A Parametric Optimization of Electric Discharge Drill Machine Using Taguchi Approach

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1 A Parametric Optimization of Electric Discharge Drill Machine Using Taguchi Approach Samar Singh, Lecturer, Dept of Mechanical Engineering, R.P. Indraprastha Institute of Technology (Karnal) MukeshVerma, Associate Professor, Dept of Mechanical Engineering, Shri Sukhmani Institute of Technology ABSTRACT Electric Discharge Drill Machine (EDDM) is a spark erosion process to produce micro holes in conductive materials. This process is widely used in aerospace, medical, dental and automobile industries. As for the performance evaluation of the Electric discharge drilling machine it is very necessary to study the process parameters of machine tool. In this research paper a brass rod 2 mm diameter was selected as a tool electrode. The experiments generate output responses such as material removal rate (MRR). The best parameters such as pulse on-time, Pulse off-time and water pressure were studied for best machining characteristics. This investigation presents the use of Taguchi approach for better MRR in drilling of Al A plan of experiments, based on L27 Taguchi design method, was selected for drilling of material. From the analysis of variance (ANOVA) shows the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination levels and the significant drilling parameters on MRR were obtained. The optimization results showed that the combination of maximum pulse on-time and minimum pulse off- time gives maximum MRR. Keywords: Electric discharge drilling Machining, MRR, ANOVA, Taguchi Method.. Introduction and Literature Review For small hole Electrical Discharge Machining (EDM) Drilling is quickly becoming the standard method for producing small, tight tolerance holes. It is an extremely cost effective method for producing fast and accurate holes into all sorts of whether hard or soft conductive materials []. Electrical Discharge Machining (EDM) is the process of machining electrically conductive materials by using precisely controlled sparks that occur between an electrode and a workpiece in the presence of a dielectric fluid. EDM is based on the erosion of electrically conductive materials through the series of spatially discrete high-frequency electrical discharges (sparks) between the tool and the workpiece. Fig. illustrates that each spark occurs between the closest points of the electrode and the workpiece. The spark removes material from both the electrode and workpiece, which increases the sparking gap (distance between the electrode and the workpiece) at that point. This causes the next spark to occur at the next-closest points between the electrode and workpiece. As EDM is a thermal process, material is removed by heat. Every discharge (or spark) melts a small amount of material from both of the electrodes.part of this material is removed by the dielectric fluid and the remaining solidifies on the surface of the electrodes. Micro-EDM is a machining process that is known to be capable of drilling burr-free holes in a wide range of materials regardless of their hardness as long as the material is electrically conductive. In micro-hole drilling, the most common technique involves making the electrode from a high temperature material such as tungsten (W), either by circular grinding with a diamond abrasive wheel or by wire electrical discharge grinding (WEDG). The diameter of the electrode is carefully matched to the size of hole to be drilled by considering the radial overcut of the EDM process. This overcut is a function of various EDM parameters such as the spark voltage, the discharge current, spark on- and off-time, but also the type of dielectric fluid EDM drilling operates on the principal of eroding material via the use of electric energy. There are many advantages of using fast EDM drilling versus conventional drilling: -Some materials are too hard to drill using conventional methods. The EDM machine drills through almost any conductive material including carbide and hardened steel. Drills tend to bend in contact with the surfaces. To prevent this, additional fixtures and guide bushings must be used. With EDM drilling, the electrode never contacts the material being cut, thus eliminating the tool pressure normally experienced when drilling on curved or angled surfaces. Deburring holes drilled by conventional methods can take longer than the drilling. EDM drilling creates Blue Ocean Research Journals 39

2 no burrs. This burr-free drilling saves time and labour, and is especially crucial when difficult holes are being drilled. In addition, surface finishes are better. The smaller the hole, the more important a smooth surface is. [2] Drilling holes with conventional methods is often extremely difficult if not impossible. EDM drilling is often the only practical method for producing such holes. As conventional drills enter or exit, they can break if torque is not carefully controlled. Small broken drills are often difficult to remove from the workpiece, and time is wasted replacing broken drills and parts may have to be scrapped. With EDM drilling, torque does not exist since the electrode never contacts the piece [3].Some of the previous works that used the Taguchi method and response surface methodology as tools for the design of experiment in various areas including machining operations are listed in. The Taguchi method was used by Yang and Chen to find the optimum surface roughness in end milling operations[4]. 2. Sparking and gap phenomena in EDM The sparking phenomena during micro-edm can be separated into three important phases named as preparation phase for ignition, discharge phase and interval phase between discharges. When the gap voltage is applied an electric-field or energy column is created. The strength of the energy column increases with the decrease of the distance between electrode and workpiece [5]. Blue Ocean Research Journals 40

