International Journal of ChemTech Research CODEN (USA): IJCRGG ISSN: 0974-4290 Vol.8, No.8, pp 278-285, 2015 Investigation of Electro Chemical Micro Machining process parameters on Al- SiCp - Gr Composites using Taguchi Methodology B.Babu 1 *, S.Dharmalingam 1, S.K. Karthikeyan 2, R.Karthik 2, V.Vairamani 2 1 Department of Mechanical Engineering, Rathinam Technical Campus, Coimbatore, Tamilnadu, India. 2 Department of Mechanical Engineering, Kongunadu College of Engineering and Technology Tamilnadu, India. Abstract: This paper investigates the influence of the process parameters like machining voltage, electrolyte concentration, frequency on the over cut and Material Removal Rate (MRR). This paper discusses a methodology for the optimization of the machining parameters on drilling of Al- SiCp - Gr Metal Matrix composites using EMM. The taguchi L 27 orthogonal array and analysis of variance are employed to study the influence of machining parameters such as machining voltage, Electrolyte concentration, Frequency on the over cut and MRR. Keywords: Metal Matrix Composite (MMCs), Material Removal Rate (MRR), Overcut, Electrochemical micromachining (EMM), Taguchi, ANOVA &Design of Experiment. 1. Introduction EMM is a nontraditional non contact [tool and work piece] machining process in which material is removed by the mechanism of anodic dissolution during an electrolysis process. MMCs having outstanding properties like high modules, low ductility, high thermal conductivity and low thermal expansion, high strength-to-weight ratio, high toughness, high-impact strength, high wear resistance, low sensitivity to surface flaws, and high surface durability. As a result, many of the current applications for MMCs are in many industrial applications including electronics, bio medicine, optics, bio technology, home appliances, Fuel injection system components, ordnance components mechanical machine parts like turbine blades, engine castings, bearing cages, gears, dies and molds and all other major parts in automobile and aerospace industries. Electrochemical machining is widely recognized that has great potential and many applications in micromachining. The micro hole is the most demanding important basic element while fabricating the micro parts and micro devices which are best made through EMM. 2. Literature Review Most of the current literature presents experimental results in terms of tool life, quality of drilled hole, and induced force when drilling MMCs. Shorter pulse period machining voltage produces lower side gap and it also increases the unit removal 1. Analysis of variance (ANOVA) was used for identifying the significant
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 279 parameters affecting the responses. In Taguchi s analysis method, the design parameters and noise parameters which influence the product quality are considered 2-4. Electrochemical micromachining (ECMM) is an emerging nonconventional technology for producing micro/meso scale components. Investigates the effect and parametric optimization process parameters of electro chemical micro machining of 304 stainless steel 5, have conducted experiments with the developed setup by varying the machining voltage, electrolyte concentration, pulse-on time, and frequency on copper plate. In the study, they reported that a considerable amount of MRR at a moderate accuracy can be achieved with a machining voltage of 6 10 V, pulse-on time of 10 15 ms, and electrolyte concentration of 15 20 g/l. The micro ECM process is complex, and it is not easy to decide the optimal machining parameters for improving the output quality. The optimization of process parameters is essential for the realization of a higher productivity, which is the preliminary basis for survival in today s dynamic market conditions. Optimal quality of the work piece in ECM can be generated through combinational control of various process parameters 4,6. An attempt made to machine the composite work material using the ECM process to study the effects of various parameters such as applied voltage, electrolyte concentration, and frequency on maximizing the MRR and minimizing overcut 4,6. 3. Experimental Details 3.1 Fabrication Of Al 6061-5 % wt of SiC p 5 % wt of Gr Hybrid Metal Matrix Composite The aluminum matrix is reinforced with 5 % wt of SiC p / 5 % wt of Gr. The average particle size SiC p was 50 microns and Gr was 70 microns. The aluminum alloy was preheated in a resistance furnace at 450º C for 2 hour before melting. SiC p and Gr were also preheated in a resistance furnace at 1200º C for 3 hour. The preheated aluminum were first heated above the liquidus temperature to melt them completely, and then slightly cooled below the liquidus to maintain the slurry in the semi-solid state. This procedure has been adopted while stir casting aluminum composites 2,4,9. The preheated reinforcements were added and mixed manually. Manual mixing was used because it was very difficult to mix using automatic device when