<4D6963726F736F667420576F7264202D2031312D3231D4DFD1ED20E6C7CDE3CF20E6E1CCEDE420E6C7CBEDD1> Al-Khwarizmi Engineering Journal Al-Khwarizmi Engineering Journal, Vol. 16, No. 1, March, (2020) P. P. 11- 21 Optimization the Effect of Electrode Material Change on EDM Process Performance Using Taguchi Method Shukry H. Aghdeab* Ahmed Ghazi Abdulameer ** Lujain Hussein Kashkool *** Atheer Rasim Mohammed **** *,**,***,**** Department of Production and Metallurgy Engineering/ University of Technology/ Baghdad/ Iraq * Email: shukry_hammed@yahoo.com ** Email: Ahmed.taku@yahoo.com *** Email: Lujain.1182@gmail.com **** Email: Atheermtc86@gmail.com (Received 20 January 2019; accepted 4 September 2019) https://doi.org/10.22153/kej.2020.09.001 Abstract Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µ s), and pulse off time (4, 12 and 25 µ s) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A Minitab software environment was used to adopt Taguchi method to analyze the effect of input on output parameters of EDM. The results of the present work showed that the best of MRR in copper and brass electrodes with (current 42 A, pulse on time 100 µ s and pulse off time 25 µ s) are (84.355×10-3 g/min) and (43.243×10-3 g/min) respectively, and the MRR predicted by Taguchi are (86.1751×10-3 g/min) in copper electrode by using the parameters with (current 10 A, pulse on time 200 µ s and pulse off time 25 µ s) and (43.2979×10-3 g/min) in brass electrode at current 42 A, pulse on time 100 µ s, and pulse off time 25 µ s. The lowest EWR occurs with a value of (1.4510×10-3 g/min) with (current 10 A, pulse on time 100 µ s, pulse off time 4 µ s) variables when using a copper electrode. The highest WR (2.602508) was found for the brass electrode with (current 24 A, pulse on time 200 µ s, pulse off time 4 µ s) variables. Keywords: EDM, taguchi method, material removal rate, electrode wear rate, wear ratio. 1. Introduction One of the non-conventional material removal processes is an electrical discharge machining (EDM), which is widely used in industry [1]. Metals are taken away from the piece by a series of frequent periodic electric spark between electrode and workpiece separate by a liquid solution [2]. At present, EDM is the most widely used technique for high – precision machining of all types of conductive metals, alloy irrespective of hardness. It is also used in Automobile industry, aerospace and in farm industry [3]. An initial cost of EDM machining is high but with a selection of optimal parameter's levels, its wastage, operating cost decreases with quality improvements [4]. In tested the influence of the electrical discharge machining parameters like, Pulse on Time (Ton), Pulse off Time (Toff), and Current (I) on Material Removal Rate (MRR) for stainless steel, the results were resolved by using variance analysis and Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 12 response graphs, it has been different collections of EDM process parameters are obtain higher MRR and better surface roughness (Ra) [5]. Srivastava & Pandey [6] conducted an experiment with the process parameters like a pulse on time, current, duty cycle and voltage on response factors like tool wear rate, material removal rate and surface roughness with the cryogenically treated electrode. They revealed that current, pulse on time and duty cycle have a significant effect on tool wear and material removal rate. Shukry et al. [7] studied the effect of EDM parameters such as current, pulsation on time and pulsation off time on surface roughness of steel 304 with dielectric solution of gas oil by supplied DC current values (10, 20, and 