Parametric Optimization of Electrical Discharge Machining Process for Machining of AISI5160 with Copper Electrode using Taguchi Method

IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) Parametric Optimization of Electrical Discharge Machining Process for Machining of AISI5160 with Copper Electrode using Taguchi Method 1 Kapil Singh, 2 Simranjeet Singh 1,2 Dept. of Mechanical Engg. ARNI University, Kathgarh, HP, India Abstract In this paper machining was performed on AISI5160 material to study the material removal rate and surface finish by using copper electrode having 26 mm diameter and also copper powder (300 mesh no.) is mixed in dielectric fluid. Study shows that MRR is increased with the increase in spark on time and peak current and SR increase with the increase in discharge current. In previous work with same work piece and Aluminum electrode, experimental study shows the same nature but the MRR and SR has different value as compare to copper electrode. Basic purpose in this experimental study is to decrease the surface roughness and increase the MRR with optimum combination of machining parameters. As the material science contributed lots to new engineering metallic materials, alloys, composite materials and high tech ceramics materials with good mechanical properties, thermal characteristics, enough electrical conductivity so that they can easily be machined by spark erosion. Machining these materials required advanced machining methods with less utilization of mechanicals components. Electric Discharge Machining (EDM), a non-conventional process, contribute lots in automotive, defense, aerospace and others industries, plays an excellent role in the development of least cost products with high reliability. peak current and concentration of silicon powder in dielectric fluid on material removal rate and surface roughness by response surface methodology. Mohan et al., (2002) analyzed the effect of rotation of electrode on EDM of Al-SiCp composites [6]. Payal and Seth (2002) study the machining characteristics of EDM of 6061 Al Al 2 O 3 p composites to optimize the machining parameters [7]. Literature review indicate that study mostly concentrated on the composites materials. II. Experiment set-up AISI5160 material used for experimental investigation. The work piece material composition are C% 0.23, Mn% 1.50, S% 0.050, P% 0.050, Si% 0.40 and C.E % 0.42. Experiments were performed using Sparkonix ZNC Electric Discharge Machine. Fig. 4.0, depicts schematically the experimental setup. In this experiment setup a separate tank is fitted for dielectric fluid and work piece. Here we are using kerosene oil as dielectric fluid because of better corrosive resistant and easy availability. A mono block pump having 0.5 HP capacities was installed for proper circulation of the dielectric fluid into the discharge gap. The dielectric fluid supply at the pressure of 0.5 kg/sq.cm to completely flush out the eroded material from the working area. Keywords ANOVA, L9 Array, Minitab Software, Taguchi Analysis. I. Introduction Electric Discharge Machining (EDM) is an advance nontraditional machining process, where electrical energy is used to remove the material from work-piece by using the thermal energy of the spark. EDM is mostly used for machining the very hard materials which are difficult-to-machine on conventional machines, can also be used to machine difficult geometries in small batches. New development in materials like high resistant to temperature materials, light weight high strength materials etc., makes very difficult to machining on conventional machine. Work material to be machined by EDM has to be electrically conductive. The unconventional methods are used for hard, tough, and brittle material, it has no limitation and can produce any complex shape on any work piece material by a suitable control over various physical parameter of the process. Dhar et al. (2007) have conducted experimental study on machining of cast Al-4Cu-6Si alloy-10 wt. % sic composites to investigate the material