A Comparative Optimization on Process Parameters of Wire Electrical Discharge Machining of Inconel-690 using Taguchi method

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1 A Comparative Optimization on Process Parameters of Wire Electrical Discharge Machining of Inconel-690 using Taguchi method 1 Raju Kumar Thakur, 2 Dr. N. Selvaraj 1,2 Dept. of Mechanical Engineering, National Institute of Technology, Warangal, India Abstract Wire Electrical Discharge Machining (WEDM) is the Nontraditional machining process which is most preferred for the machining of hard material. In this paper, Inconel-690 (Nickelchromium based alloy) is used as work material. Two wire material namely brass and zinc-coated brass wire each of 0.25 mm are used for the study of the process performance like kerf width, and. The input process parameters considered Pulse on time, Pulse off time, Peak current and Servo voltage. Taguchi design of L9 orthogonal array is used to optimize the process performance. For the analyse of experimental results, analysis of variance is used to check the percentage contribution of each input process parameter on Kerf Width, and. Optimum level value of Process performance provides the best suitable wire for kerf width, and. Keywords WEDM,,, Kerf Width, Taguchi Method, ANOVA I. Introduction As mechanical industry developed, the requirement of hard material has increased. Traditional methods are not sufficient for machining of hard material. WEDM is a non traditional method which is capable for the machining of hard material. In WEDM, the accurate position of workpiece and wire feeding system are established. A series of spark is produced on material with the help of wire, there is no contact between work material and wire. coolant such as de-ionized water is suppied continuously on the machining zone by using nozzle. It also removes eroded material from the machining zone of work material. Fig. 1: Wire EDM Process Diagram 2. Literature Review Several researchers have optimized performance responses such as Material Removal Rate, Surface Roughness and Kerf width. A.V.S Ram Prasad, et al [1] used titanium alloy as work material of size 110 x 89 x 11 mm and 0.25mm brass is used as wire material. Pulse on time, servo voltage, pulse off time and peak current are selected as input process parameter. It is found that pulse on time has highest effect on kerf width and surface roughness. Pulse on time has 77.92% effect on material removal rate and 66.83% effect on surface roughness. Pulse on time and peak current was the most important parameter for material removal rate and surface roughness whereas pulse off time and servo voltage was the less effective parameter. Chiang et al [2] used Al2O3 reinforced material. Pulse on time, pulse off time, servo voltage, arc on time, arc off time and water flow are used as an input process parameter to optimize and using grey relational analysis. Sudhir Ashok Shardul, et al [3] used Graphite Plate as work material and 0.25mm brass is used as wire material. Pulse on time, pulse off time, wire tension and peak current are selected as input process parameter. Based on taguchi method, L9 orthogonal array is used for design of experiment. By changing the different level value based on taguchi method, surface roughness and material removal rate are investigated. By ANOVA analysis, it is found that wire tension has more effect on and (contribute about 41.89% on and 64.27% on ). Pradeep kumar karsh, et al [4] used inconel 625 as work material of size 440 x 650 mm and 0.25mm copper is used as wire material. Pulse on time, pulse off time and peak current are selected as input process parameter. Based on taguchi method, L9 orthogonal array is used for design of experiment. It is found that surface roughness increases as pulse on time increases but decreases as pulse on time increases. By ANOVA analysis, it is found that pulse on time effects more (contribute about 92.35%). S.R.Dhale, et al [5] used inconel 718 as work material of size 150 x 150 x 8 mm and two wires namely brass and zinc coated brass wire each of 0.25mm are used as wire material. Pulse on time, pulse off time, wire material, wire tension, wire feed and flushing pressure are selected as input process parameter. Wire material has