30A). The voltage of (140V) uses to cut 1.7mm thickness of the steel and use the copper electrode. They found that the parameters of current and pulsation on time affected the surface roughness (Ra) directly. Discharge current was the most effective parameter on the MRR & Ra when using the copper material as voltage, current, Pon and Poff for responses of surface roughness and material removal rate on the EDM of tool steel (AISI D2) [8]. Selection of input parameter played a great property of EDM on nickel superalloy material (RENE80) with aluminum (Al) as an electrode. That the input parameters considered are I; Pon and Poff are used for Experimental Work and their effect on MRR, Tool Wear Rate, and Ra [9]. 2. Objectives Although various parameters could be considered for electrical discharge machining process, but in the present work, three process parameters namely discharge current, pulse-on- time, and pulse-off time are considered. To find out the optimal factors of maximization for MRR in EDM process, Taguchi technique is used. The works have been done with oil as dielectric solution on (CM 323C EDM machine), as shown in Fig. 1. High-speed steel AISI M2 size 60×45×3mm plate is chosen for conductive experiment with nine specimens. The chemical, mechanical, and physical properties of the high- speed steel are given in table 1, and table 2, respectively. Fig. 1. EDM CM323C CNC Machine. Table 1, Chemical composition of AISIM2 works material. Material Weigh t (%) Material Weight (%) C 0.855 Mo 5.83 Si 0.305 Ni 0.14 Mn 0.28 Cu 0.175 P 0.001 V 1.88 S 0.001 W 5.73 Cr Sn 4.71 0.001 Co Fe 0.045 Balance Table 2, Mechanical and Physical properties of high speed steel. properties AISI M2 (%) Modulus of Elasticity (GPa) 207 Specific Heat Capacity (J/g- °C) 0.46 Thermal conductivity (W/m- K ) 19 Electrical Resistivity (ohm- cm) 54x10-6 Density (g/cm3) 8.14 Hardness (HRC) Chirpy Impact (J) Poisson's ratio 61-66 31.2-38 0.30 The tool electrodes’ material that are used in the experimental work are copper and brass electrodes (ϕ4×100 mm) with negative polarity, as shown in Fig. 2 (a- copper electrode and b- brass electrode). Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 13 Fig. 2. The high-speed steel (HSS) AISI M2 as a workpieces and electrodes (a) Copper electrode, (b) Brass electrode. By using three sets of experiments (Peak Current (Ip), Pulse on time (Ton), Gap Voltage (Vg)) to find tool wear rate, experiments showed that the optimization of process parameters, the third set gave the maximum tool wear rate when using the copper as a tool material and the aim was to optimize set of process parameters [10]. Variables on the material removal rate (MRR) in die-sinking EDM of EN19 material for four processes (Pulse on time, pulse off time, discharge current and gap voltage) with electrolytic copper use as the electrode material. The different combinations of process parameters and by analysis of variance (ANOVA) found that pulse off time, discharge current, gap voltage and the interaction terms are significant whereas the pulse on time has almost negligible effect on MRR 1.45% is the error between the predicted and experimental MRR value was found to be very effective as shown in this studied [11]. This work studies the optimization of EDM process parameters on machining per for using high-speed steel AISI M2 as a workpiece and copper and brass as an electrode. The material removal rate of the process obtained by the formula [12]: …(1) MRR= Material removal rate in (g/min). Mt = Machining time in (min). Wbm= Weight workpiece before machining in (g). Wam= Weight after workpiece machining in (g). The electrode wear rate of the process obtained by the formula [12]: …(2) Where: EWR= Electrode wear rate in (g/min). Mt = Machining time in (min). Ebm= Weight electrode before machining in (g). Eam= Weight electrode after machining in (g). The wear ratio of the process obtained by used the formula [13]: …(3) Where: WR= Wear ratio. EWR= Electrode wear rate in (g/min). MRR= Material removal rate in (g/min). 