removal rate and surface roughness with varying the electric discharge machine machining parameters [1]. Karthikeyan et al., (1999) investigated the effect of % SiC and other machining parameters make mathematical modeling for electric discharge machining of aluminium-silicon carbide particulate composites [2]. Lajis and Amin reported the implementation of Taguchi Method on EDM Process of Tungsten Carbide to study the effect of machining parameters [3]. Khullar and Kishore 2011, Optimization of EDM Parameters by Using Minitab software [4]. Kansal et.al (2005) investigated the effects on time, duty cycle, Fig. 4.0: Above experimental setup show that a separate pump is used to circulate the dielectric fluid. In this setup side flushing is used to flush the eroded material and a magnetic is put inside working tank to collect the eroded materials (debris). The copper powder is mixed in the dielectric fluid which is constantly stirring by separate motor so that powder is completely mixed with dielectric fluid. A. Work Piece Material AISI 5160 alloy steel is selected as work material in the present study. AISI 5160 alloy steel is a hard material and is difficult to machine by traditional machining methods because of its high w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 113

IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) abrasion resistance, excellent wear resistance and high compressive strength. Work-piece size of 9.5 cm x 6.5 cm x1cm is used. It is used in manufacturing die and heavy spring applications primarily in the automotive field for leaf springs. The chemical composition of 5160 alloy steel is shown in table 4.2. E. Selection of Orthogonal Array & Parameter Assignment In this experiment, there are four parameters at three levels each. The degree of freedom (DOF) of a three level parameter is 2 (number of levels-1), hence total DOF for the experiment is 8. The DOF of the orthogonal array selected should have higher than that of total DOF of the experiment. Table 3.5: Standards L9 Orthogonal Array (WOP) B. Preparation of Electrode The electrode material selected for the present work is copper (99.99%Cu) electrode. The material of electrode was prepared in the central workshop of SMVDU University. The material of electrode is copper having dimensions length 15 cm and diameter 2.6 cm. The copper electrode cut in pieces having length 2.5 cm and each for investigation. The diameter of electrode was reduced on the lathe machine with high speed and small depth of cut for getting the fine finish. After that bottom of electrode was prepared on the polishing machine to get the fine surface finish. EDM electrode materials are the components consist of highly conductive and arc erosion-resistant materials. C. Response Variables Evaluation The quantity of material removed in each experiment was known from changing weight of the work pieces. The material removal rate (MRR) is calculated as: MRR = (W i W F )/T g/min Where, W i is initial weight of work piece (g/min), W F is final weight of work piece (g/min), T is time (min.) The surface roughness was measured using surface roughness tester giving valves Ra valve in microns. The SR of the work piece can be expressed in different ways like arithmetic average (Ra), average peak to the valley heights (Rz) or peak roughness (Rp), etc. Generally, the SR is measured in terms of arithmetic mean (Ra) which according to the ISO 4987:1999 is defined as the arithmetic average roughness of the deviation of the roughness profile from the central line along the measurement. D. Design of Experiment The objective of this research work is to study MRR and Surface roughness, design variables can be summarized as follows: Table 3.4 Design scheme of experiment of parameters and levels Control parameter Level -1 0 +1 Peak Current, 3 21 45 Pulse on time, 2 30 150 Pulse off Time 4 6 9 Observed Values MRR(g/min) SR(u) No. of Control Parameter Observed Value Trial P Ton Toff MRR SR(Ra) 1 3 2 4 0.0000421 1.877 2 21 30 6 0.0083588 5.440 3 45 150 9 0.0224261 