two levels and all other input process parameter have three level values. Based on taguchi method, L18 orthogonal array is used for design of experiment. By changing the different level value based on taguchi method, surface roughness and are investigated. Percentage contribution of each input process parameter is analysed by ANOVA analysis. is more affected by pulse on time and wire material. and are more by using zinc coated brass wire. By ANOVA analysis, it is found that pulse on time effects more compared to other input process parameter. Neeraj, et al. [6] used Inconel 600 as work material and zinc coated brass wire is used for the machining of Inconel 600. The input process parameters is used pulse on time, pulse off time, wire feed, wire tension and peak current to investigate Surface Roughness and Wire wear ratio. Pulse on time, pulse off time and peak current are major effect on. U. A. Dabade, et al. [7] used Inconel 718 as work material and zinc coated brass wire is used for machining of Inconel 718 using L8 orthogonal array. The input process parameters considered as pulse on time, pulse off time, peak current, wire feed, wire tension and spark gap set voltage has been their effect on,, Kerf width and Dimensional deviation. It was observed that pulse on time is the 48 International Journal of Research in Mechanical Engineering & Technology

2 ISSN : (Online) ISSN : (Print) most important factor for all the response variables,, Kerf width and Dimensional deviation. Venkaiah N, et al [8] used Inconel 690 as work material and 0.25mm zinc coated brass is used as wire material. Pulse on time, pulse off time, servo voltage and peak current are selected as input process parameter. Total 60 experiments were conducted; a 6.5mm thick plate was used on which 10mm holes were produced. ANN model was used to predict the circularity error. It was found that circularity error increases as pulse on time and pulse off time inceases whereas servo voltage increases then circularity error decreases. Siva Prasad Arikatla, et al. [9] used titanium as work material and diffused brass wire as electrode. It is observed that pulse on time, pulse current and servo voltage are mostly influences the Kerf width and increases. Rodge M. K, et al [10] used inconel 625 as work material of size 100 x 30 x 10 mm and 0.25mm brass is used as wire material. Pulse on time, pulse off time, wire tension, wire feed, upper flush and lower flush are selected as input process parameter. All input process parameter have five level values. Based on taguchi method, L25 orthogonal array is used for design of experiment. By changing the different level value based on taguchi method wire wear, kerf width and hardness are investigated. Percentage contribution of each input process parameter is analysed by ANOVA analysis. Kerf width is most affected by pulse on time whereas wire wear is most affected by wire feed and hardness is most affected by pulse off time. It is found that kerf width increases as pulse on time increases which results in lower wire wear. Sarvesh Shivanand Rane, et al [11] used Inconel 800 as work material and 0.18mm molybdenum is used as wire material. Pulse on time, pulse off time, servo voltage, bed speed and peak current are selected as input process parameter. Voltage has two level values whereas all other input process parameter has three level values. Based on taguchi method, L18 orthogonal array is used for design of experiment. By changing the different level value based on taguchi method, surface roughness and material removal rate are investigated. Percentage contribution of each input process parameter is analysed by ANOVA analysis. Peak current has highest effect on material removal rate whereas pulse on time has highest effect on surface roughness. Peak current has 39% effect on material removal rate and pulse on time has 32% effect on surface roughness. III. Material Selection Inconel-690 (a nickel-chromium alloy) is used as work material in the present experimental investigation. Chemical composition of inconel 690 is shown in Table 1. Table 1: Chemical Composition of Inconel 690 INCONEL 690 Elements Specifications (%) Nickel Iron 8.70 Chromium Titanium 0.27 Silicon 0.66 Aluminium 0.96 IV. Experimental Setup In the current