3. Taguchi Method To find out the best machining parameters of maximization for MRR in EDM process, Taguchi analysis is used. This method can identify the main effective parameters with embedded sub- level parameters. This method is used to loss function parameters diverge from the required values into a Signal to Noise (S/N) ratio to three types mainly as follows:- (1) Larger-The-Better (2) Nominal-The-Better (3) Smaller-The-Better The characteristic of higher value represents better machining performance. For example, material removal rate is termed as Larger-the- better. Characteristics of lower value appear for best machining interpretation. Hence it is concluded that for material removal rate "larger- is –better" were selected for finding optimum machining parameters. The overcut of (S/N) ratio is calculated by [14]: …(4) Where the Yi is ith observed value of the response and n: number of observations. The design and levels parameters of the study Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 14 experiments at different factors of consideration (current, pulse on time and pulse on time) are shown in table 3. MINITAB 17 Software is used for the design of the experiment in Taguchi analysis. A number from ordinary orthogonal array has been created to ease of experimental designing. Table 4 shows the Taguchi matrix method of the experiment at a different number of experiments with machining parameters grades. Table 3, Design of experiments. factors of code consideration grade 1 2 3 Current(A) I 10 24 42 PULSE ON TIME(µ s) Ton 100 150 200 PULSE OFF TIME(µ s) Toff 4 12 25 Table 4, Taguchi matrix ((3-grades design)). No. of Experiments Machining parameters grades I Ton Toff Current(A) Pulse On Pulse Off Time(µs) Time(µs) 1 2 3 4 5 6 7 8 9 1 1 1 2 2 2 3 3 3 1 2 3 1 2 3 1 2 3 1 2 3 2 3 1 3 1 2 4. Results and Discussion The obtained experimental results are shown in the tables (5-13), respectively. MRR, EWR and WR were analyzed in accordance with the input parameters i.e. current, Ton and Toff. Nine experiments were conducted according to the Tables (5-7) and the average of the three was taken for the analysis purpose. In order to investigate the effect of three parameters i.e. I. Ton and Toff on the MRR, EWR and WR experiments were conducted using L9 Orthogonal array along with the S/N ratio by used Taguchi design method of experiment at a different number of experiments with machining parameters grades. According to Taguchi method of the experiment, the better quality characteristics for material removal rate, electrode wear rate and wear ratio by use copper and brass electrodes. The ideal conditions for MRR required is current 42 A, Ton 100 µs and Toff 25 µ s of copper electrode. The required EWR is current 10 A, Ton 100 µ s and Toff 4 µ s of copper electrode, and the required WR is current 10 A, Ton 100 µ s and Toff 4 µ s of copper electrode. The optimal process parameters combination for max. MRR is found to be current at the highest level, pulse on time at the lowest level, and pulse off time at the highest level of the copper electrode, max. EWR is found to be current at the highest level, pulse on time at the lowest level, and pulse off time at the highest level of the