Multi-objective optimization of high-pressure jet-assisted turning of Inconel 718

  • Djordje CicaEmail author
  • Davorin Kramar


Proper selection of cooling/lubricating technique is very important in the machining of difficult-to-cut materials such as nickel-based alloys due to their poor machinability. Among the available cooling/lubricating techniques, high-pressure jet-assisted machining offer remarkable opportunities in terms of increasing the productivity, reducing temperature in the cutting zone, excellent chip-breaking ability, and reduction of the costs associated with cooling/lubrication fluids. This article presents experimental investigation and multi-objective optimization of machining parameters of the high-pressure jet-assisted turning of Inconel 718 with coated carbide tools. The Taguchi L27 orthogonal array was used for the experimental design. Diameter of the nozzle, distance between the impact point of the jet and the cutting edge, pressure of the jet, cutting speed, and feed were considered as machining parameters. In order to optimize the six performance characteristics, namely cutting power, hydraulic power, material removal rate, surface roughness, cutting tool temperature, and chip length, Taguchi-based grey relational analysis and genetic algorithms were applied as multi-objective optimization approaches to identify the optimal levels of machining parameters. Moreover, the weights of the responses were determined by employing the analytic hierarchy process. Finally, a confirmation experiment with the machining parameters in their optimal levels was conducted with the aim to demonstrate the effectiveness of proposed multi-objective optimization approaches.


Optimization High-pressure jet-assisted turning Inconel 718 Taguchi method Grey relational analysis Genetic algorithm 