12.72 4 3 30 9 0.000051 3.919 5 21 150 4 0.0504587 10.36 6 45 2 6 0.0000463 6.494 7 3 150 6 0.0002548 4.198 8 21 2 9 0.0002039 8.298 9 45 30 4 0.0051525 7.839 Table 3.6: Standards L9 Orthogonal Array (WP) No. of Trial Control Observed Value P T A T B MRR SR(Ra) 1 3 2 4 5.096E-05 1.184 2 21 30 6 0.009785 4.789 3 45 150 9 0.024714 12.52 4 3 30 9 7.094E-05 3.148 5 21 150 4 0.045366 8.463 6 45 2 6 4.639E-05 6.242 7 3 150 6 0.000254 3.361 8 21 2 9 0.000102 8.125 9 45 30 4 0.004874 4.887 III. Results and Discussion Table 4.1: ANOVA for SN Ratios for SR Ip 2 140.4 140.424 70.212 15.88 0.050 Ton 2 38.32 38.327 19.164 4.33 0.047 Toff 2 17.18 17.181 8.590 1.94 0.340 2 8.842 8.842 4.421 Total 8 204. S = 2.103 R-Sq = 95.7% R-Sq(adj) = 82.7% Table 4.2: ANOVA for Means for SR Ip 2 55.4071 55.4071 27.7036 606.39 0.002 Ton 2 23.8263 23.8263 11.9132 260.76 0.004 Toff 2 12.9681 12.9681 6.4840 141.93 0.007 2 0.0914 0.0914 0.0457 Total 8 92.2929 S = 0.2137 R-Sq = 99.9% R-Sq(adj) = 99.6% 114 International Journal of Research in Mechanical Engineering & Technology www.ijrmet.com

ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) Table 4.3: Response Table for SN for SR 1-9.931-13.366-14.554 2-17.800-14.820-14.474 3-18.742-18.286-17.444 Delta 8.811 4.920 2.970 Rank 1 2 3 Table 4.4: Response Table for Means for SR 1 3.331 5.556 6.692 2 8.033 5.733 5.377 3 9.018 9.093 8.312 Delta 5.686 3.536 2.935 Rank 1 2 3 Table 4.5: ANOVA for SN Ratios for MRR Ip 2 1972.5 1972.5 986.2 7.93 0.112 Ton 2 2348.4 2348.4 1174.2 9.44 0.096 Toff 2 316.3 316.3 158.2 1.27 0.440 2 248.9 248.9 124.4 Total 8 4886.0 S = 11.15 R-Sq = 94.9% R-Sq(adj) = 79.6% Table 4.6: ANOVA table for Means for MRR Ip 2 0.000575 0.000575 0.000287 1.70 0.371 Ton 2 0.001004 0.001004 0.000502 2.97 0.252 Toff 2 0.000388 0.000388 0.000194 1.15 0.466 2 0.000338 0.000338 0.000169 Total 8 0.002305 S = 0.01301 R-Sq = 85.3% R-Sq(adj) = 41.3% Table 4.7: Response Table for SN Ratios for MRR 1-81.75-82.67-53.07 2-47.10-57.72-66.71 3-55.14-43.60-64.22 Delta 34.64 39.07 13.64 Rank 2 1 3 Table 4.8: Response Table for Means for MRR 1 0.000116 0.000097 0.018551 2 0.019674 0.004521 0.002887 3 0.009208 0.024380 0.007560 Delta 0.019558 0.024282 0.015664 Rank 2 1 3 Table 4.9: ANOVA for SN ratios for SR IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 Ip 2 187.662 187.662 93.831 19.11 0.050 Ton 2 47.725 47.725 23.862 4.86 0.171 Toff 2 45.154 45.154 22.577 4.60 0.179 2 9.820 9.820 4.910 Total 8 290.361 S = 2.216 R-Sq = 96.6% R-Sq(adj) = 86.5% Table 4.10: ANOVA for Means for SR Ip 2 49.6675 49.6675 24.8338 63.01 0.016 Ton 2 24.1626 24.1626 12.0813 30.65 0.032 Toff 2 19.3476 19.3476 9.6738 24.54 0.039 2 0.7883 0.7883 0.3941 Total 8 93.9660 S = 0.6278 R-Sq = 99.2% R-Sq(adj) = 96.6% Table 4.11: Response Table for SN Ratios for SR 1-7.319-11.857-11.266 2-16.784-12.449-13.347 3-17.213-17.011-16.703 Delta 9.894 5.154 5.437 Rank 1 3 2 Table 4.12: Response Table for Means for SR 1 2.564 5.184 4.845 2 7.126 4.275 4.797 3 7.883 8.115 7.931 Delta 5.319 3.840 3.134 Rank 1 2 3 Table 4.13: ANOVA for SN Ratios for MRR Ip 2 1650.5 1650.5 825.3 4.86 0.171 Ton 2 2569.6 2569.6 1284.8 7.57 0.117 Toff 2 321.4 321.4 160.7 0.95 0.514 2 339.3 339.3 169.7 Total 8 4880.8 S = 13.03 R-Sq = 93.0% R-Sq(adj) = 72.2% Table 4.14: ANOVA for Means for MRR Ip 2 1650.5 1650.5 825.3 4.86 0.171 Ton 2 2569.6 2569.6 1284.8 7.57 0.117 Toff 2 321.4 321.4 160.7 0.95 0.514 2 339.3 339.3 169.7 Total 8 4880.8 S = 13.03 R-Sq = 93.0% R-Sq(adj) = 72.2% w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 115

IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) Table 4.15: Response Table for SN Ratios 1-80.24-84.12-52.99 2-48.96-56.47-66.25 3-55.02-43.63-64.98 Delta 31.27 40.50 13.26 Rank 2 1 3 Table 4.16: Response Table for Means 1 0.000126 0.000066 0.016762 2 0.018417 0.004910 0.003362 3 0.009880 0.023445 0.008298 Delta 0.018291 0.023379 0.013400 Rank 2 1 3 pulse on time increases from 2μs to 150μs SR increases and also as the pulse off time increases 4 to 9 the SR first reduce upto 6 then further increases. Surface roughness s lower down by suspending aluminium powder in dielectric fluid. The slope of the curve indicates the rate of decrease of surface roughness. This improvement in surface quality is due to the reason that added powder particles enlarges and widens the discharge passage which facilitates easy evacuation of produced debris from the spark gap. The powder particles lead to uniform dispersion of discharge energy in all directions. This results in reduction of surface roughness. A. Surface Roughness Figure shows the main effects of SR of each factor for various level conditions. According to this figure the SR increases with voltage and slightly increases with peak current. Larger craters were produced by a larger power supply voltage, possibly producing a larger discharging energy. The influence of peak current with various setting is shown in figure. According to K.P Rajurkar, etc. the variation of crater diameter, depth and volume with respect to peak current is consistent with the general findings in EDM literature that higher currents generate larger crater and therefore produces rough surfaces. Fig. 4.1: Plots for SN Ratios for SR Fig. 4.3: Main Effects Plot for SN ratios (SR) Fig. 4.2: Plots for Means for SR From the main effect plot 4.4 it is observed that SR increases with the increase in peak current from 3 Amp to 45Amp. As Fig. 4.4: Main Effects Plot for Means (SR) 116 International Journal of Research in Mechanical Engineering & Technology www.ijrmet.com

ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) Table 4.17 Optimum Machining Condition Based on Results of SR Peak Current, P(ampere) 3 1 IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 caused a higher MRR with lower discharge energy. According to this figure, MRR increases with short interval time and peak current. The possible reason for the higher MRR may be due to more frequency discharge per unit cycle time. Pulse Duration, T on (µs) 2 1 Interval Time Toff(µs) 6 2 Fig. 4.7: Main Effects Plot for SN Ratios for MRR Fig. 4.5: Plots for Signal to Noise Fig. 4.8: Main Effects Plot for means for MRR Table 4.18: Optimum Machining Condition Based on Results of MRR Peak Current, P(ampere) 21 2 Pulse Duration, T on (µs) 30 2 Interval Time T off (µs) 4 1 Table 4.19: Optimum Machining Condition Based on Results of MMR Peak Current, P(ampere) 21 2 Fig. 4.6: Plots for Means for MRR Pulse Duration, T on (µs) 150 3 Interval Time Toff(µs) 4 1 From the main effect plot 4.8 it is observed that MRR increases with the increase in peak current from 3 Amp to 21Amp. Because at higher current stronger spark is generated so melting starts earlier which results in higher MRR. As pulse on time increases from 2 μs to 150μs, MRR also increases because longer is the pulse duration higher will be the spark energy. MRR is directly proportional to the amount of energy applied during this on time. B. Material Removal Rate Figure shows the main effects of MRR of each factor for various level conditions. It was observed the MRR increases with pulse on time and slightly increases with peak current. According to B.H. Yan, etc, using a negative polarity in EDM caused higher MRR with higher discharge energy; in contrast a positive polarity Fig. 4.9: Plots for SN Ratios (26 mm) w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 117

IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) Table 4.20: Optimum Machining Condition Based on Results of SR Peak Current, P(ampere) 3 1 Pulse Duration, Ton(µs) 30 2 Interval Time T off (µs) 4 1 Fig. 4.10: Plots for Means (26 mm) Fig. 4.13: Plots for SN Ratios for MRR Fig. 4.11: Main Effects Plot for Signal to Noise Ratio for SR Fig. 4.14: Plots for Means for MRR Fig. 4.12: Main Effects plot for Means for SR From the main effect plot it is observed that SR increases with the increase in peak current from 3 Amp to 45Amp. As pulse on time increases from 2μs to 150μs, SR decreases first and further increases upto 150 μs and also as the pulse off time increase from 4 to 6 remain almost constant then further