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, 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
  • LONG BANH TIEN
  • QUY TRAN DUC
  • DONG PHAM VAN
  • CHUNG NGUYEN XUAN
  • THIEN NGUYEN VAN
  • LUAN NGUYEN DUC
  • MUHAMMAD JAMIL
  • AQIB MASHOOD KHAN
Article
  • 62 Downloads

Abstract

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%.

Keywords

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

Notes

Acknowledgements

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”.

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Copyright information

© Indian Academy of Sciences 2019

Authors and Affiliations

  • PHAN NGUYEN HUU
    • 1
    Email author
  • LONG BANH TIEN
    • 2
  • QUY TRAN DUC
    • 1
  • DONG PHAM VAN
    • 1
  • CHUNG NGUYEN XUAN
    • 1
  • THIEN NGUYEN VAN
    • 1
  • LUAN NGUYEN DUC
    • 1
  • MUHAMMAD JAMIL
    • 3
  • AQIB MASHOOD KHAN
    • 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

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