, Volume 11, Issue 2, pp 733–739 | Cite as

Effects of Wire Electro-Discharge Machining Process Parameters on the Machined Surface of Ti50Ni49Co1 Shape Memory Alloy

  • Hargovind SoniEmail author
  • Narendranath S.
  • Ramesh M. R.
Original Paper


Wire electro-discharge machining is one of the advanced machining processes which can machine all conductive materials without changing their internal properties. Pulse on time and servo voltage are the most influential process parameters of wire electro-discharge machining. In the present study, attempts have been made to study the effects of these process parameters on the machined surface of Ti50Ni49Co1 shape memory alloy by adopting a two process parameters experimental design approach. Cutting speed and surface roughness were considered as output parameters; surface crack density, microhardness and XRD analysis were carried out at the higher and lower values of these parameters. Higher surface crack density has been found at high values of cutting speed (125 μs pulse on time and 20 V servo voltage) while it is lower at the lower value of cutting speed (105 μs pulse on time and 60 V servo voltage). Moreover, a harder surface was found near the machined surface. By XRD analysis it was found that the crystal size of the WED machined surface was reduced at high Ton and lower SV.


WEDM TiNiCo alloys Surface crack density Microhardness XRD analysis 


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This work was supported by the Department of Science and Technology (DST) Government of India project reference no. SB/S3/MMER/0067/2013. Authors would like to thank DST for its funding support.