the alloy was in a semi-solid state. The composite slurry was then reheated to a fully liquid state, and mechanical mixing was carried out for about 20 min at an average mixing speed of 300 rpm. The final temperature was controlled to be within 750 C ± 20 C, and pouring temperature was controlled to be around 700 C. After thorough stirring, the melt was poured into steel molds of size 100x100x10 mm and allowed to cool to obtain cast sheet. Then the thickness was reduced to 0.5 mm through rolling and the same was cut in to 50x50x0.5 mm used as work-piece in EMM. 3.2 Electro-Chemical Micro Machining EMM (Figure 3.2) is one of the nonconventional machining processes. It offers the unique advantage of better accuracy with high surface integrity of hard-machined components; also it has wider application because it produces good quality surfaces without affecting the metallurgical properties of the work material. During ECM, there will be reactions occurring at the electrodes i.e. at the anode or work-piece and at the cathode or the tool along with within the electrolyte. Ion and electrons crossing phase boundaries (the interface between two or more separate phases, such as liquid-solid) would result in electron transfer reaction carried out at both anode and cathode. It does not induce any deformation because no heat is generated while machining. Tool electrode feeding system, electrolyte supply system, mechanical machining system, inter electrode gap control system, pulse rectifier system are the major components of the EMM. The tool electrode feed mechanism, with resolution of 2 µm along Z axis designed with stepper motor and 8051 micro controller. The electrolyte supply system consists of filter and pump arrangement. A pulsed power supply of 20 v and 30 A with capability for varying voltage, current, and pulse width was used. The electrolyte of varying concentrations used in this study was sodium nitrate (NANO 3 ) and Al - SiCp - Gr of thickness of 0.4 mm as work piece. Based on the literature review and preliminary experiments conducted, the initial process parameters and their corresponding levels are chosen. The work piece thickness 0.4 mm, machining current 0.8 A as fixed for entire experiment. Table 2 shows the machining parameters and their level indentified for this investigation. Electrochemical micro machining (EMM) characteristics (MRR and Overcut) as output responses for through micro hole machining. MRR was derived as work piece removal weight over machining time. Overcut of the micro hole has been related with the machining accuracy, hence it is the difference between the diameters of the tool electrode and machined micro hole. With the support of optical microscope the diameter of the machined micro hole was measured.
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 280 Fig 3.1 Stir Casting Set Up Fig 3.2 EMM Set Up 3.3 Methodology The optimization of process parameters is the key step in the Taguchi method. Twenty seven experimental runs (L 27 ) based on the Orthogonal Array (OA) of Taguchi methods have been carried out. The multi-response optimization of the process parameters viz. MRR, Over cut has been performed for making a micro hole in the process of micro-ecm of hybrid Al- SiCp - Gr metal matrix composites, each experiment was replicated twice. Machining time, over cut, MRR noted for every trial. There are three categories of quality characteristic in the analysis of the S/N ratio: 1. Larger is better 2 Nominal is best 3. Smaller is best Larger is better The signal-to-noise (S/N) ratio is calculated for each factor level combination. The formula for the larger-is-better S/N ratio using base 10 log is: S/N = - 10log [sum (1/Y 2 )/n)] where Y = responses for the given factor level combination and n = number of responses in the factor level combination. Nominal is best (I) The signal-to-noise (S/N) ratio is calculated for each factor level combination. The formula for the nominal-is-best I S/N ratio using base 10 log is: S/N = -10 log ( 10 s 2 ) where s = standard deviation of the responses for all noise factors for the given factor level combination. Nominal is best (II) The signal-to-noise (S/N) ratio is calculated for each factor level combination. The formula for the nominal-is-best II S/N ratio using base 10 log is: S/N = 10 log((y 2 ) / s 2 ) where Y = mean of responses for the given factor level combination, s = standard deviation of the responses for the given factor level combination, and n = number of responses in the factor level combination. Smaller is better The signal-to-noise (S/N) ratio is calculated for each factor level combination. The formula for the smaller-is-better S/N ratio using base 10 log is: S/N = -10 log [sum(y 2 )/n)] where Y = responses for the given factor level combination and n = number of responses in the factor level combination. In this study higher MRR and Lower over cut are desired. Therefore MRR is Larger is better and Overcut is Smaller is better chosen for this study.
