Advertisement

Optimization of Input Control Variables in Electric Discharge Machining of Inconel-718

  • Rahul DavisEmail author
  • Abhishek Singh
  • Tanya Singh
  • Subham Chhetri
  • V. Vikali Sumi
  • Alomi P. Zhimomi
  • Stephen Dilip Mohapatra
Conference paper
  • 45 Downloads
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

With rising requests of ongoing building items, the controlling of surface texture alongside dimensional exactness turns out to be increasingly indispensable. It has been analyzed that the working of the machined components and properties, for example, appearance, resistivity against fatigue/wear/corrosion, grease, introductory resistance, capacity to hold weight, load conveying limit, and commotion decrease (if there should arise an occurrence of apparatuses), are largely extraordinarily impacted by surface texture. The anomalies superficially as variety in stature and spacing are termed as surface roughness usually. It is always very strenuous and costly to control this in manufacturing, no matter what process is employed. Thus, accuracy in dimension and surface roughness is one of the main factors required to consider machining variables of any machining operation. In this paper, a research is being conducted to obtain optimal settings of the various levels of the input control variables in the machining of Inconel-718 by electric discharge machining (EDM), for achieving minimum roughness of the machined surface (SR).

Keywords

Design of experiment Electric discharge machining Inconel-718 Taguchi method ANOVA 

References

  1. 1.
    Mohan B, Muthuramalingam T (2015) A review on influence of electrical process parameters in EDM process. Arch Civ Mech Eng 15(1):87–95CrossRefGoogle Scholar
  2. 2.
    Rahman M, Jahan M, Wong YS (2013) Micro-electrical discharge machining (Micro-EDM): micro-manufacturing: design and manufacturing of micro-products, vol 11. Springer-Verleg London, pp 333–371Google Scholar
  3. 3.
    Mahapatra SS, Amar P (2007) Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method. Int J Adv Manuf Technol 34(9):911–925CrossRefGoogle Scholar
  4. 4.
    Ho KH, Newman ST (2003) State of the art electrical discharge machining (EDM). Int J Mach Tools Manuf 43:1287–1300CrossRefGoogle Scholar
  5. 5.
    Mohanty CP, Mahapatra SS, Singh MR (2017) An intelligent approach to optimize the EDM process parameters using utility concept and QPSO algorithm. Int J Eng Sci Technol 20(2):552–562Google Scholar
  6. 6.
    Holmberg J, Berglund J, Wretland A, Beno T (2019) Evaluation of surface integrity after high energy machining with EDM, laser beam machining and abrasive water jet machining of alloy 718. Int J Adv Manuf Technol 100:1575–1591CrossRefGoogle Scholar
  7. 7.
    Wang C, Qiang Z (2019) Comparison of Micro-EDM characteristics of inconel 706 between EDM oil and an Al powder-mixed dielectric. Adv Mater Sci Eng 1–11Google Scholar
  8. 8.
    Kumar S, Singh R, Singh TP, Sethi BL (2009) Surface modification by electrical discharge machining: a review. J Mater Process Technol 209(8):3675–3687CrossRefGoogle Scholar
  9. 9.
    George PM, Raghunath BK, Manocha LM, Warrier AM (2004) EDM machining of carbon-carbon composite—a Taguchi approach. J Mater Process Technol 145(1):66–71CrossRefGoogle Scholar
  10. 10.
    Her GM, Weng TF (2002) A study of the electrical discharge machining of semi-conductor BaTiO3. J Mater Process Technol 122(1):1–5CrossRefGoogle Scholar
  11. 11.
    Rao PS, Ramji K, Satyanarayana B (2016) Effect of Wire EDM conditions on generation of residual stresses in machining of aluminium T6 alloy. Alex Eng J 55:1077–1084CrossRefGoogle Scholar
  12. 12.
    Rahul, Abhishek K, Datta S, Biswal BB, Mahapatra SS (2017) Machining performance optimisation during EDM of Inconel 718: a case experimental investigation. Int J Prod Qual Manag 21(4):460–489Google Scholar
  13. 13.
    Ramakrishnan R, Karunamoorthy L (2008) Modelling and multi-response optimization of inconel-718 on machining of CNC WEDM process. J Mater Process Technol 207:343–349CrossRefGoogle Scholar
  14. 14.
    Bigot S, Valentincic J, Blatnik O, Junkar M (2006) Micro EDM parameters optimization, second international conference on multi-material micro manufacture (4M):195–198Google Scholar
  15. 15.
    Anil K, Sachin M, Sharma C, Beri N (2012) Machining efficiency evaluation of cryogenically treated copper electrode in additive mixed EDM. Mater Manuf Processes 27:1051–1058CrossRefGoogle Scholar
  16. 16.
    Balasubramanian P, Senthilvelan T (2014) Optimization of machining parameters in EDM process using cast and sintered copper electrodes. In: 3rd International conference on materials processing and characterization (ICMPC 2014), vol 6, pp 1292–1302Google Scholar
  17. 17.
    Sahu BK, Datta S, Mahapatra SS (2018) On electro-discharge machining of inconel 718 super alloys: an experimental investigation, ICMPC 2017. Mater Today Proc 5:4861–4869CrossRefGoogle Scholar
  18. 18.
    Keskin Y, Halkac HS, Kizil M (2006) An Experimental study for determination of the effects of machining parameters on surface roughness in electrical discharge machining (EDM. Int J Adv Manuf Technol 28:1118–1121Google Scholar
  19. 19.
    Seref A (2011) Surface roughness prediction in machining castamide material using ANN. Acta Polytech Hung 8(2):21–32Google Scholar
  20. 20.
    Swiercz R, Oniszczuk-Swiercz D, Chmielewski T (2019) Multi-response optimization of electrical discharge machining using the desirability function. Micromachines 72:1–25Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Rahul Davis
    • 1
    Email author
  • Abhishek Singh
    • 1
  • Tanya Singh
    • 2
  • Subham Chhetri
    • 2
  • V. Vikali Sumi
    • 2
  • Alomi P. Zhimomi
    • 2
  • Stephen Dilip Mohapatra
    • 2
  1. 1.National Institute of Technology PatnaPatnaIndia
  2. 2.Vaugh Institute of Agricultural Engineering & Technology, SHUATSPrayagrajIndia

Personalised recommendations