study all the experiments were performed on a ELECTRONICA machine which is shown in fig. 2. The workpiece is a block of Inconel 690 with length 100mm x width 150mm x IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 thickness 10mm. brass and zinc-coated brass of 0.25mm thickness is used as electrode. The cuts of 20 mm depth along the length are taken. Fig. 2: CNC Wire Cut EDM V. Experimental Design In this experiment, Pulse on time, pulse off time, peak current and Servo voltage is used as input process parameter to investigate Kerf width (mm), Material Removal Rate (mm 3 /min) and Surface Roughness (μm). Each input process parameter is assigned three level value. The range of level value for input process parameters are Ton ( µs), Toff (57-63 µs), Ip (10-12 A) and Sv (40-80 V) respectively as it is shown in Table 2. Minitab 17 Software is used for orthogonal array as it is shown in Table 3. Table 2: Level Values of Input Parameter S. No Parameters Level-1 Level-2 Level-3 1 Pulse on time Pulse off time Peak Current Servo Voltage Table 3: Design of L9 Orthogonal Array S. No Pulse on time Pulse off time Peak Current Servo Voltage A. Kerf Width (KW) Kerf is the amount of the material wasted during machining. During machining the main aim is to maximum and minimum Kerf width. It is measured by optical micrometer. B. Material Removal Rate () The material removal rate is the amount of the material removed per minute. Material removal rate is calculated by using the formula = V/t mm 3 /min Where V = Volume of material (mm 3 ) and t = Time of machining in minute. w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 49

3 C. Surface Roughness () Roughness checks of the texture of a surface. Surface roughness tester is used to measure surface roughness. Table 7: Response Table for S/N ratios for Delta Rank Table 8: Analysis of Variance for Fig. 3: Surface Roughness Tester VI. Result and Discussion A. For Brass Wire By performing the experiment using brass wire, the value of, and Kerf width is obtained. The results are investigated by S/N Ratios, Response graph, Response table with the help of Minitab 17 Software. Minitab 17 software helps to calculate S/N Ratio according to response value as shown in Table 14 and provides percentage contribution of each input parameters using Analysis of variance and also provides response plot for optimum combination of input process parameter for desired responses. Table 4: Results of Experiments S. No Time (Min) Kerf Width (mm) KW (mm 3 / min) (µm) Table 9: Response Table for S/N ratios for Delta Rank Table 10: Analysis of Variance for Table 5: Response Table for S/N Ratios for Kerf Width Delta Rank Table 6: Analysis of Variance for Kerf Width Fig. 4: Graphs for Kerf Width 50 International Journal of Research in Mechanical Engineering & Technology

4 ISSN : (Online) ISSN : (Print) IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t Confirmation Experiment Pick the optimum condition from S/N Ratio graph, for each response process parameter and at optimum condition, experiments are performed and experimental value is compaired with predicted value given by minitab 17 software, for Kerf width as shown in Table 11, for as shown in Table 12 and for as shown in Table 13. However error can be minimized if more number of experiments for measurement is performed. Table 11: Result of Confirmation Experiment for KW Optimal Level A1-B2-C3-D1 A1-B2-C3-D1 KW (mm) Kerf Width Fig. 5: Graphs for Material Removal Rate Table 12: Result of Confirmation Experiment for Optimal Level A2-B3-C2-D1 A2-B3-C2-D1 (mm3/min) Table 13: Result of Confirmation Experiment for Optimal Level A1-B3-C2-D1 A1-B3-C2-D1 Optimal Level (µm) Fig. 6: Graphs for Surface Roughness The aim of the experiment is to obtain the optimum factors level value which strongly affects the machining performance. From mean of S/N ratios (Table 5) for kerf width, it is found that peak current has highest rank 1, so it has main effect on kerf width. Pulse off time has least effect on kerf width. Anova analysis (Table 6) gives the percentage contribution of each input process parameter. The optimum condition for kerf width (smaller is better) is obtained from S/N ratio graph (Figure 4), the optimal combination of level value is found to be