Application of Desirability to Find Out Ideal Input Parameter Setting in WEDM Operation

  • Himadri MajumderEmail author
  • Santosh Hiremath
  • Subhash Kumar
  • Pragat Kulat
Conference paper


Among the different non-traditional machining practice wire electrical discharge machining (WEDM) is the most flexible, useful and high précised machining process which is used to machine conductive materials. Presence of several contradictory responses in WEDM makes it difficult to choose the optimum machining parameter setting. This research demonstrates a multiple-criteria decision analysis (MCDA), desirability function analysis to optimize key input parameters for some contrary outputs during WEDM of inconel 718. Several significant machining variables, like pulse on time (TON), pulse off time (TOFF), pulsed current (WF) and servo voltage (SV) were considered as machining inputs for this investigation. The selected WEDM outputs are kerf width (KW), material removal rate (MRR) and root mean square roughness (Rq). The ideal input setting for multi-performance features has been found as TON = 120 µs., TOFF = 53 µs., I = 210 A. and SV = 25 V. The current research concentrated on the application of MCDA desirability function analysis as a precarious selection approach to deal with multi criteria optimization atmosphere.


Inconel 718 MCDA DFA Optimization WEDM 


  1. 1.
    Lazarenko, B.: To invert the effect of wear on electric power contacts. Dissertation of the All-Union Institute for Electro Technique in Moscow/CCCP (1943)Google Scholar
  2. 2.
    Majumder, H., Maity, K.: Predictive analysis on responses in WEDM of titanium grade 6 using general regression neural network (GRNN) and multiple regression analysis (MRA), Silicon, pp. 1–14 (2018)Google Scholar
  3. 3.
    Kumar, A., et al.: NSGA-II approach for multi-objective optimization of wire electrical discharge machining process parameter on inconel 718. Mater. Today: Proc. 4(2), 2194–2202 (2017)Google Scholar
  4. 4.
    Majumder, H., et al.: Use of PCA-grey analysis and RSM to model cutting time and surface finish of Inconel 800 during wire electro discharge cutting. Measurement 107, 19–30 (2017)CrossRefGoogle Scholar
  5. 5.
    Majumder, H., Maity, K.: Optimization of machining condition in WEDM for titanium grade 6 using MOORA coupled with PCA—a multivariate hybrid approach. J. Adv. Manufact. Syst. 16(02), 81–99 (2017)CrossRefGoogle Scholar
  6. 6.
    Majumder, H., Maity, K.: Application of GRNN and multivariate hybrid approach to predict and optimize WEDM responses for Ni-Ti shape memory alloy. Appl. Soft Comput. 70, 665–679 (2018)CrossRefGoogle Scholar
  7. 7.
    Manjaiah, M., Narendranath, S., Basavarajappa, S.: Wire electro discharge machining performance of TiNiCu shape memory alloy. Silicon 8(3), 467–475 (2016)CrossRefGoogle Scholar
  8. 8.
    Saha, A., Mondal, S.C.: Statistical analysis and optimization of process parameters in wire cut machining of welded nanostructured hardfacing material, Silicon, pp. 1–14 (2018)Google Scholar
  9. 9.
    Kumar, C.S., Patel, S.K.: Effect of WEDM surface texturing on Al2O3/TiCN composite ceramic tools in dry cutting of hardened steel. Ceram. Int. 44(2), 2510–2523 (2018)CrossRefGoogle Scholar
  10. 10.
    Khan, A., Maity, K.: A novel MCDM approach for simultaneous optimization of some correlated machining parameters in turning of CP-titanium grade 2. Int. J. Eng. Res. Afr. 22, 94–111 (2016)CrossRefGoogle Scholar
  11. 11.
    Khan, A., Maity, K.: Application of MCDM-based TOPSIS method for the optimization of multi quality characteristics of modern manufacturing processes. Int. J. Eng. Res. Afr. 23, 33–51 (2016)CrossRefGoogle Scholar
  12. 12.
    Naik, D.K., et al.: Experimental investigation of the PMEDM of nickel free austenitic stainless steel: a promising coronary stent material, Silicon, pp. 1–9 (2018)Google Scholar
  13. 13.
    Majumder, H., Maity, K.: Prediction and optimization of surface roughness and micro-hardness using grnn and MOORA-fuzzy-a MCDM approach for nitinol in WEDM. Measurement 118, 1–13 (2018)CrossRefGoogle Scholar
  14. 14.
    Majumder, H., Maity, K.: Multi-response optimization of WEDM process parameters using taguchi based desirability function analysis. In: IOP Conference Series: Materials Science and Engineering. IOP Publishing (2018)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Himadri Majumder
    • 1
    Email author
  • Santosh Hiremath
    • 1
  • Subhash Kumar
    • 1
  • Pragat Kulat
    • 1
  1. 1.G.H.Raisoni College of Engineering and ManagementPuneIndia

Personalised recommendations