, 44:211 | Cite as

Multi-objective optimization of process parameter in EDM using low-frequency vibration of workpiece assigned for SKD61

  • PHAN NGUYEN HUUEmail author


Integrated vibration in electrical discharge machining (EDM) plays a key role in achieving high efficiency. High levels of variables can be employed in this approach due to integration. However, simultaneous optimization of the EDM parameters to achieve multi-objectives is still very complex and challenging. Studies on integrated vibration are still in a preliminary stage. This report addresses multi-objective optimization in EDM for SKD61 die steel using low-frequency vibration. MOORA (Multi-objective optimization based on ratio analysis) was chosen to resolve this multi-objective optimization problem. The material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) were selected as performance measures in the EDM process. An analytical hierarchical process (AHP) was used to determine the weight value of the quality indicators. The results indicate that low-frequency vibrations significantly improve machining efficiency. When the frequency of the vibrations increased, MRR increased significantly such that MRRMAX = 64.48%. TWR and SR are smaller and their increase are given as TWRMAX = 20.3% and SRMAX = 18.47%. MOORA has been identified as a suitable alternative to multi-objective optimization in an EDM process using low-frequency vibrations for an assigned workpiece. The optimum parameters required to achieve the multi-objective were Ton = 25 μs, I = 8 A, Tof = 5.5 μs and F = 512 Hz, at the resultant quality criteria of MRR = 9.564 mm3/min, TWR = 1.944 mm3/min and SR = 3.24 µm with a maximum error of 8.24%.


Material removal rate surface roughness tool wear rate low-frequency vibrational-EDM AHP MOORA 



The work described in this paper was supported by Hanoi University of Industry for a scientific project. This research is funded by Hanoi University of Industry under Grant No. “08-2018-RD/HD-DHCN”.