brass electrode, and max. WR is found to be current at a moderate level, pulse on time at the highest level, and pulse off time at lowest level of brass electrode. Figs. (3-4) show the main effect of machining variables (I, Ton and Toff) on the MRR of copper electrode in rang (27.391-84.355×10-3 g/min) with current (10-42 A), pulse on time (100-200 µ s), and pulse off time (4-25 µ s) and obtained high MRR (84.355×10-3 g/min) with current (42 A), Ton (100 µ s), and Toff (25 µ s) and the MRR of brass electrode in rang (18.034-43.243×10-3 g/min) with current (10-42 A), Ton (100-200 µ s), and Toff (4-25 µ s). High MRR of (43.243×10-3 g/min) was obtained with current (42 A), Ton (100 µs), and Toff (25 µ s). Figs. (5-6) show the main effect of machining variables (I, Ton and Toff) on the EWR of copper electrode in rang (1.451-25.0716×10-3 g/min) with current (10-42 A), pulse on time (100-200 µ s), and pulse off time (4-25 µ s) and obtained low EWR (1.451×10-3 g/min) with current (10 A), Ton (100 µ s), and Toff (4 µ s) and the EWR of brass electrode in rang (25.8523-91.4651×10-3 g/min) with current (10-42 A), Ton (100-200 µ s), and Toff (4-25 µ s).Low EWR of (25.8523×10-3 g/min) was obtained with current (10 A), Ton (150 µs), and Toff (12 µ s). Figs. (7-8) show the main effect of machining variables (I, Ton and Toff) on the WR of copper electrode in rang (0.026619-0.297215) with current (10-42 A), pulse on time (100-200 µ s), and pulse off time (4-25 µ s). High WR of (0.297215) was obtained with current (42 A), Ton (100 µs), and Toff (25 µ s) and the WR of brass electrode in rang (1.38796-2.60258) with current (10-42 A), Ton (100-200 µs), and Toff (4-25 µ s) and obtained high WR (2.60258) with current (24 A), Ton (200 µ s), and Toff (4 µ s). The response tables for MRR, EWR and WR are given in Tables (8-13). It is verified from Table 8 that Toff has the maximum effect as compared to the I and Ton of the copper electrode. The ranks on the process parameters clarify this. Delta values are the difference between the maximum and minimum values from Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 15 level 1 to level 3. As MRR is the higher, the better type performance characteristics, so Table 8 gives the optimal setting of process parameters. From Table 8 and Fig. 3, it has been envisaged that (I) 2 (Ton) 3 (Toff) 1 gives the maximum MRR of copper electrode. Same condition as the rest of the tables (9- 13). From Table 9 and Fig. 5 it has been envisaged that (I) 2 (Ton) 3 (Toff) 1 gives the maximum MRR of copper electrode. Figs. (9-14) shows the main effect curve of MRR on current and pulse on at copper and brass electrodes. It has been noted from 3D figures influence that whenever current and pulse on-time increases the material removal rate increases. The MRR, EWR and WR increase with the increase in I and Ton. The reason exists behind this was the high value of spark-energy. As Ton is the time for which the current pulse in a circuit remains active. A large value of Ton depicts the large current value and this current value is the reason for spark. So, a high Ton value correspondingly enhances the spark energy. This spark energy removes the material from the work-piece. High Ton value removes a large amount of material as compared to the low Ton value. The values of MRR, EWR and WR found to be decreased with the increases in Toff value. This was due to the low value of spark-energy in the circuit. As Toff is the time gap between two successive pulses in a circuit, so if the time gap between two successive pulses decreased, then the value of current within a specified time period also