3 Fig.Step in EDM:(a)occurrence of spark at the closest point between workpiece and electrode,(b) melting and vaporization of workpiece and electrode materials during spark on time,(c)vaporized cloud of materials suspended in dielectric fluid,and(d) removal of molten metal and occurrence of next spark.[6] 3. Experimental Set-Up Experiments are performed on Electronica Make ED 300 Electric discharge drilling Machine. The goal is to obtain the best machining parameters resulting in Maximum MRR and minimum TWR. Holes were made in a 9 mm thick plate of Al 7075 using a 2 mm diameter electrode of Brass. Fig. 2 Machine Tool Fig. 3 EDM drilling process Fig. 4(a) Electrodes Used for EDDM Fig. 4(b) Blue Ocean Research Journals 4

4 Before experimentation, the workpiece faces were rectified to a good surface finish using a surface grinding machine. The bottom of the electrode rod is polished for best electric contact at every experiment. The initial weight of the workpiece was precise weighed using an accuracy digital scale. The workpiece was connected to the terminals of power supply and clamped on the machine table. The dielectric fluid was flushed at a constant pressure in the gap between electrode and workpiece. Holes of 9 mm depth were drilled in all the experiments. The time taken for machining each hole was recorded. At completion of each hole the workpiece was removed from the machine, washed, dried, and weighted. The material removed rate was calculated using the following formula: [7] Table: Properties of Al-7075 Table 2: Chemical composition (wt %) Parameters values Density (g/cm3) 2.8 Hardness (HB) 60.0 Ultimate tensile 228 strength(mpa) Tensile yield strength 03 (MPa) Elongation at break (%) 6.0 Element % Wt Si 0.4 Fe 0.5 Cu Mn 0.3 Mg Cr Zn Ti 0.2 Others 0.5 Al Balance Table 3: Input Process Parameters and their Levels Sr. No Parameter Unit Level Level 2 Level 3 Pulse on-time (A) µs Pulse off-time (B) µs Water pressure (C) Kg/cm The Taguchi method involves reducing the variation in a process through robust design of experiments. The overall objective of the method is to produce high quality product at low cost to the manufacturer. The Taguchi method was developed by Dr. Genichi Taguchi of Japan who maintained that variation. Taguchi developed a method for designing experiments to investigate how different parameters affect the mean and variance of a process performance characteristic that defines how well the process is functioning. An L 27 orthogonal array has been employed as per Taguchi s method based robust design philosophy to evaluate the main influencing factors that affect the material removal rate (MRR).Three EDDM parameters factor A (Pulse on-time), factor B (Pulse off-time),factor C (Water pressure) are considered as the controlling factors for optimal analysis during drilling of Material.[8] Higher the Better Whose values are preferred when high, are calculated using this approach. Such factors are tool life, material removal rate, etc. The following equation is used to calculate the S/N ratio for HB type of characteristics. R (S/N) HB = -0 Log 2 R y j j Blue Ocean Research Journals 42

5 Fig. 5 Workpiece Profile 4. Results and Discussion The controllable variables chosen for the experimentation were peak current, pulse time-on and electrode rotation speed. Other factors such as voltage, (65 V), Air- pressure 3kg/cm 2, and flushing were kept constant during the experimentation. Table 4 shows the controllable parameters and actual values. Table 4: Metal removal Rate at specified Design of Experiments (L 27 ) Sr. No MRR(R) MRR(R2) MRR(R3) Sr.NO MRR(R) MRR(R2) MRR(R3) Selection of Optimal Levels To find the significance of the process parameters towards MRR ANOVA was performed. It was found that water pressure is non significant process parameter for MRR as revealed from Table 5. The pooled version of ANOVA of the SN data for MRR is given in Table 5 while Table 6 gives pooled analysis of variance for mean. From these tables this is found that pulse on time has the maximum contribution onto the MRR. While pulse-off time is significant and water pressure is non-significant for MRR. Blue Ocean Research Journals 43

6 Table 5: Pooled Analysis of Variance for SN ratios Source DF Seq SS Adj MS F P %P A B Residual Error Total DF - degrees of freedom, SS - sum of squares, MS - mean squares (Variance), F-ratio of variance of a source to variance of error, P < determines significance of a factor at 95% confidence level, p - % contribution Table 6 : Pooled Analysis of Variance for Means Source DF Seq SS Adj MS F P % P A B Residual Error Total DF - degrees of freedom, SS - sum of squares, MS - mean squares(variance), F-ratio of variance of a source to variance of error, P < determines significance of a factor at 95% confidence level Table: 7 Response Table for Means Level A B Delta Rank 2 ` From Fig 6 it is found that MRR increases with increases in pulse on- time. Time for which current is on increases, which may increases the spark energy consequently increases MRR. With increases in pulse off-time, MRR decreases. This is due to the fact that pulse off-time is the time for which current is off during a cycle. So with increases in pulse off time the current is decreases for a specified cycle and decreases spark energy consequently MRR decreases Blue Ocean Research Journals 44

