EXPERIMENTAL ANALYSIS AND OPTIMIZATION OF EDM PROCESS PARAMETERS THROUGH MODELING OF MATERIAL REMOVAL AND ELECTRODE WEAR BEHAVIOR
Keywords:
electrical discharge machining, full factorial experiment, material removal rate, electrode wear rateAbstract
This paper presents an experimental approach to analyze and optimize the Electrical Discharge Machining (EDM). The study's core methodology involves developing a model of the process to determine the functional relationship between the input parameters and the resulting Material Removal Rate (MRR) and Tool Wear Rate (TWR).The research demonstrated that impulse energy (Wi) is the most influential factor on MRR, while electrode diameter (De) is the most significant for TWR. It was also observed that brass electrodes have a higher wear rate than copper ones, due to their inferior electrical and thermal conductivity. The surface analysis confirmed that brass electrodes produce greater roughness, while copper electrodes provide superior surface quality. The study established two optimal parameter configurations for maximizing performance. For the brass electrode, the optimal combination was at a Wi of 0.45 J and a De of 10 mm, resulting in an MRR of 114.58 mm3/min and an TWR of 5.92%. For the copper electrode, the optimal settings were a Wi of 0.60 J and a De of 8.59 mm, which led to an MRR of 102.24 mm3/min and an TWR of 4.98%. The results highlight the importance of parameter optimization to ensure process productivity and efficiency.References
1. Dinesh, S., Vijayan, V., Thanikaikarasan, S., Sebastian, P.J. Productivity and quality enhancement in powder mixed electrical discharge machining for OHNS die steel by utilization of ANN and RSM modeling. Journal of New Materials for Electrochemical Systems, Vol. 22, No. 1, pp. 33-43, (2019), doi.org/10.14447/jnmes.v22i1.a07.
2. Gaikwad, M.U.; Krishnamoorthy, A.; Jatti, V.S. Estimation of Surface Integrity Parameters in Electrical Discharge Machining (EDM) Process—A Review. In Techno-Societal, Springer Cham, Switzerland, pp. 601–614, (2020), doi: 10.1007/978-3-030-16962-6_61.
3. Boral, S.; Sidhu, S.S.; Chatterjee, P.; Chakraborty, S.; Gugaliya, A. Multi-response Optimization of Micro-EDM Processes: A State-of-the-Art Review. In Micro-Electrical Discharge Machining Processes; Springer: Singapore, pp. 293–310, (2019), doi: 10.1007/978-981-13-3074-2_13.
4. Bahgat, M.M.; Shash, A.Y.; Abd-Rabou, M.; El-Mahallawi, I.S. Influence of process parameters in electrical discharge machining on H13 die steel. Heliyon, (2019), doi.org/10.1016/j.heliyon.2019.e01813
5. E. Ayhan, S. Güner, M. Yurdakul, and Y. T. İç, Robust parameter design for EDM-based AL2024-T3 machining, ournal of Engineering and Applied Science, (2025), doi: 10.1186/s44147-025-00618-8.
6. Barenji, R. V., Pourasl, H. H., &Khojastehnezhad, V. M. Electrical discharge machining of the AISI D6 tool steel: Prediction and modeling of the material removal rate and tool wear ratio. Precision Engineering, (2016), doi.org/10.1016/j.precisioneng.2016.01.012.
7. Karthik, S., and Sivakumar Annamalai. Investigation & analysis of Electrical Discharge Machining on Titanium Diboride Ceramic material with various Electrode materials and dielectric fluids. Materials Research Express, 2025, doi:10.1088/2053-1591/ada10e.
8. Abu Qudein, J. E., Zaiout, A., Mourad, A. H. I., &Abidi, M. H., &Elkascer, A. Principles and Characteristics of Different EDM Processes in Machining Tool and Die Steels. Applied Sciences, 10 (6), 2082, (2020), https://doi.org/10.3390/app10062082.
9. Kuppan, P.; Rajadurai, A.; Narayanan, S. Influence of EDM process parameters in deep hole drilling of Inconel 718. Int. J. Adv. Manuf. Technol, 38, 74–84, (2008).
10. Marafona, J.; Wykes, C. A new method of optimising material removal rate using EDM with copper–tungsten electrodes. Int. J. Mach. Tools Manuf, 40, 153–164, (2000).
11. Guu, Y.H.; Hocheng, H.; Chou, C.Y., Deng, C.S. Effect of electrical discharge machining on surface characteristics and machining damage of AISI D2 tool steel. Mater. Sci. Eng. A, 358, 37–43, (2003), https://doi.org/10.1016/S0921-5093(03)00272.
12. Gubencu, D.V. Îmbunătățirea continuă a proceselor tehnologice, Politehnica, Timișoara, Romania, (2023).
13. Montgomery, D.C. Design and Analysis of Experiments, 5th ed.; John Wiley and Sons: New York, NY, USA, 2001; pp. 218–276.
14. D. Taloi, Optimizarea proceselor tehnologice, Editura Academiei RSR, Bucureşti, (1987)
15. Hinkelmann, K.; Kempthorne, O. Response Surface Design. In Design and Analysis of Experiments, Volume 1. Introduction to Experimental Design, 2nd ed.; John Wiley & Sons: New Jersey, USA, pp. 497–531, (2008).
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