increases upto 9. Surface roughness s lower down by suspending copper powder in dielectric fluid. The slope of the curve indicates the rate of decrease of surface roughness. This improvement in surface quality is due to the reason that added powder particles enlarges and widens the discharge passage which facilitates easy evacuation of produced debris from the spark gap. The powder particles lead to uniform dispersion of discharge energy in all directions. This results in reduction of surface roughness as compare to the without powder EDM. Fig. 4.15: Main Effects Plot for Signal to noise for MRR 118 International Journal of Research in Mechanical Engineering & Technology www.ijrmet.com

ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 current. The possible reason for the higher MRR may be due to more frequency discharge per unit cycle time. Fig. 4.16: Main Effects Plot for Means for MRR Table 4.21: Optimum Machining Condition Based on Results of MMR Peak Current, P(ampere) 21 2 Pulse Duration, Ton(µs) 150 3 Interval Time Toff(µs) 4 1 Influence of Peak current (3 A, 21A, 45A) on discharging crater Table 4.22: Confirmatory Test for MRR Factors Level Description Responses Peak Current, P(ampere) 21 MRR = 0.345gm/min Pulse Duration, Ton(µs) 150 MRR = 0.382gm/min Interval Time Toff(µs) 4 (with powder) Table 4.23: Confirmatory Test for SR Factors Level Description Peak Current, P(ampere) 3 Pulse Duration, T on (µs) 30 Interval Time T off (µs) 6 IV. Conclusion Responses SR = 3.88 (26 mm) SR = 3.120(26 mm) With powder A. Material Removal Rate Figure shows the main effects of MRR of each factor for various level conditions. It was observed the MRR increases with pulse on time and slightly increases with peak current. According to B.H. Yan, etc, using a negative polarity in EDM caused higher MRR with higher discharge energy; in contrast a positive polarity caused a higher MRR with lower discharge energy. According to this figure, MRR increases with short interval time and peak B. Surface Roughness Figure shows the main effects of SR of each factor for various level conditions. According to this figure the SR increases with voltage and slightly increases with peak current. Larger craters were produced by a larger power supply voltage, possibly producing a larger discharging energy. The influence of peak current with various setting is shown in figure. According to K.P Rajurkar, etc. the variation of crater diameter, depth and volume with respect to peak current is consistent with the general findings in EDM literature that higher currents generate larger crater and therefore produces rough surfaces In present work, an addition of a copper powder mixed in dielectric resulted in high MRR, good surface finish when compared with pure dielectric. Both MRR and TWR apparently increase with the increase of the peak current and pulse on time. The result obtained from the present study is extremely helpful for selecting the optimum machining conditions for AISI 5061 stainless steel work material, which is extensively used in moulds and dies making industries. Within the range of parameters selected the following specific conclusions are drawn from the experimental results. EDM process plays a big role in mold manufacturing industries. Due to longer machining time, it machining cost is high. To increase EDM process efficiency, PMEDM was proposed. However further investigations are required before the new PMEDM can be commercialized. This work proposes investigation on copper PMEDM powder concentration and powder particles size in cutting material. The results are expected to provide information on: 1. The influence of PMEDM in machining material in terms of MRR and SR. 2. The reduction machining time of EDM process with PMEDM. 