Optimization of Cutting Force for End Milling with the Direction of Cutter Rotation

엔드밀가공에서 커터회전방향에 따른 절삭력의 최적화

  • Choi, Man Sung (School of Mechatronics Engineering, Korea University of Technology and Education)
  • 최만성 (한국기술교육대학교 메카트로닉스공학부)
  • Received : 2017.06.16
  • Accepted : 2017.06.23
  • Published : 2017.06.30


This paper outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling when machining STS304 with TiAlN coated SKH59 tool under up and down end milling conditions. The end milling parameters evaluated are depth of cut, spindle speed and feed rate. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to analyze the effect of these end milling parameters. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. An orthogonal array of $L_9(33)$ was used. The most important input parameter for cutting force, however, is the feed rate, and depending on the cutter rotation direction. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.


Supported by : 한국기술교육대학교


  1. Parashar Vishal, Purohit Rajesh, "Investigation of the Effects of the Machining Parameters on Material Removal Rate using Taguchi method in End Milling of Steel Grade EN19," Materials Today: Proceedings 4, pp. 336-341, 2017. https://doi.org/10.1016/j.matpr.2017.01.030
  2. Masmiati, N., Sarhan, A.A.D., "Optimizing Cutting Parameters in Inclined End Milling for Minimum Surface Residual Stress - Taguchi Approach, Measurement Vol. 60, pp. 267-275, 2015. https://doi.org/10.1016/j.measurement.2014.10.002
  3. Moufki. A., Coz, G. Le, Dudzinski. D., "End-Milling of Inconel 718 Superalloy - An Analytical Modelling," Procedia CIRP Vol. 58, pp. 358 - 363, 2017. https://doi.org/10.1016/j.procir.2017.03.330
  4. Tsai, Y.H., Chen, J.C., Lou, S.J., "In-process Surface Recognition System Based on Neural Networks in End Milling Cutting Operations," Int. J. Mach. Tool Manuf. Vol. 39(4) , pp. 583-605, 1999. https://doi.org/10.1016/S0890-6955(98)00053-4
  5. Bouzid, W., Zghal, A., "Taguchi Method for Design Optimization of Milled Surface Roughness," Mater. Technol. Vol. 19 (3), pp. 159-162, 2004. https://doi.org/10.1080/10667857.2004.11753079
  6. Ismail, F., Elbestawi, M.A., Du, R., Urbasik, K., "Generation of Milled Surfaces Including Tool Dynamic and Wear," J. Eng. Ind. T. ASME Vol. 115 (3) , pp. 245-252, 1993.
  7. Kalpakjian, S., Schmid, S. R., "Manufacturing 7. Engineering and Technology, 5th". Prentice Hall, Inc.", NJ., 2005.
  8. Li, H.Z. Chen, X.Q., Zeng, H., "Flank Wear of Coated Carbide Inserts in the End Milling of Inconel 718," in: Proceedings of International Conference on Precision Engineering (IcoPE2003/04), Grand Hyatt, Singapore, March 2-5, pp. 203-209, 2004.
  9. Prickett, P.W. , Johns, C., "An Overview of Approaches to End Milling Tool Monitoring," Int. J. Mach. Tools Manuf. Vol. 39, 105-122, 1999. https://doi.org/10.1016/S0890-6955(98)00020-0
  10. Montgomery, D.C., "Design and Analysis of Experiments", 6th ed. John Wiley and Sons, Inc., New York, 2004.
  11. Lin, T., Chananda, B., "Quality Improvement of an Injection-Molded Product using Design of Experiments: a Case Study", Qual. Eng. Vol. 16 (1), pp. 99-104, 2004. https://doi.org/10.1081/QEN-120020776
  12. Puertas, I., Luis, C.J., "A study of Optimization of Machining Parameters for Electrical Discharge Machining of Boron Carbide", Mater. Manuf. Process. Vol. 19 (6), pp. 1041-1070, 2004. https://doi.org/10.1081/AMP-200035200