  1. 1.
    Xue D, Xue D, Yuan R, Zhou Y, Balachandran PV, Ding X, Sun J, Lookman T (2017) An informatics approach to transformation temperatures of NiTi-based shape memory alloys. Acta Mater 125:532–541CrossRefGoogle Scholar
  2. 2.
    Dadbakhsh S, Speirs M, Van Humbeeck J, Kruth J-P (2016) Laser additive manufacturing of bulk and porous shape-memory NiTi alloys: from processes to potential biomedical applications. MRS Bull 41(10):765–774CrossRefGoogle Scholar
  3. 3.
    Zheng YF, Zhang BB, Wang BL, Wang YB, Li L, Yang QB, Cui LS (2011) Introduction of antibacterial function into biomedical TiNi shape memory alloy by the addition of element Ag. Acta Biomater 7 (6):2758–67CrossRefGoogle Scholar
  4. 4.
    Zheng HX, Mentz J, Bram M, Buchkremer HP, Stöver D (2008) Powder metallurgical production of TiNiNb and TiNiCu shape memory alloys by combination of pre-alloyed and elemental powders. J Alloys Compd 463(1–2):250–256CrossRefGoogle Scholar
  5. 5.
    Mohammad Sharifi E, Kermanpur A, Karimzadeh F (2014) The effect of thermomechanical processing on the microstructure and mechanical properties of the nanocrystalline TiNiCo shape memory alloy. Mater Sci Eng A 598:183–189CrossRefGoogle Scholar
  6. 6.
    Lekston Z, Stroz D, Drusik-Pawlowska MJ (2012) Preparation and characterization of nitinol bone staples for cranio-maxillofacial surgery. J Mater Eng Perform 21(12):2650–2656CrossRefGoogle Scholar
  7. 7.
    Chen Z, Zhang Y, Zhang G, Huang Y, Liu C (2017) Theoretical and experimental study of magnetic-assisted finish cutting ferromagnetic material in WEDM. Int J Mach Tools Manuf 123(932):36–47CrossRefGoogle Scholar
  8. 8.
    Rattan N, Mulik RS (2017) Experimental investigations and multi-response optimization of silicon dioxide (quartz) machining in magnetic field assisted TW-ECSM process. Silicon 9(5):663– 673CrossRefGoogle Scholar
  9. 9.
    Soni H, Sannayellappa N, Motagondanahalli Rangarasaiah R (2017) An experimental study of influence of wire electro discharge machining parameters on surface integrity of TiNiCo shape memory alloy. J Mater Res 32 (16):3100–3108CrossRefGoogle Scholar
  10. 10.
    Puri AB, Bhattacharyya B (2005) Modeling and analysis of white layer depth in a wire-cut EDM process through response surface methodology. Int J Adv Manuf Technol 25:301–307CrossRefGoogle Scholar
  11. 11.
    Rao R, Yadava V (2009) Multi-objective optimization of Nd:YAG laser cutting of thin superalloy sheet using grey relational analysis with entropy measurement. Opt Laser Technol 41(8):922–930CrossRefGoogle Scholar
  12. 12.
    Sarikaya M, Güllü A (2015) Multi-response optimization of minimum quantity lubrication parameters using Taguchi-based grey relational analysis in turning of difficult-to-cut alloy Haynes 25. J Clean Prod 91:347–357CrossRefGoogle Scholar
  13. 13.
    Dhobe MM, Chopde IK, Gogte CL (2013) Investigations on surface characteristics of heat treated tool steel after wire electro-discharge machining. Mater Manuf Process 28(10):1143–1146CrossRefGoogle Scholar
  14. 14.
    Kumar A, Kumar V, Kumar J (2016) Surface crack density and recast layer thickness analysis in WEDM process through response surface methodology. Mach Sci Technol 20(2):201– 230CrossRefGoogle Scholar
  15. 15.
    Manjaiah M, Narendranath S, Basavarajappa S (2015) Wire electro discharge machining performance of TiNiCu shape memory alloy. Silicon 8(3):467–475CrossRefGoogle Scholar
  16. 16.
    Daneshmand S, Monfared V, Lotfi Neyestanak AA (2016) Effect of tool rotational and Al2O3 powder in electro discharge machining characteristics of NiTi-60 shape memory alloy. Silicon 9(2):273–283CrossRefGoogle Scholar
  17. 17.
    Sharma P, Chakradhar D, Narendranath S (2017) Analysis and optimization of WEDM performance characteristics of Inconel 706 for aerospace application. Silicon 1–10.
  18. 18.
    Sharma P, Chakradhar D, Narendranath S (2015) Evaluation of WEDM performance characteristics of Inconel 706 for turbine disk application. Mater Des 88:558–566CrossRefGoogle Scholar
  19. 19.
    Manjaiah M, Narendranath S, Basavarajappa S, Gaitonde VN (2014) Wire electric discharge machining characteristics of titanium nickel shape memory alloy. Trans Nonferrous Met Soc China (English Ed.) 24 (10):3201–3209CrossRefGoogle Scholar
  20. 20.
    Dewangan S, Gangopadhyay S, Biswas CK (2015) Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach. Eng Sci Technol Int J 18(3):361–368CrossRefGoogle Scholar
  21. 21.
    Sharma N, Khanna R, Gupta RD, Sharma R (2013) Modeling and multiresponse optimization on WEDM for HSLA by RSM. Int J Adv Manuf Technol 67(9–12):2269–2281CrossRefGoogle Scholar
  22. 22.
    Khanna R, Singh H (2016) Comparison of optimized settings for cryogenic-treated and normal D-3 steel on WEDM using grey relational theory. Proc Inst Mech Eng Part L J Mater Des Appl 230(1):219–232Google Scholar
  23. 23.
    Ekmekci B, Elkoca O, Erman Tekkaya A, Erden A (2005) Residual stress state and hardness depth in electric discharge machining: de-ionized water as dielectric liquid. Mach Sci Technol 9(1):39–61CrossRefGoogle Scholar
  24. 24.
    Kumar A, Kumar V, Kumar J, Markandeshwar M (2014) Machining science and technology?: an microstructure analysis and material transformation of pure titanium and tool wear surface after wire electric discharge. Mach Sci Technol 18:37–41CrossRefGoogle Scholar
  25. 25.
    Choudhary R, Kumar H, Garg RK (2010) Analysis and evaluation of heat affected zones in electric discharge machining of EN-31 die steel. Indian J Eng Mater Sci 17(2):91–98Google Scholar
  26. 26.
    Hsieh SF, Hsue AWJ, Chen SL, Lin MH, Ou KL, Mao PL (2013) EDM surface characteristics and shape recovery ability of Ti35.5Ni48.5Zr16 and Ni60Al24.5Fe15.5 ternary shape memory alloys. J Alloys Compd 571:63–68CrossRefGoogle Scholar
  27. 27.
    Hsieh SF, Chen SL, Lin HC, Lin MH, Chiou SY (2009) The machining characteristics and shape recovery ability of Ti-Ni-X (X=Zr, Cr) ternary shape memory alloys using the wire electro-discharge machining. Int J Mach Tools Manuf 49(6):509– 514CrossRefGoogle Scholar
  28. 28.
    Sharma P, Chakradhar D, Narendranath S (2016) Effect of wire material on productivity and surface integrity of WEDM-processed Inconel 706 for aircraft application. J Mater Eng Perform 25(9):3672–3681CrossRefGoogle Scholar

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringNational Institute of Technology KarnatakaSurathkalIndia

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