3. The optimum powder concentration and size of powder particles to achieve the highest efficiency of EDM process. The peak current and powder concentration is the most contributing factor that improves the MRR. The metal removal rate will increase as the peak current and powder concentration increase. The result shows the highest of MRR as Cu as electrode is 45.7mm3/min at peak current 40A. With 8 g/l of powder concentration the improvement is almost 32% in comparison to without powder concentration at the same parameter setting. The result shows that the introduction of powder concentration in dielectric fluid will helps to enhance the machining efficiency. It also found that within selected parameters, 8g/l is the best powder concentration to achieve high MRR. The experiments were conducted under various parameters setting of Discharge Current (Ip), Pulse On-Time (Ton) and Pulse On- Time (Ton). L-9 OA based on Taguchi design was performed for Minitab software was used for analysis the result and theses responses were partially validated experimentally. 1. Finding the result of MRR, discharge current is most influencing factor and then pulse duration time. MRR increased with the discharge current (Ip). As the pulse duration extended, the MRR decreases monotonically. 2. In the case of surface roughness the most important factor is discharge current. Other parameter like flushing etc can be considered and also under presence of some expert. w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 119

IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 ISSN : 2249-5762 (Online) ISSN : 2249-5770 (Print) We can change polarity. Effect of different Dielectric fluids No interaction is consider so we can consider interaction by applying L27 or L32 this will improve optimum condition as compare to L9 considered in this work. Also side clearance and thermal effect on material and work piece can also be considered to study the effect on properties of work piece and tool. Other modeling method like genetic algorithm, artificial neural network can also apply. Machining of Composite materials considered in future work. Reference [1] Yan, B.H.; Chen, S.L.,"Effects of dielectric with suspended aluminum powder on EDM", Journal of Chinese Society of Mechanical Engineering, 14 (3), pp. 307 312, 1993. [2] Jeswani, M.L., Effect of addition of graphite powder to kerosene used as a dielectric fluid in electrical discharge machining, Wear, Vol. 70, pp. 133 139, 1981. [3] Kansal, H.K et al,"effect of Silicon Powder Mixed EDM on Machining Rate of AISI D2 Die Steel", Journal of Manufacturing Processes Vol. 9, No. 1, 2007. [4] 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", Materials Science and Engineering A358: pp. 37-43, 2003. [5] Kansal, H.K. et al,."numerical simulation of powder mixed electric discharge machining (PMEDM) using finite element method", Mathematical and Computer Modelling 47, pp. 1217 1237, 2008. [6] Ojha, K. et al,."parametric Optimization of PMEDM Process using Chromium Powder Mixed Dielectric and Triangular Shape Electrodes", Journal of Minerals & Materials Characterization & Engineering, Vol. 10, No. 11, pp. 1087-1102, 2011. [7] Kansal, H.K. et al,."parametric optimization of powder mixed electrical discharge machining by response surface methodology", Journal of Materials Processing Technology 169, pp. 427 43, 2005. [8] Wu, K.L. et al.,"improvement of surface finish on SKD steel using electro-discharge machining with aluminum and surfactant added dielectric", International Journal of Machine Tools & Manufacture 45, pp. 1195 1201, 2005. [9] Kansal, H.K. et al., (2006),"Technology and research developments in powder mixed electric discharge machining (PMEDM)", Journal of Materials Processing Technology 184, pp. 32 41, 2007. Kapil Singh received his B-Tech degree in Mechanical Engineering from RIMT Instiute of Engg & Technology, Mandigobindgarh, Punjab, in 2008, the M.Tech degree in Automation & Manufacturing from Shri Mata Vaishno Devi University, Katra, India, in 2013, with 90 percent. He was in industry from 2008 to 2010 as production manager. Presently he is working as Assistant Professor cum Head of Mechanical Engg Department in Arni University, indora from 2014 to present. 120 International Journal of Research in Mechanical Engineering & Technology www.ijrmet.com