7 Frequency Residual Percent Residual Mean of Means Journal of Engineering, Computers & Applied Sciences (JEC&AS) ISSN No: Main Effects Plot for Means Data Means A B Fig. 6 Main Effect plots for Means Residual Plots for Means 99 Normal Probability Plot Versus Fits Residual Fitted Value Histogram Versus Order Residual Observation Order Fig. 7 Residual Plots for Means Blue Ocean Research Journals 45

8 Fig. 7 revealed that the residual fall on a straight line is distributed normally. So the normality test has been verified and is found good. Versus fits shows the variation of residual versus fits. In this figure the values are not found in any order, this is sign of better results. It is found to be distributed randomly, hence it is the constant variance test which must be structure less for better result, and figure made no structure so the test is verified. Optimum Value of Material removal Rate (MRR): Optimum value of MRR is predicted at the selected levels of significant variables Pulse on-time, Pulse off- time, water pressure. The estimated mean of the response characteristic can be determined as µ mrr = A 3 + B -(T ) Where, T = overall mean of material removal rate (MRR) = ( R + R 2 + R 3 )/8 = μm where, R =0.6408, R 2 =0.6399, R 3 =0.622 Where R, R 2, and R 3 values are taken from the Table 4. And the values of A 3 and B are estimated from the experimental data reported in the same table. A 3 = average value of MRR at the third level of Pulse on- time = gm/s B = average value of MRR at the first level of pulse off -time = gm/s Substituting the values of various terms in the above equation, µ mrr = = gm/s The 95 % confidence intervals of confirmation experiments (CI CE ) and population (CI POP ) are calculated as: n eff = 8 / (+4) = 6.2 N = Total number of results = 27 x 3 =8, R = Sample size for confirmation experiments = 3 V e = Error variance = fe = error DOF = 4 F 0.05 (, 4) = (Tabulated F value (Ross, 996)) So, CI CE = ± CI pop = ± Therefore, the predicted confidence interval for confirmation experiments is: Mean μ MRR CI CE < μ MRR < Mean μ MRR + CI CE i.e < μ MRR < The 95% confidence interval of the population is: Mean μ MRR CIPOP < μ MRR < Mean μ MRR + CI POP i.e < μ MRR < The optimal values of process variables at their selected levels are as follows: ( A 3 ) : 8 µs; ( B ):6 µs 5. CONFIRMATION EXPERIMENT Confirmation Experiment is plays an important role in any parametric optimization of any machine tool, as in Confirmation experiment set the significant parameters according to our optimal values which are find out by Taguchi approach. After set the machine tool at the optimum setting and check the response at this setting to find the actual value of the response. In Table 8 optimal setting of the parameters are shown and also the actual value of the response is calculated. Blue Ocean Research Journals 46

9 Table 8: Predicted Optimal Values, Confidence Intervals and Results of Confirmation Experiments Performance Measures/ Responses Optimal Set of Parameters Predicted Optimal Value Predicted Confidence Intervals at 95% confidence level Actual value(average of three confirmation experiments MRR A 3 B CI CE : < μ mrr < CI POP : < μ mrr < CONCLUSION Influences of EDDM process parameters on MRR of Al 7075 were investigated in this paper. ANOVA shows that Pulse on time (A) has the maximum contribution i.e. 94% on MRR and Pulse off time has 4 % contribution on MRR. It is also concluded from this research that with increase of pulse on time MRR increases and with the increase of Pulse off time MRR decreases. (A 3 ) 8 µs, (B ) 4 µs, is the optimized setting of machine tool for the present study. [8] Singh H, Khanna R (20) Parametric optimization of Cryogenic treated D-3 for cutting rate in wire electrical discharge machining. J Eng Technology, Vol. (2), References [] Anon., 977. EDM electrodes in orbit. Tooling Prod. 43 (7), 04. [2] Bamberg, E., Heamawatanachai, S., Jorgensen, J.D. (2005). Flexural micro-edm head for increased productivity of micro-hole, Proceedings of the 2005 ASPE Conference, [3] Carl Somer, Complete EDM Handbook, USA, [4] Tosun N, Cogun C, Tosun G. (2004), A study on kerf and material removal rate in wire electrical discharge machining based on Taguchi method. J Mater Process Technol, Vol. 52, , [5] B.M. Schumacher (2004). After 60 years of EDM the discharge process remains still disputed, Journal of Materials Processing Technology, vol. 49, [6] E.C. Jameson (200), Description and development of electrical discharge machining (EDM), in: Electrical Discharge Machining, Society of Manufacturing Engineers, Dearbern, Michigan, 2. [7] Asokan T, Reddy SS, Costa - Electrical discharge drilling of titanium alloys for aerospace applications. Proceedings of 9th AIMTDR conference, Madras, Chennai, Blue Ocean Research Journals 47