Tool design and cutting parameter optimization for side milling blisk

  • Yaonan ChengEmail author
  • Jinlong Yang
  • Chao Qin
  • Diange Zuo


As the core component of the aircraft engine, high-efficiency manufacture of blisk is very difficult, because of its complex structure, high precision, and whose material belonging to difficult-to-machine materials such as titanium alloy, high temperature alloy and so on. It is one of the effective methods to solve the above problems by applying the side milling technology to the manufacture of blisk; the design and manufacture of ball end milling tool and the optimization of cutting parameters are of great significance to the advantage of the side milling process. Firstly, by analyzing the sectional line of tool, the mathematic models of tool edge line and tool escape curve are established. Based on these models, the parameterized model of the tool is finished, which paves the way for the subsequent analysis and optimization of the tool. After optimization, it is found that the ball end milling tool with a rake angle of 10°, a first rear angle of 12°, and a spiral angle of 38° has the best cutting effect on titanium alloy; secondly, the finite element method is used to design and analyze the geometrical structure of tool, and the modal analysis of the tool is carried out by DEFORM-3D to ensure the stability of cutting process, and the designed tool was manufactured by using the tool grinder; finally, the experimental research on the side milling titanium alloy was carried out by using the manufactured tool, and the influence of cutting parameters on the cutting force and the surface roughness was analyzed, and the model of cutting force and surface roughness and machining efficiency is completed. Based on the NSGA-II algorithm, the multi-objective optimization of the cutting parameters with cutting force, surface roughness, and metal removal rate as index is completed; the optimized results are as follows: vc = 70.2 m/min, fz = 0.03 mm/z, ae = 0.7 mm, and the axial depth is ap = 7.6 mm. This set of cutting parameters can guarantee small surface roughness and high machining efficiency under the condition of small cutting force, which is expected to provide a better theoretical reference and technical support for the tool design and high efficient manufacture of blisk.


Blisk Titanium alloy Ball end milling tool Side milling Cutting parameters 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


Funding information

This project was financially supported by the research and development project of applied technology of Harbin (2014DB4AG017) and the National Natural Science Foundation of China (51675145).