A1-B2-C3-D1. From mean of S/N ratios (Table 7) for, It is found that peak current has highest rank 1. So it has main effect on. Pulse-on time has least effect on. Anova analysis (Table 8) gives the percentage contribution of each input process parameter. The optimum condition for (larger is better) is obtained from S/N ratio graph (Fig. 5), the optimal combination of level value is found to be A2-B3-C2-D1. From mean of S/N ratios (Table 9) for, It is found that peak current has highest rank 1, so it has main effect on. Pulse off time has least effect on Surface roughness. Anova analysis (Table 10) gives the percentage contribution of each input process parameter. The optimum condition for surface roughness (smaller is better) is obtained from S/N ratio graph (Fig. 6), the optimal combination of level value is found to be A1-B3-C2-D1. B. For Zinc-Coated Brass Wire: By performing the experiment using Zinc coated brass wire, the value of, and Kerf width is obtained. The results are investigated by S/N Ratios, Response graph, Response table with the help of Minitab 17 Software. Minitab 17 software helps to calculate S/N Ratio according to response value as shown in table 14 and provides percentage contribution of each input parameters using Analysis of variance and also provides response plot for optimum combination of input process parameter for desired responses. Table 14: Results of Experiments S. No Time (Min) Kerf Width (mm) KW (mm 3 / min) (µm) w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 51

5 Table 15: Response Table for S/N ratios for Kerf Width Delta Rank Table 16: Analysis of Variance for Kerf Width Fig. 7: Graphs for Kerf Width Table 17: Response Table for S/N ratios for Delta Rank Table 18: Analysis of Variance for Fig. 8: Graphs for Material Removal Rate Table 19: Response Table for S/N Ratios for Delta Rank Table 20: Analysis of Variance for International Journal of Research in Mechanical Engineering & Technology Fig. 9: Graphs for Surface Roughness The aim of the experiment is to obtain the optimum factors level value which strongly affects the machining performance. From mean of S/N ratios (Table 15) for kerf width, it is found that peak current has highest rank 1, So it has main effect on kerf width. Pulse-on time has least effect on kerf width. Anova analysis (Table 16) gives the percentage contribution of each

6 ISSN : (Online) ISSN : (Print) input process parameter. The optimum condition for kerf width (smaller is better) is obtained from S/N ratio graph (Figure 7), the optimal combination of level value is found to be A1-B2-C3-D2. From mean of S/N ratios (Table 17) for, It is found that peak current has highest rank 1. So it has main effect on. Pulse-on time has least effect on. Anova analysis (Table 18) gives the percentage contribution of each input process parameter. The optimum condition for (larger is better) is obtained from S/N ratio graph (Figure 8), the optimal combination of level value is found to be A3-B2-C3-D2. From mean of S/N ratios (Table 19) for, It is found that pulse on time has highest rank 1, therefore it has main effect on. Pulse off time has least effect on Surface roughness. Anova analysis (Table 20) gives the percentage contribution of each input process parameter. The optimum condition for surface roughness (smaller is better) is obtained from S/N ratio graph (Figure 9), the optimal combination of level value is found to be A3-B1-C3-D1. 1. Confirmation Experiment Pick the optimum condition from S/N Ratio graph for each response process parameter and at optimum condition, experiments are conducted and obtained experimental value is compaired with predicted value given by minitab 17 software at optimum condition, for Kerf width as shown in table 21, for as shown in table 22 and for as shown in table 23. However error can be minimized if more number of experiments for measurement is performed. Table 11: Result of Confirmation Experiment for KW Optimal Level A1-B2-C3-D2 A1-B2-C3-D2 KW (mm) Kerf Width Table 12: Result of Confirmation Experiment for Optimal Level A3-B2-C3-D2 A3-B2-C3-D2 (mm 3 /min) Table 13: Result of Confirmation Experiment for Predicated Value Experimental Value % error Optimal Level A3-B1-C3-D1 A3-B1-C3-D1 Optimal Level (µm) VII. Comparision of Optimized