 (2002)Google Scholar
  6. 6.
    A. Richetti, A.R. Machado, M.B. Da Silva, E.O. Ezugwu, J. Bonney, Influence of the number of inserts for tool life evaluation in face milling of steels. Int. J. Mach. Tools Manuf 44, 695–700 (2004)CrossRefGoogle Scholar
  7. 7.
    H.Z. Li, K. Liu, X.P. Li, A new method for determining the undeformed chip thickness in milling. J. Mater. Process. Technol. 113, 378–384 (2001)CrossRefGoogle Scholar
  8. 8.
    I.G. Euanac, E. Ozturkb, N.D. Sims, Modellingstatic and dynamic cutting forces and vibrations for inserted ceramic milling tools. Procedia CIRP 8, 564–569 (2013)CrossRefGoogle Scholar
  9. 9.
    H. Perez, J. Rios, E. Dıez, A. Vizan, Increase of material removal rate in peripheral milling by varying feed rate. J. Mater. Process. Technol. 201, 486–490 (2008)CrossRefGoogle Scholar
  10. 10.
    A.B. Chattopadhyay, Machining and Machine Tool (Wiley, Hoboken, 2011), pp. 91–137Google Scholar
  11. 11.
    A. Bhattacharyya, Metal Cutting Theory and Practice (Central Book Publishers, Baruipur, 1984), p. 339Google Scholar
  12. 12.
    R. Autay, M. Kchaou, F. Dammak, Friction and wear behavior of induction hardened ISO 42CrMo4 low-alloy steel under reciprocating sliding conditions. J. Eng. Tribol. 229(2), 115–125 (2015)Google Scholar

Copyright information

© The Institution of Engineers (India) 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringKalyani Government Engineering CollegeKalyaniIndia

Personalised recommendations