  1. 1.
    Zhan H, Zhao W, Wang G (2000) Manufacturing turbine blisks. Aircr Eng Aerosp Technol 72(3):247–252CrossRefGoogle Scholar
  2. 2.
    Ren JX, Yao CF, Zhang DH, Xue YL, Liang YS (2009) Research on tool path planning method of four-axis high-efficiency slot plunge milling for open blisk. Int J Adv Manuf Technol 45(1):101–109CrossRefGoogle Scholar
  3. 3.
    Zhao P, Huang J, Shi Y (2016) Structure design and rotation control of the disc milling head in blisk manufacturing. Int J Adv Manuf Technol 88(5–8):1–13CrossRefGoogle Scholar
  4. 4.
    Aspinwall DK, Mantle AL, Chan WK, Hood R, Soo SL (2013) Cutting temperatures when ball nose end milling γ-TiAl intermetallic alloys. CIRP Ann Manuf Technol 62(1):75–78CrossRefGoogle Scholar
  5. 5.
    Morishige K, Kase K, Takeuchi Y (1997) Collision-free tool path generation using 2-dimensional C-space for 5-axis control machining. Int J Adv Manuf Technol 13(6):393–400CrossRefGoogle Scholar
  6. 6.
    Senatore J, Monies F, Redonnet JM, Rubio W (2007) Improved positioning for side milling of ruled surfaces: analysis of the rotation axis's influence on machining error. Int J Mach Tool Manu 47(6):934–945CrossRefGoogle Scholar
  7. 7.
    Irene BC, Joan VC, Rojas G (2011) Influence of feed, eccentricity and helix angle on topography obtained in side milling processes. Int J Mach Tool Manu 51(12):889–897CrossRefGoogle Scholar
  8. 8.
    Wojciechowski S, Maruda R W, Królczyk G M, Nieslony P (2017) Application of signal to noise ratio and grey relational analysis to minimize forces and vibrations during precise ball end milling. Precis Eng 51Google Scholar
  9. 9.
    Wojciechowski S, Twardowski P, Pelic M, Maruda RW, Barrans S, Krolczyk GM (2016) Precision surface characterization for finish cylindrical milling with dynamic tool displacements model. Precis Eng 46:158–165CrossRefGoogle Scholar
  10. 10.
    Zhou JH, Ren JX, Yao CF (2017) Multi-objective optimization of multi-axis ball-end milling Inconel 718 via grey relational analysis coupled with RBF neural network and PSO algorithm. Measurement 102:271–285CrossRefGoogle Scholar
  11. 11.
    Yang SC, Zhou YZ, Zhang YH, Tong X, Liu WW (2017) Prediction on surface roughness of milling titanium alloy with micro texture ball end milling tool. Journal of Harbin University of Science and Technology 22(03):141–146Google Scholar
  12. 12.
    Ren J, He Q, Yao C, Liang Y, Liu B (2012) Tool axis orientation planning method of fixed axis in each cutting line for closed blisk tunnel five-axis machining. Acta Aeronaut Astronaut Sin 33(10):1923–1930Google Scholar
  13. 13.
    Wu K, He N, Jiang CY (2012) Application of APDL in the analysis of force and deformation of vertical milling. Mechanical Science and Technology for Aerospace Engineering 21(6):885–887Google Scholar
  14. 14.
    Ma JW, Wang FJ, Jia ZY, Xu Q, Yang YY (2014) Study of machining parameter optimization in high speed milling of Inconel 718 curved surface based on cutting force. Int J Adv Manuf Technol 75(1–4):269–277CrossRefGoogle Scholar
  15. 15.
    Chang CK, Lu HS (2006) Study on the prediction model of surface roughness for side milling operations. Int J Adv Manuf Technol 29(9–10):867–878CrossRefGoogle Scholar
  16. 16.
    Yang XY, Ren CZ, Wang Y, Chen G (2012) Experimental study on surface integrity of Ti6Al4V in high speed side milling. Transactions of Tianjin University 18(3):206–212CrossRefGoogle Scholar
  17. 17.
    Zhang CL, Zhang S, Yan XF, Zhang Q (2016) Effects of internal cooling channel structures on cutting forces and tool life in side milling of H13 steel under cryogenic minimum quantity lubrication condition. Int J Adv Manuf Technol 83(5–8):975–984CrossRefGoogle Scholar
  18. 18.
    Li AH, Zhao J, Wang ZM, Cui XB (2010) An experimental study of cutting forces in high speed side milling of inconel 718. Modular Machine Tool & Automatic Manufacturing Technique 10:75–78Google Scholar
  19. 19.
    Ribeiro MV, Moreira MRV, Ferreira JR (2003) Optimization of titanium alloy (6Al-4V) machining. J Mater Process Technol 143(36):458–463CrossRefGoogle Scholar
  20. 20.
    Rahman M, Wang ZG, Wong YS (2006) A review on high-speed machining of titanium alloys. JSME Int J 49(1):11–20CrossRefGoogle Scholar
  21. 21.
    Arrazola PJ, Garay A, Iriarte LM, Armendia M, Marya S, Maitre FL (2009) Machinability of titanium alloys (Ti6Al4V and Ti555.3). J Mater Process Technol 209(5):2223–2230CrossRefGoogle Scholar
  22. 22.
    M’Saoubi R, Axinte D, Soo SL, Nobel C, Attia H, Kappmeyer G, Engin S, Sim WM (2015) High performance cutting of advanced aerospace alloys and composite materials. CIRP Ann Manuf Technol 64(2):557–580CrossRefGoogle Scholar
  23. 23.
    Luo M, Luo H, Zhang D (2018) Improving tool life in multi-axis milling of Ni-based superalloy with ball-end cutter based on the active cutting edge shift strategy. J Mater Process Technol 252:105–115CrossRefGoogle Scholar
  24. 24.
    Davim JP, António CAC (2001) Optimisation of cutting conditions in machining of aluminium matrix composites using a numerical and experimental model. J Mater Process Technol 112(1):78–82CrossRefGoogle Scholar
  25. 25.
    Jiang ZX, Sun J, Li GC, Jia XM, Li JF (2015) Investigation on the relationship among tool wear, cutting force and vibration in milling of TC4. Acta Armamentarii 36(1):144–150Google Scholar
  26. 26.
    Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197CrossRefGoogle Scholar
  27. 27.
    Deb K, Kalyanmoy D (2001) Multi-objective optimization using evolutionary algorithms. John Wiley & Sons 39(1):75–96MathSciNetzbMATHGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Yaonan Cheng
    • 1
    Email author
  • Jinlong Yang
    • 1
  • Chao Qin
    • 1
  • Diange Zuo
    • 1
  1. 1.The Key Laboratory of National and Local United Engineering for “High-Efficiency Cutting & Tools”Harbin University of Science and TechnologyHarbinPeople’s Republic of China

Personalised recommendations