Skip to main content
Log in

Optimization of material removal rate and tool wear rate of Cu electrode in die-sinking EDM of tool steel

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The principle of electrical discharge machining is based on electrical discharge which occurs between two electrodes (a cathode and an anode). The cathode is generally represented by workpiece and the anode by electrode tool. An electric discharge between the cathode and the anode occurs always upon fulfillment of basic conditions. A decisive influence has a kind of workpiece and tool electrode materials; spacing between the electrodes, called also gap; properties of dielectric fluid; and the main technological parameter setting. The combination of these parameters generates crater of specific shape on the workpiece and also on the tool electrode. The shape and size of the crater, formed during one electric discharge in die-sinking EDM, have a significant impact on material removal rate and on electrode wear. The aim of the paper is based on experimental measurement to identify the impact of selected process parameters on material removal rate and electrode wear in die-sinking EDM of tool steels EN X210Cr12 with Cu electrode EN CW004A, based on acquired dependencies to perform optimization of these parameters with a view of maximization of material removal rate and minimization of tool wear rate.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Che Haron CH (2001) Investigation on the influence of machining parameters when machining tool steel using EDM. J Mater Process Technol 116(1):84–87

    Article  Google Scholar 

  2. Mascaraque-Ramírez C, Franco P (2017) Experimental study of tool degradation in EDM processes: electrode material loss at the border and central zones. Int J Adv Manuf Technol 95:3497–3511. https://doi.org/10.1007/s00170-017-1469-5

    Article  Google Scholar 

  3. Saha SK, Chaudhary SK (2009) Experimental investigation and empirical modeling of the dry electrical discharge machining process. Int J Mach Tools Manuf 49:297–308

    Article  Google Scholar 

  4. Panda A, Prislupčák M, Pandová I (2014) Progressive technology diagnostic and factors affecting to machinability. Appl Mech Mater 616:183–190

    Article  Google Scholar 

  5. Straka Ľ, Čorný I (2009) Heat treating of chrome tool steel before electroerosion cutting with brass electrode. Acta Metall Slovaca 15(3):180–186

    Google Scholar 

  6. Dubják J, Piteľ J, Tóthová M (2016) Diagnostics of aluminum alloys melting temperature in high pressure casting. Key Eng Mater 669:110–117

    Article  Google Scholar 

  7. Panda A, Duplák J, Hatala M (2016) Cutting ceramic durability in machining process of bearings steel 100Cr6. MM Sci J 10:1060–1065

    Article  Google Scholar 

  8. Krenický T, Marcin J, Švec P (2004) Magnetic properties of FeCoNbB nanocrystalline alloys heat treated under longitudinal magnetic field. Czechoslov J Phys 54:185–188

    Article  Google Scholar 

  9. Kiyak M, Cakir O (2007) Examination of machining parameters on surface roughness in EDM of tool steel. J Mater Process Technol (1–3):41–144

  10. Amorim FL, Weingaertner WL (2007) The behavior of graphite and copper electrodes on the finish die-sinking electrical discharge machining (EDM) of AISI P20 tool steel. J Braz Soc Mech Sci Eng 29:366–371

    Article  Google Scholar 

  11. Khan AA (2008) Electrode wear and material removal rate during EDM of aluminum and mild steel using copper and brass electrodes. Int J Adv Manuf Technol 39:482–487

    Article  Google Scholar 

  12. Mathew S, Varma PRD, Kurian PS (2014) Study on the influence of process parameters on surface roughness and MRR of AISI 420 stainless steel machined by EDM. Int J Eng Trends Technol 15(2):54–58

    Article  Google Scholar 

  13. Tóthová M, Balara M, Dubják J (2015) Simulation model of cascade control of the heating system. Int J Eng Res Afr 18:20–27

    Article  Google Scholar 

  14. Ťavodová M (2014) Research state heat affected zone of the material after wire EDM. Acta Fac Tech 19:145–152

    Google Scholar 

  15. Mičietová A, Neslušan M, Čilliková M (2013) Influence of surface geometry and structure after non-conventional methods of parting on the following milling operations. Manuf Technol 13:199–204

    Google Scholar 

  16. Kreheľ R, Pollák M (2016) The contactless measuring of the dimensional attrition of the cutting tool and roughness of machined surface. Int J Adv Manuf Technol 86(1–4):437–449

    Google Scholar 

  17. Hašová S, Straka Ľ (2016) Design and verification of software for simulation of selected quality indicators of machined surface after WEDM. Acad J Manuf Eng 14(2):13–12

    Google Scholar 

  18. Maradia U, Boccadoro M, Stirnimann J, Beltrami I, Kuster F, Wegener K (2012) Die-sink EDM in meso-micro machining. Procedia CIRP 1:166–171

    Article  Google Scholar 

  19. Monka PP, Monková K, Balara M, Hloch S, Rehor J, Andrej A, Šomšák M (2016) Design and experimental study of turning tools with linear cutting edges and comparison to commercial tools. Int J Adv Manuf Technol 85(9–12):2325–2343

    Article  Google Scholar 

  20. Straka Ľ, Čorný I, Piteľ J (2016) Properties evaluation of thin microhardened surface layer of tool steel after wire EDM. Metals 6(5):1–16

    Article  Google Scholar 

  21. Michalik P, Zajac J, Hatala M, Duplák J, Mitaľ D (2016) Comparison of programming production of thin walled parts using different CAM systems. MM Sci J 10:1056–1059

    Article  Google Scholar 

  22. Straka Ľ, Hašová S (2016) Assessing the influence of technological parameters on the surface quality of steel MS1 after WEDM. MM Sci J 11:1194–1200

    Article  Google Scholar 

  23. Jaganathan P, Naveen Kumar T, Sivasubramanian R (2012) Machining parameters optimization of WEDM process using Taguchi method. Int J Sci Res Publ 2(12):1–4

    Google Scholar 

  24. Marafona J, Wykes C (2000) A new method of optimizing material removal rate using EDM with copper–tungsten electrodes. Int J Mach Tools Manuf 2000(40):153–164

  25. Straka Ľ, Čorný I, Piteľ J, Hašová S (2017) Statistical approach to optimize the process parameters of HAZ of tool steel EN X32CrMoV12-28 after die-sinking EDM with SF-Cu electrode. Metals 7(2):1–22

    Article  Google Scholar 

  26. Stephen P, Radzevich PS, Kreheľ R (2011) Application priority mathematical model of operating parameters in advanced manufacturing technology. Int J Adv Manuf Technol 56(2):835–840

    Google Scholar 

  27. Patel AD, Parekh MC, Patel BB, Patel BB (2012) Multi-objective optimisation of die sinking electro discharge machining process using Taguchi. Int J Eng Res Appl 2(6):1367–1371

    Google Scholar 

  28. Puthumana G, Bissacco G, Hansen HN (2017) Modeling of the effect of tool wear per discharge estimation error on the depth of machined cavities in micro-EDM milling. Int J Adv Manuf Technol 92:3253–3264. https://doi.org/10.1007/s00170-017-0371-5

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ľuboslav Straka.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Straka, Ľ., Hašová, S. Optimization of material removal rate and tool wear rate of Cu electrode in die-sinking EDM of tool steel. Int J Adv Manuf Technol 97, 2647–2654 (2018). https://doi.org/10.1007/s00170-018-2150-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-018-2150-3

Keywords

Navigation