Result Using Brass and Zinc Coated Brass Wire Comparison of optimum experimental value for Kerf width, material removal rate and surface roughness is shown in fig. 9. Figure indicates that zinc coated brass wire gives 6.53% higher kerf width, 19.23% higher material removal and 14.49% higher surface roughness than brass wire KW IJRMET Vo l. 7, Is s u e 2, Ma y - Oc t 2017 BRASS ZINC COATED BRASS Fig. 10: Comparison of Process Performance of Brass and Zinc Coated Brass Wire VIII. Conclusion In the present experimental work, Inconel 690 is used as workpiece and two wires namely brass and zinc coated brass wire each of 0.25mm is used. Performance parameter such as kerf width, material removal rate and surface roughness are obtained at different level values of process parameters namely pulse on time, pulse off time, peak current and servo voltage. For any material, minimum kerf width is desirable. It is found that zinc coated brass wire produces more kerf width so brass wire is better than zinc coated brass wire for minimum kerf width. Material removal rate produced by zinc coated brass wire is more than brass wire. Since Maximum is desirable so zinc coated brass wire is used for maximum. Zinc coated brass wire produces more than brass wire. Since minimum surface roughness is desirable so brass wire is better than zinc coated brass wire for minimum surface roughness. References [1] A.V.S Ram Prasad, Koona Ramji, G.L.Datta, An experimental study of wire edm on ti-6al-4v alloy, International Conference on Advances in Manufacturing and Materials Engineering, Procedia Materials Science 5 (2014) pp [2] Chiang, K.T., Chang, F.P, Optimization of the wedm process of particle- reinforced material with multiple performance characteristics using grey relational analysis, Journal of Materials Processing Technology, 180, 2006, pp [3] Sudhir Ashok Shardul, Sachin K. Dahake, Parametric optimization on graphite plate by wedm, International Research Journal of Engineering and Technology, Vol. 02, Issue 09, [4] Pradeep Kumar Karsh, Hari Singh, Optimization of process parameters for surface roughness of inconel 625 in wire edm by using taguchi method, ISOR Journal-JMCE. [5] S. R. Dhale, M. L. Kulkarni, Effect of electrode coatings in wire electrical discharge machining of inconel-718, IO Journal-JMCE; Vol. 13, Issue 4, pp , [6] Neeraj, Ashwani Mor, Balinder Singh,"Review of various performance parameters of wire electrical discharge machining using taguchi analysis, International Journal of Enhanced Research in Science, Technology & Engineering, Vol. 4 Issue 10, October [7] U. A. Dabadea, S. S. Karidkarb, Analysis of response variables in wedm of inconel 718 using taguchi technique, 48th CIRP Conference on Manufacturing Systems - CIRP CMS 2015, Procedia CIRP 41 (2016) pp w w w.i j r m e t.c o m International Journal of Research in Mechanical Engineering & Technology 53

7 [8] Sreenivasa Rao M, Venkaiah N, Modeling of Circularity error while machining inconel-690 using wedm, International Journal of Applied Engineering Research, Vol. 11, No. 6, pp , [9] Siva Prasad Arikatla, Dr K.Tamil Mannan, Dr Arkanti Krishnaiah, Ch.V.Krishna Rao, Surface integrity of wire electrical discharge machined surface of titanium alloy, International Journal of Advances in Mechanical & Automobile Engg. (IJAMAE) Vol. 3, Issue 1, pp , [10] Rodge M. K, Sarpate S. S, Sharma S. B, Investigation on process response and parameters in wire edm of inconel 625, IJMET, Vol. 4, Issue 1, [11] Sarvesh Shivanand Rane, Dr. C.P.S Prakash, Selection of optimal process parameters in machining aerospace material by wire electrical discharge machining process, International Journal for Scientific Research & Development, Vol. 3, Issue 09, Raju Kumar Thakur received his B.Tech degree in Mechanical Engineering from Darbhanga College of Engineering, Darbhanga, Bihar, India. The M.Tech degree in Computer Integrated Manufacturing from National Institute of Technology Warangal, Telangana, India, in Dr. N. Silvaraj is a professor in Mechanical Engineering Department in National Institute of Technology Warangal. He has completed his P.hd degree in Production Engineering from National Institute of Technology Warangal. 54 International Journal of Research in Mechanical Engineering & Technology