  1. 1.
    Ezugwu EO (2005) Key improvements in the machining of difficult-to-cut aerospace super alloys. Int J Mach Tool Manu 45(12–13):1353–1367CrossRefGoogle Scholar
  2. 2.
    Ezugwu EO, Bonney J, Yamane Y (2003) An overview of the machinability of aeroengine alloys. J Mater Process Technol 134(2):233–253CrossRefGoogle Scholar
  3. 3.
    Astakhov VP (2006) Tribology of metal cutting. Elsevier Science, MichiganGoogle Scholar
  4. 4.
    Weinert K, Inasaki I, Sutherland JW, Wakabayashi T (2004) Dry machining and minimum quantity lubrication. CIRP Ann-Manuf Technol 53(2):511–537CrossRefGoogle Scholar
  5. 5.
    Pusavec F, Kramar D, Krajnik P, Kopac J (2010) Transitioning to sustainable production-part II: evaluation of sustainable machining technologies. J Clean Prod 18(12):1211–1221CrossRefGoogle Scholar
  6. 6.
    Shokrani A, Dhokia V, Newman ST (2012) Environmentally conscious machining of difficult-to-machine materials with regard to cutting fluids. Int J Mach Tool Manu 57:83–101CrossRefGoogle Scholar
  7. 7.
    Hong SY, Zhao Z (1999) Thermal aspects, material considerations and cooling strategies in cryogenic machining. Clean Prod Process 1(2):107–116Google Scholar
  8. 8.
    Sharma VS, Dogra M, Suri NM (2009) Cooling techniques for improved productivity in turning. Int J Mach Tool Manu 49(6):435–453CrossRefGoogle Scholar
  9. 9.
    Ezugwu EO, Bonney J (2004) Effect of high-pressure coolant supply when machining nickel-base Inconel 718 alloy with coated carbide tools. J Mater Process Technol 153–154:1045–1050CrossRefGoogle Scholar
  10. 10.
    Naves V, Da Silva M, Da Silva F (2013) Evaluation of the effect of application of cutting fluid at high pressure on tool wear during turning operation of AISI 316 austenitic stainless steel. Wear 302(1):1201–1208CrossRefGoogle Scholar
  11. 11.
    Ezugwu E, Bonney J (2005) Finish machining of nickel-base Inconel 718 alloy with coated carbide tool under conventional and high-pressure coolant supplies. Tribol T 48(1):76–81CrossRefGoogle Scholar
  12. 12.
    Courbon C, Kramar D, Krajnik P, Pusavec F, Rech J, Kopac J (2009) Investigation of machining performance in high-pressure jet assisted turning of Inconel 718: An experimental study. Int J Mach Tool Manu 49(14):1114–1125CrossRefGoogle Scholar
  13. 13.
    Ezugwu E, Bonney J, Fadare D, Sales W (2005) Machining of nickel-base, Inconel 718, alloy with ceramic tools under finishing conditions with various coolant supply pressures. J Mater Process Technol 162–163:609–614CrossRefGoogle Scholar
  14. 14.
    Sharman A, Hughes J, Ridgway K (2008) Surface integrity and tool life when turning Inconel 718 using ultra-high pressure and flood coolant systems. Proc IME B-J Eng 222(6):653–664CrossRefGoogle Scholar
  15. 15.
    Klocke F, Sangermann H, Kramer A, Lung D (2011) Influence of a high pressure lubri-coolant supply on thermo-mechanical tool load and tool wear behaviour in the turning of aerospace materials. Proc IME B-J Eng 225(1):52–61CrossRefGoogle Scholar
  16. 16.
    Kramar D, Kopac J (2009) High pressure cooling in the machining of hard-to-machine materials. Stroj Vestn-J Mech E 55(11):685–694Google Scholar
  17. 17.
    Klocke F, Lung D, Cayli T, Dobbeler B, Sangermann H (2014) Evaluation of energy efficiency in cutting aerospace materials with high-pressure cooling lubricant supply. Int J Precis Eng Manuf 15(6):1179–1185CrossRefGoogle Scholar
  18. 18.
    Bermingham J, Palanisamy S, Kent D, Dargusch MS (2012) A comparison of cryogenic and high pressure emulsion cooling technologies on tool life and chip morphology in Ti–6Al–4V cutting. J Mater Process Technol 212(4):752–765CrossRefGoogle Scholar
  19. 19.
    Mia M, Khan MA, Dhar NR (2017) Performance prediction of high-pressure coolant assisted turning of Ti-6Al-4V. Int J Adv Manuf Technol 90(5–8):1433–1445CrossRefGoogle Scholar
  20. 20.
    Da Silva RB, Sales WF, Costa ES, Ezugwu EO, Bonney J, Da Silva MB, Machado AR (2017) Surface integrity and tool life when turning of Ti-6Al-4V with coolant applied by different methods. Int J Adv Manuf Technol 93(5–8):1893–1902CrossRefGoogle Scholar
  21. 21.
    Pawade RS, Joshi SS (2011) Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA). Int J Adv Manuf Technol 56(1–4):47–62CrossRefGoogle Scholar
  22. 22.
    Jafarian F, Amirabadi H, Sadri J (2015) Experimental measurement and optimization of tensile residual stress in turning process of Inconel718 superalloy. Measurement 63:1–10CrossRefGoogle Scholar
  23. 23.
    Senthilkumaar JS, Selvarani P, Arunachalam RM (2012) Intelligent optimization and selection of machining parameters in finish turning and facing of Inconel 718. Int J Adv Manuf Technol 58(9–12):885–894CrossRefGoogle Scholar
  24. 24.
    Jafarian F, Amirabadi H, Fattahi M (2014) Improving surface integrity in finish machining of Inconel 718 alloy using intelligent systems. Int J Adv Manuf Technol 71(5–8):817–827CrossRefGoogle Scholar
  25. 25.
    Jafarian F, Amirabadi H, Sadri J, Banooie HR (2014) Simultaneous optimizing residual stress and surface roughness in turning of Inconel 718 superalloy. Mater Manuf Process 29(3):337–343CrossRefGoogle Scholar
  26. 26.
    Pusavec F, Deshpande A, Yang S, M’Saoubi R, Kopac J, Dillon OW, Jawahir I (2015) Sustainable machining of high temperature nickel alloy–Inconel 718: part 2–chip breakability and optimization. J Clean Prod 87:941–952CrossRefGoogle Scholar
  27. 27.
    Thakur DG, Ramamoorthy B, Vijayaraghavan L (2010) Investigation and optimization of lubrication parameters in high speed turning of superalloy Inconel 718. Int J Adv Manuf Technol 50(5–8):471–478CrossRefGoogle Scholar
  28. 28.
    Colak O (2014) Optimization of machining performance in high-pressure assisted turning of Ti6Al4V alloy. Stroj Vestn-J Mech E 60(10):675–681CrossRefGoogle Scholar
  29. 29.
    Mia M, Khan MA, Rahman SS, Dhar NR (2017) Mono-objective and multi-objective optimization of performance parameters in high pressure coolant assisted turning of Ti-6Al-4V. Int J Adv Manuf Technol 90(1–4):109–118CrossRefGoogle Scholar
  30. 30.
    Himmelreich U (1992) Fluiddynamische modelluntersuchungen an wasserabrasivstrahlen. Dissertation, Universität HannoverGoogle Scholar
  31. 31.
    Taguchi G (1990) Introduction to quality engineering. McGraw-Hill, New YorkGoogle Scholar
  32. 32.
    Deng JL (1989) Introduction to grey system. J Grey Syst 1:1–24MathSciNetzbMATHGoogle Scholar
  33. 33.
    Satty T (1980) The analytical hierarchy process. McGraw-Hill, New YorkGoogle Scholar
  34. 34.
    Serra R, Chibane H, Duchosal A (2018) Multi-objective optimization of cutting parameters for turning AISI 52100 hardened steel. Int J Adv Manuf Technol 99(5–8):2025–2034CrossRefGoogle Scholar
  35. 35.
    Radovanović M (2019) Multi-objective optimization of multi-pass turning AISI 1064 steel. Int J Adv Manuf Technol 100(1–4):87–100CrossRefGoogle Scholar
  36. 36.
    Qu S, Zhao J, Wang T (2017) Experimental study and machining parameter optimization in milling thin-walled plates based on NSGA-II. Int J Adv Manuf Technol 89(5–8):2399–2409CrossRefGoogle Scholar
  37. 37.
    Ghosh G, Mandal P, Mondal SC (2019) Modeling and optimization of surface roughness in keyway milling using ANN, genetic algorithm, and particle swarm optimization. Int J Adv Manuf Technol 100(5–8):1223–1242CrossRefGoogle Scholar
  38. 38.
    Li S, Liu Y, Li Y, Landers RG, Tang L (2013) Process planning optimization for parallel drilling of blind holes using a two phase genetic algorithm. J Intell Manuf 24(4):791–804CrossRefGoogle Scholar
  39. 39.
    Zhou Y, Gong Y, Zhu Z, Gao Q, Wen X (2016) Modeling and optimization of surface roughness from microgrinding of nickel-based single crystal superalloy using the response surface methodology and genetic algorithm. Int J Adv Manuf Technol 85(9–12):2607–2622CrossRefGoogle Scholar
  40. 40.
    Varun A, Venkaiah N (2015) Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353. Int J Adv Manuf Technol 76(1–4):675–690CrossRefGoogle Scholar
  41. 41.
    Pandey AK, Gautam GD (2018) Grey relational analysis-based genetic algorithm optimization of electrical discharge drilling of Nimonic-90 superalloy. J Braz Soc Mech Sci Eng 40:117CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of Banja Luka, Faculty of Mechanical EngineeringBanja LukaBosnia and Herzegovina
  2. 2.University of Ljubljana, Faculty of Mechanical EngineeringLjubljanaSlovenia

Personalised recommendations