Comparing and Investigating the Effect of Input Parameters on External Parameters in Parts of Different Materials in EDM Operation Using Taguchi Method
الموضوعات :
Seyed Mohammad Reza Nazemosadat
1
,
Ahmad Afsari
2
,
Najwan Nejah Adnan Jeddeh
3
,
Alireza Bahramkia
4
1 - Department of Mechanical Engineering, Faculty of Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
2 - Department of Mechanical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
3 - Department of Mechanical Engineering, Faculty of Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
4 - Department of Mechanical Engineering, Sarvestan Branch, Islamic Azad University, Sarvestan, Iran
الکلمات المفتاحية: EDM, Surface Roughness, MRR, EWR, Taguchi Method,
ملخص المقالة :
The correct selection of input parameters in the electric discharge machining (EDM) process leads to improvements in the material removal rate (MRR), dimensional accuracy of the parts, quality of the surface finish, and reduction of tool wear. The main goal of the research was to investigate the type and extent of the influence of input on output parameters in EDM operations. Experimental data and the contribution of parameters were obtained using the Taguchi test design with three levels. The tool used was made of copper. Samples were selected from three types of alloy steel: 4340, Ti6Al-4V, and AISI D2 steel. The test variables included maximum current (Ip), gap voltage (Vg), and duty factor (DF). In these experiments, Ip values of 5, 10, and 15 amps, Vg values of 25, 50, and 75 volts, and DF values of 0.3, 0.6, and 0.9 were selected. The number of machining operations was 81 tests, and the L9 orthogonal array related to the Taguchi approach used for Design of Experiments (DOE) reduced the number of machining operations from 81 to 27 tests. The results indicated that the current parameter of 5 amps had the highest effect on surface roughness (SR) in samples of AISI4340 steel. The current of 15 amps had the greatest impact on MRR, while the duty factor (DF) of 0.6 played the highest role in electrode wear rate (EWR). Maximum Ip contributed 36.77%, Vg contributed 31.03%, and DF contributed 32.18% to EWR.
[1] Afsari, A., Saharkhiz, I. and Khadem S. M. R. 2014. Non-conventional Machinery (Electrophysical Process). Publications of Islamic Azad University of Shiraz.
[2] El-Hofy, H. A. G. 2005. Advanced Machining Processes: Nontraditional and Hybrid Machining Processes. McGraw Hill Professional.
[3] Selvarajan, L., Sasikumar, R., Kumar, N.S., Kolochi, P. and Kumar, P.N. 2021. Effect of EDM parameters on material removal rate, tool wear rate and geometrical errors of aluminium material. Materials Today: Proceedings. 46: 9392-9396. doi:10.1016/j.matpr.2020.03.054.
[4] Sarapure, S. 2023. Optimization of material removal rate and surface roughness during electric discharge machining of ultra‐fine grained Al6082 using Taguchi technique. Materialwissenschaft und Werkstofftechnik. 54(2):168-179. doi:10.1002/mawe.202200074.
[5] Arunnath, A., Madhu, S. and Tufa, M. 2022. Experimental investigation and optimization of material removal rate and tool wear in the machining of aluminum-boron carbide (Al-B4C) nanocomposite using EDM process. Advances in Materials Science and Engineering. 2022: Article ID 4254024 doi:10.1155/2022/4254024.
[6] HajHosseini, M.J., Mokhtarian, A., Rahimi, M. and Masoudi, B. 2022. Investigation and optimization of the effect of input parameters on material removal rate, tool wear rate, and surface roughness in electrical discharge machining of A356 Nano-composite reinforced by alumina. Advanced Processes in Materials Engineering. 16(3): 1-12. doi:20.1001.1.24233226.1401.16.3.1.2.
[7] Kumar, R. and Singh, B. 2020. Experimental Study for MRR and TWR on Machining of Inconel 718 using ZNC EDM. Strategic System Assurance and Business Analytics. Springer, Singapore.
[8] Rahmani, A., Mokhtarian, A. and Rahimi, M. 2021. Investigation and optimization of the effect of input parameters on output parameters of electrical discharge machining of A356 nano-composite reinforced by SiC. Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering. 13(4): 5-18.
[9] Safarabadi, A., Tahmasbi, V., Sousanabadi Farahani, A. and Zolfaghari, M. 2022. Electrical discharge machining of metal matrix composite AZ91 magnesium alloy and investigation and optimization of the effect of input parameters on material removal rate and workpiece surface roughness. Iranian Journal of Manufacturing Engineering. 9(6): 59-69. doi:10.22034/IJME.2022.160942.
[10] Motevasseli, H., Afsari, A. and Khosravifard, A. 2020. Investigation of Parameters Affecting Surface Integrity and Material Removal during Electrical Discharge Machining of HARDOX-400 Steel. Journal of Modern Processes in Manufacturing and Production. 9(2): 73-84. dor:20.1001.1.27170314.2020.9.2.6.0.
[11] Jafari, E., Afsari, A. and Abedpour, S. 2020. Predicting the Influence of Electrical Discharge Machining (EDM) Parameters on the Finished Work Surface in CK45 Steel. Journal of Modern Processes in Manufacturing and Production. 9(1): 63-78. dor: 20.1001.1.27170314.2020.9.1.6.8.
[12] Aghdeab, S.H. and Salman, T.M. 2021. Effect of Input Parameters on SR and MRR for Tool Steel AISI L2 by Electric Discharge Machine (EDM). Engineering and Technology Journal. 39(6): 928-935. doi:10.30684/etj.v39i6.1849.
[13] Heidari, S., Afsari, A. and Ranaei, M.A. 2020. Increasing wear resistance of copper electrode in electrical discharge machining by using ultra-fine-grained structure. Transactions of the Indian Institute of Metals. 73: 2901-2910. doi:10.1007/s12666-020-02091-8.
[14] William F. Smith and Hashemi, J. 2006. Foundations of Materials Science and Engineering. Mcgraw-Hill Publishing.
[15] Santhosh, A.J., Tura, A.D., Jiregna, I.T., Gemechu, W.F., Ashok, N. and Ponnusamy, M. 2021. Optimization of CNC turning parameters using face centred CCD approach in RSM and ANN-genetic algorithm for AISI 4340 alloy steel. Results in Engineering. 11: 100251. doi:10.1016/j.rineng.2021.100251.
[16] Venkateswarlu, V., Tripathy, D., Rajagopal, K., Tharian, K.T. and Venkitakrishnan, P.V. 2013. Failure analysis and optimization of thermo-mechanical process parameters of titanium alloy (Ti-6Al-4V) fasteners for aerospace applications. Case Studies in Engineering Failure Analysis. 1(2): 49-60. doi:10.1016/j.csefa.2013.04.003.
[17] Saeedifar, M. and Ahmadi Najafabadi, M. 2015. Determination of fracture toughness of heat treated AISI D2 steel using Finite Element and Acoustic Emission methods. Modares Mechanical Engineering. 14(11): 1-8. doi:20.1001.1.10275940.1393.14.11.11.0.
[18] Purushottam, N. R. A. M. D., and Dange, S. 2017. An Experimental Investigation of Machining Parameters for EDM using Electrode Shape Configuration of AISI P20 Tool Steel. IJSRD - International Journal for Scientific Research & Development. 5(9): 2321-0613.
[19] Sultan, T., Kumar, A. and Gupta, R.D. 2014. Material removal rate, electrode wear rate, and surface roughness evaluation in die sinking EDM with hollow tool through response surface methodology. International Journal of Manufacturing Engineering. 2014: Article ID 259129. doi:10.1155/2014/259129.