decreases. This would reduce the intensity of the spark in the circuit. Table 5, Result machining variables experimental of MRR with Taguchi design. Table 6, Result machining variables experimental of EWR with Taguchi design. No. of Experiments I Ton Toff MRR Current (µs) (µs) 10- 3 (A) (g/min.) (Copper) PMEA N2 MRR 10-3(g/min.) (Brass) PMEAN3 1 10 100 4 54.510 58.2514 18.982 18.8696 2 10 150 12 70.072 63.8051 18.034 18.0889 3 4 5 6 7 8 9 10 24 24 24 42 42 42 200 100 150 200 100 150 200 25 83.652 12 48.840 25 68.876 4 31.833 25 84.355 4 27.391 12 32.849 86.1751 51.3654 72.6174 25.5661 78.0881 29.9164 36.5904 22.252 30.030 30.157 18.129 43.243 27.116 30.769 22.3096 30.0876 30.0446 18.1839 43.2979 27.1736 30.6566 No. of Experiments I Ton Toff EWR Current (µs) (µs) 10-3 (A) (g/min.) PMEAN2 EWR 10-3(g/min.) (Brass) PMEAN3 1 10 100 4 1.4510 1.4311 32.7528 32.6525 2 10 150 12 3.8702 3.8708 28.8523 28.8513 3 4 5 6 7 8 9 10 24 24 24 42 42 42 200 100 150 200 100 150 200 25 3.9706 12 13.4573 25 10.9633 4 1.4791 25 25.0716 4 7.074 12 5.9832 3.9706 13.4673 10.9333 1.4721 25.2716 7.0584 5.7822 30.8768 58.9802 59.5285 48.4499 91.4651 66.8264 71.7554 30.8771 58.9502 59.5235 48.4139 91.4651 66.7263 71.7253 Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 16 Table 7, Result machining variables experimental of WR with Taguchi design. Fig. 3. Main effects plot of the mean value for MRR of the copper electrode. Fig. 4. Main effects plot of the mean value for MRR of the brass electrode. Fig. 5. Main effects plot of the mean value for EWR of the copper electrode. Fig. 6. Main effects plot of the mean value for EWR of the brass electrode. No. of Experiments I Ton Toff WR Current (A) (µs) (µs) (Copper) PMEAN2 WR (Brass) PMEAN3 1 10 100 4 0.026619 0.026531 1.725466 1.72547 2 10 150 12 0.055232 0.056252 1.599883 1.59988 3 4 5 6 7 8 9 10 24 24 24 42 42 42 200 100 150 200 100 150 200 25 0.047465 12 0.275538 25 0.159174 4 0.046464 25 0.297215 4 0.258238 12 0.182142 0.049462 0.275732 0.158175 0.048465 0.299213 0.254233 0.186143 1.387596 1.464042 1.973953 2.602508 2.115143 2.464463 2.332068 1.38760 1.46404 1.97395 2.60251 2.11514 2.46446 2.33207 Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 17 Fig. 7. Main effects plot of mean value for WR of copper electrode. Fig. 8. Main effects plot of the mean value for WR of the brass electrode. Table 8, Response Table for Means of the copper electrode (MRR). Level I (A) Ton (µs) Toff (µs) 1 69.41 62.57 37.91 2 49.85 55.45 50.59 3 48.20 49.44 78.96 Delta 21.21 13.12 41.05 Rank 2 3 1 Table 9, Response Table for means of brass electrode (MRR). Level I (A) Ton (µs) Toff (µs) 1 19.76 30.75 21.41 2 26.11 25.10 26.28 3 33.71 23.72 31.88 Delta 13.95 7.03 10.47 Rank 1 3 2 Table 10, Response Table for means of copper electrode (EWR). Level I (A) Ton (µs) Toff (µs) 1 3.097 13.327 3.335 2 8.633 7.302 7.770 3 12.710 3.811 13.335 Delta 9.612 9.516 10.000 Rank 2 3 1 Table 11, Response Table for means of brass electrode (EWR). Level I (A) Ton (µs) Toff (µs) 1 30.83 61.07 30.83 2 55.65 51.74 53.20 3 76.68 50.36 60.62 Delta 45.86 10.71 11.28 Rank 1 3 2 Table 12, Response Table for means of copper electrode (WR). Level I (A) Ton (µs) Toff (µs) 1 0.04311 0.19979 0.11044 2 0.16039 0.15755 0.17097 3 0.24587 0.09202 0.16795 Delta 0.20276 0.10777 0.06053 Rank 1 2 3 Table 13, Response Table for means of brass electrode (WR). Level I (A) Ton (µs) Toff (µs) 1 1.571 1.768 2.264 2 2.014 2.013 1.799 3 2.304 2.107 1.826 Delta 0.733 0.339 0.465 Rank 1 3 2 Fig. 9. Show Main effect curve of MRR on current and pulse on of copper electrode. Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 18 Fig. 10. Show Main effect curve of MRR on current and pulse on of brass electrode. Fig. 11. Show Main effect curve of EWR on current and pulse on of copper electrode. Fig. 12. Show Main effect curve of EWR on current and pulse on of brass electrode. Fig. 13. Show Main effect curve of WR on current and pulse on of copper electrode. Fig. 14. Show Main effect curve of WR on current and pulse on of brass electrode. 5. Conclusions In this investigation, experiments on Electrical Discharge Machining were conducted to examine the influence of machining output possessed for idea are MRR, EWR and WR of the high speed steel AISI M2 workpiece using copper and brass electrodes tool by Taguchi design method. Improvement of MRR, EWR and WR have been also investigated. The experiment depends on various parameters namely (I), (Ton), and (Toff) which has been selected. This experiment is based on L9 orthogonal array by Taguchi design, was conducted and Minitab 17 software was used for this experiment. The major conclusions of this work are as follows: Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 19 1- Current has most significant parameters on MRR, EWR and WR but Ton moderately affects the MRR, EWR and WR while Toff has the least significant influence on MRR, EWR and WR for two electrodes copper and brass. 2- The best operation parameters, as shown in the observation table, are current 42 A, Ton 100 µ s, and Toff 25 µ s, for both copper and brass electrodes. 3- Through practical experiments, it has been noted that the use of a copper electrode is better than the electrode of the brass in terms of the MRR, EWR, and WR. Notation EDM Electrical Discharge Machining EWR Electrode wear rate HSS High speed steel I Current Ip Peak Current MR Material removal MRR Material removal rate Mt Machining time N Number of observations NTM Nontraditional machining Poff Pulse off Time Pon Pulse on Time Ra Surface roughness S/N Signal to Noise Ratio Toff Pulse off Time Ton Pulse on Time Vg Gap Voltage WR Wear ratio Wam Weight after machining Wbm Weight before machining Yi ith observed value of the response 6. References [1] K. Ojha, R. K. Garg, K. K. Singh, "MRR improvement in sinking electrical discharge machining: A Review," Journal of Minerals & Materials Characterization & Engineering, vol. 9, no. 8, p. 709-739, 2010. [2] S. B. Chikalthankar, V. M. Nandedkar, S. V. Borde, "Experimental investigations of EDM parameters," International Journal of Engineering Research and Development, vol. 7, p.31-34, 2013. [3] S. Shamsudin, M. Yusof, "Electrical Discharge Machining (EDM) Of Beryllium Copper Alloys Using Design Of Experiment (Doe) Approach," International Engineering Convention, Damascus Syria 11:p. 257- 268, 2009. [4] J. Kapoor , S.Singh and J.S. Khamba , "Effect of cryogenic treated brass wire electrode on material removal rate in wire electrical discharge machining," Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 226(11): p. 2750-2758, 2012. [5] S. Jaspreer, S. Mukhtiar and S. Harpreet, "Optimization of machining parameters in electrical discharge machining for 202 stainless steel," IJMER, Vol. 3, Issue.4, p.2166-2169, 2013. [6] V.Srivastava , P. M. Pandey , "Experimental investigation on EDM process with ultrasonic assisted cryogenically cooled electrode, "Journal of Engineering manufacturing 227: 301-314, 2013. [7] S.H. Aghdeab, N.H. Obaeed and M.Q. Ibraheem, "Surface roughness prediction for steel 304 In Edm using response graph modeling" Al-Khwarizmi Engineering Journal, vol. 14, No. 4, p. 115- 124, 2018. [8] S.B. Chikalthankar, V.M. Nandedkar, S.V. Borde, "Experimental investigations of EDM