  1. 1.
    Ali M A M, Samsul M, Hussein N I S, Rizal M, Izamshah R, Hadzley M, Kasim M S, Sulaiman M A and Sivarao S 2013 The effect of EDM die-sinking parameters on material removal rate of beryllium copper using full factorial method. Middle East J. Sci. Res. 16(1): 44–50Google Scholar
  2. 2.
    Chavoshi S Z and Luo X 2015 Hybrid micro-machining processes: a review. Precis. Eng. 41: 1–23Google Scholar
  3. 3.
    Marashi H, Jafarlou D M, Sarhan A A D and Hamdi M 2016 State of the art in powder mixed dielectric for EDM applications. Precis. Eng. 46: 11–33Google Scholar
  4. 4.
    Unune D R and Mali H S 2014 Current status and applications of hybrid micro-machining processes: a review. Part B J. Eng. Manuf. 229(10): 1681–1693Google Scholar
  5. 5.
    Atul S, Pankaj A and Rana R S 2017 Applications of TOPSIS algorithm on various manufacturing processes: a review. Mater. Today Proc. 4: 5320–5329Google Scholar
  6. 6.
    Zhu G, Zhang M, Zhang Q, Song Z C and Wang K 2018 Machining behaviors of vibration-assisted electrical arc machining of W9Mo3Cr4V. Int. J. Adv. Manuf. Technol. Google Scholar
  7. 7.
    Unune D R and Mali H S 2016 Experimental investigations on low frequency workpiece vibration in micro electro discharge drilling of Inconel 718. In: Proceedings of the 6th International and 27th All India Manufacturing Technology, Design and Research Conference, pp. 1413–1417Google Scholar
  8. 8.
    Unune D R, Nirala C K and Mali H S 2019 Accuracy and quality of micro-holes in vibration assisted micro-electro-discharge drilling of Inconel 718. Measurement 135: 424–437Google Scholar
  9. 9.
    Pyeong A L, Younghan K and Bo H K 2015 Effect of low frequency vibration on micro EDM drilling. Int. J. Precis. Eng. Manuf. 16(13): 2617–2622, Google Scholar
  10. 10.
    Deepak R U and Harlal S M 2017 Experimental investigation on low-frequency vibration assisted micro-WEDM of Inconel 718. Eng. Sci. Technol. Int. J. 20(1): 222–231Google Scholar
  11. 11.
    Liu Y, Chang H, Zhang W, Ma F, Sha Z and Zhang S 2017 Study on gap flow field simulation in small hole machining of ultrasonic assisted EDM. Mater. Sci. Eng. 280(7): 1–23, Google Scholar
  12. 12.
    Hao T, Yang W and Li Y 2008 Vibration-assisted servo scanning 3D micro EDM. J. Micromechan. Microeng. 18(2): 025011, Google Scholar
  13. 13.
    Puthumana G 2016 Analysis of the effect of ultrasonic vibrations on the performance of micro-electrical discharge machining of A2 tool steel. Int. J. Recent Adv. Mechan. Eng. 5(3): 1–11Google Scholar
  14. 14.
    Mwangi J, Ikua B W, Nyakoe G N, Zeidler H and Kabini S K 2014 Effect of low frequency vibration in electrical discharge machining of AlSiC metal–matrix composite. J. Sustain. Res. Eng. 1(2): 45–50Google Scholar
  15. 15.
    Prihandana G S, Mahardika M, Hamdi M and Mitsui K 2011 Effect of low-frequency vibration on workpiece in EDM processes. J. Mechan. Sci. Technol. 25(5): 1231–1234Google Scholar
  16. 16.
    Garn R, Schubert A and Zeidler H 2011 Analysis of the effect of vibrations on the micro-EDM process at the workpiece surface. Precis. Eng. 35(2): 364–368Google Scholar
  17. 17.
    Kumar S and Grover S 2017 Optimisation strategies in ultrasonic vibration assisted electrical discharge machining: a review. Int. J. Precis. Technol. 7(1): 51–83Google Scholar
  18. 18.
    Todkar A S, Sohani M S, Kamble G S and Nikam R B 2013 Effects of vibration on electro discharge machining processes. Int. J. Eng. Innov. Technol. 3(1): 270–275Google Scholar
  19. 19.
    Qudeiri J E A, Mourad A H I, Ziout A, Abidi M H and Elkaseer A 2018 Electric discharge machining of titanium and its alloys: review. Int. J. Adv. Manuf. Technol. 96(1–4): 1319–1339Google Scholar
  20. 20.
    Todkar A S, Sohani M S, Kamble G S and Nikam R B 2013 Analysis of metal removal in vibration assisted micro-EDM. Int. J. Eng. Res. Technol. 2(7): 2401–2412Google Scholar
  21. 21.
    Iwai M, Ninomiya S and Suzuki K 2013 Improvement of EDM properties of PCD with electrode vibrated by ultrasonic transducer. Proc. CIRP 6: 146–150Google Scholar
  22. 22.
    Pandey A and Singh S 2010 Current research trends in variants of electrical discharge machining: a review. Int. J. Eng. Sci. Technol. 2(6): 2172–2191Google Scholar
  23. 23.
    Maity K P and Choubey M 2018 A review on vibration-assisted EDM, micro-EDM and WEDM. Surf. Rev. Lett. Google Scholar
  24. 24.
    Jaiswal A, Peshwani B, Shivakoti I and Bhattacharya A 2018 Multi response optimization of wire EDM process parameters. Mater. Sci. Eng. 377: 1–7, Google Scholar
  25. 25.
    Brauers W K M and Zavadskas E K 2012 Robustness of MULTIMOORA: a method for multi-objective optimization. Informatica 23(1): 1–25MathSciNetzbMATHGoogle Scholar
  26. 26.
    Majumder H and Maity K 2018 Prediction and optimization of surface roughness and micro-hardness using GRNN and MOORA-fuzzy-a MCDM approach for nitinol in WEDM. Measurement 118: 1–13Google Scholar
  27. 27.
    Saaty T L 2008 Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1): 83–98Google Scholar
  28. 28.
    Endo T, Tsujimoto T and Mitsui K 2008 Study of vibration-assisted micro-EDM—the effect of vibration on machining time and stability of discharge. Precis. Eng. 32(4): 269–277Google Scholar

Copyright information

© Indian Academy of Sciences 2019

Authors and Affiliations

    • 1
    Email author
    • 2
    • 1
    • 1
    • 1
    • 1
    • 1
    • 3
    • 3
  1. 1.Faculty of Mechanical EngineeringHanoi University of IndustryHanoiVietnam
  2. 2.School of Mechanical EngineeringHanoi University of Science and TechnologyHanoiVietnam
  3. 3.College of Mechanical and Electrical EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina

Personalised recommendations