parameters" International Journal of Engineering Research and Development,"vol. 7, Issue 5, p. 31-34, 2013. [9] S. Chandramouli, U. B. Shrinivas, K. Eswaraiah, "Optimization of electrical discharge machining process parameters using taguchi method," International Journal of Advanced Mechanical Engineering, vol. 4, p. 425-434, 2014. [10] S. Tiwari, "Optimization of electrical discharge machining (EDM) with respect to tool wear rate," International Journal of Science, Engineering and Technology Research, vol. 2, p.764-768, 2013. [11] A.K.R. Shashikant, K. Kumar, "Optimization of Machine Process Parameters on Material Removal Rate in EDM for EN19 Material Using RSM," International Conference on Advances in Engineering & Technology, PP 24-28, 2014. [12] A.M. Ubaid, F. T. Dweiri, S. H. Aghdeab, L. Abdullah Al-Juboori, "Optimization of Electro Discharge Machining Process Parameters With Fuzzy Logic for Stainless Steel 304 (ASTM A240)" Journal of Manufacturing Science and Engineering, Mohannad R. Ghanim Al-Khwarizmi Engineering Journal, Vol. 15, No. 4, P.P. 11- 21 (2020) 20 vol. 140, p.011013-1-13, 2018. [13] A. A. Khan, M. Y. Ali and M. M. Haque, “A study of electrode shape configuration on the performance of die sinking EDM” International Journal of Mechanical and Materials Engineering (IJMME), Vol. 4, No. 1, p.19 -23, 2009. [14] S. K. Ghazi, S. H. Aghdeab and M. A. Abdullah “Investigation and Prediction of MRR in ECM Process Using Taguchi Method” Association of Arab Universities Journal of Engineering Sciences, Vol. 24, No. 3, p.190 -197, 2017. )2020( 11- 21، صفحة 1العدد ، 16دجلة الخوارزمي الهندسية المجلمشكري حميد غضيب 21 (EDM)امثيلية تاثير تغير مادة القطب على اداء عملية التشغيل بالشرارة الكهربائية باستخدام طريقة تاكوشي **احمد غازي عبداالمير *شكري حميد غضيب ****أثير راسم محمد ***لجين حسين كشكول الجامعة التكنولوجية /قسم هندسة االنتاج والمعادن *******،،**،* shukry_hammed@yahoo.com: البريد االلكتروني* Ahmed.taku@yahoo.com: البريد االلكتروني** Lujain.1182@gmail.com: البريد االلكتروني*** Atheermtc86@gmail.com: البريد االلكتروني**** الخالصة لتصنيع هندسة معقدة أو أجزاء معدنية صلبة للغاية يصعب NTM) عمليات تصنيع غير تقليدية واسعة النطاق ( (EDM)تعتبر عملية التفريغ الكهربائي تتميز باستخدام تآكل التفريغ الكهربائي. تناقش هذه (MR)تشغيلها بواسطة عمليات التشغيل التقليدية. آلتشغيل بالتفريغ الكهربائي هي عملية إلزالة المواد باعتبارها القطعة المشغلة واستخدم النحاس والبراص كأقطاب. محددات M2عالي السرعة AISI (HSS)على الصلب EDMت المثلى لالورقة المحددا ١٢و ٤)مايكروثانية ووقت نبضة التوقف ( ٢٠٠و ١٥٠، ١٠٠) ، وقت نبضة التشغيل (A ٤٢ (24,10, اإلدخال المستخدمة في العمل التجريبي الحالية ). استخدام برنامج ميني تاب باعتماد WR) ونسبة البلى (EWR)، معدل بلى االقطاب ( (MRRيكروثانية والتي تؤثر على معدل إزالة المواد) ما ٢٥و . أظهرت نتائج هذا العمل أن أفضل معدل إزالة المواد في أقطاب النحاس EDMطريقة تاكوشي لتحليل تأثير المدخالت على مخرجات المحددات من ال × ٤٣٫٢٤٣غرام/دقيقة) و (٣-١٠× 84.355 (مايكرو ثانية) ٢٥مايكرو ثانية ووقت نبضة التوقف ١٠٠، وقت نبضة التشغيل A ٤٢راص مع (لتيار والب لمتغيرات غرام/دقيقة) في القطب النحاسي باستخدام ا ٣-١٠× ٨٦٫١٧٥١غرام/دقيقة) على التوالي ، ومعدل إزالة المواد التي تنبأت عن تاكوشي هي ( ٣-١٠ غرام/دقيقة) في القطب النحاسي في ٣-١٠× ٤٣٫٢٩٧٩مايكرو ثانية ) و ( ٢٥مايكرو ثانية ووقت نبضة التوقف ٢٠٠، وقت نبضة التشغيل A ١٠(التيار غرام ٣-١٠×١٫٤٥١٠يمة (مايكرو ثانية. يحدث أدنى معدل بلى االقطاب بق ٢٥مايكرو ثانية ، ووقت نبضة التوقف ١٠٠، وقت نبضة التشغيل A ٤٢التيار مايكرو ثانية) عند استخدام القطب النحاس. تم العثور على ٤مايكرو ثانية ، ووقت نبضة التوقف ١٠٠، نبضة التشغيل A ١٠دقيقة) مع متغيرات (التيار / مايكرو ثانية). ٤رو ثانية ، ووقت نبضة التوقف مايك ٢٠٠، نبضة التشغيل A ٢٤لإللكترود النحاسي مع المتغيرات (التيار 2.602508)نسبة البلى ( أعلى