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 281 4. Results and Discussions 4.1 Single Response Optimization Of Machining Parameters For The Drilling Of Al 6061-5% SiC p - 5%Gr The assignment of factors with their levels indentified for this investigation is given in Table 4.1. Based on Taguchi s L 27 OA, drilling experiments were conducted on EMM of Al 6061-SiC-Gr. The experimental results such as MRR and Overcut were gathered for each trial and it is shown in Table 4.1. S/N ratios were calculated for all the responses since the objective of this work was the maximization of MRR and the minimization of Overcut. Therefore, MRR is larger-is-better and for overcut, smaller-is-better type was considered for the analysis. The S/N ratio for larger-is-better type is given by the equation and smaller-is-better is given by the equation. The S/N ratio was computed using the equations for each of the twenty-seven trial conditions for the MRR and Overcut and is shown in Table 4.1. Figure 4.1 and 4.2 shows the optical image for micro-hole of Al 6061-SiC-Gr MMC. The optimal setting levels for each factor resulting from the S/N ratios were shown in Table 4.2. Table 4.1 Experimental results for L 27 OA of Al 6061- SiC p -Gr MMC S/N ratio of MRR and Overcut Trial MRR S/N Ratio for S/N Ratio for V E F Overcut µ m No mg/min MRR Overcut 1 6 20 30 0.19 212.46-14.42-46.55 2 6 20 40 0.218 167.32-13.56-44.47 3 6 20 50 0.3 141.67-10.75-43.03 4 6 25 30 0.374 156.2-8.874-43.87 5 6 25 40 0.354 125.62-9.37-41.98 6 6 25 50 0.3 143.44-10.75-43.13 7 6 30 30 0.364 145.65-9.119-43.27 8 6 30 40 0.31 173-10.17-44.76 9 6 30 50 0.343 169.86-9.63-44.6 10 8 20 30 0.281 129.4-11.37-42.24 11 8 20 40 0.208 171.1-13.98-44.67 12 8 20 50 0.291 138.92-11.06-42.86 13 8 25 30 0.198 116-14.42-41.29 14 8 25 40 0.406 138.14-8.179-42.81 15 8 25 50 0.229 155.86-13.15-43.85 16 8 30 30 0.374 89.4-8.874-39.03 17 8 30 40 0.280 152-11.06-43.64 18 8 30 50 0.270 76.6-11.37-37.68 19 10 20 30 0.177 162.72-15.39-44.23 20 10 20 40 0.239 187-12.77-45.44 21 10 20 50 0.218 161.16-13.56-44.15 22 10 25 30 0.322 149-10.17-43.46 23 10 25 40 0.198 212.46-14.42-46.55 24 10 25 50 0.218 167.32-13.56-44.47 25 10 30 30 0.302 141.67-10.75-43.03 26 10 30 40 0.374 156.2-8.874-43.87 27 10 30 50 0.354 125.62-9.37-41.98
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 282 Figure 4.1 Optical image for Micro-hole Figure 4.2 Optical image for Micro-hole 8V /30 10V /20 g/l/40 Hz - Al 6061- SiC p -Gr MMC g/l/40 Hz - Al 6061- SiC p -Gr MMC 4.2 Analysis for MRR of Drilling Al 6061-5% SiC p -5% Gr MMC Figure 4.3 shows the main effects at each level. It can be seen that the optimal values for the maximum MRR is the machining voltage of 6 V, electrolyte concentration of 30 g/l and frequency of 40 Hz. Figure 4.4 shows the residual plot for MRR. Table 4.2 shows the response table for S/N ratio of MRR. Figure 4.5 shows the interaction plot for S/N ratio of MRR. The interaction plot has been plotted to pictorially depict the interactions process parameters on MRR. In the full interaction plot, two panels per pair of process parameters have been shown. It shows that the MRR is maximum in the combination value of lower voltage, higher electrolyte concentration and medium frequency. Table 4.2 Response table for the MRR of drilling Al 6061- SiC p -Gr MMC Signal-to-noise ratios (larger-is-better) Level Voltage (V) Electrolyte concentration (E) Frequency (F) 1-10.739-12.984-11.489 2-11.496-11.434-11.375 3-12.096-9.913-11.466 Delta 1.357 3.070 0.184 Rank 2 1 3 Figure 4.3 S/N ratio graph for the MRR of drilling Al 6061- SiC p -Gr MMC R esidual P lots for M R R No rm a l P ro b a b ilit y P lo t Versus Fits 99 0.10 90 Percent 50 Residual 0.05 0.00 10-0.05 1-0.10-0.05 0.00 0.05 0.10-0.10 0.20 0.24 0.28 0.32 0.36 Residual Fitted V alue Histogram Versus Order 8 0.10 Frequency 6 4 2 Residual 0.05 0.00-0.05 0-0.0 75-0.0 50-0.025 0.000 0.02 5 R esid ua l 0.050 0.075 0.100-0.10 2 4 6 8 10 12 14 16 18 20 22 24 26 Observation Order Figure 4.4 Residual graph for the MRR of drilling Al 6061- SiC p -Gr MMC
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 283 Figure 4.5 Interation plot for the S/N ratios of MRR of drilling Al 6061- SiC p -Gr MMC 4.3Analysis for Overcut of Drilling Al 6061-5% SiC p -5% Gr MMC Table 4.3 shows the response table for S/N ratio of overcut and its ranked order. Figure 4.6 shows the main effects at each level. It can be concluded that the optimal values for the minimum overcut is machining voltage of 8 V, electrolyte concentration of 30 g/l and frequency of 50 Hz. Table 4.3 Response table for overcut of drilling Al 6061- SiC p -Gr MMC Signal-to-noise ratios (smaller-is-better) Level Voltage(V) Electrolyte concentration (E) Frequency ( F ) 1-43.96-44.18-43.00 2-42.01-43.49-44.24 3-44.13-42.43-42.86 Delta 2.12 1.75 1.38 Rank 1 2 3 Figure 4.6 S/N ratio graph for overcut of drilling Al 6061- SiC p -Gr MMC Figure 4.7 Residual graph for overcut of drilling Al 6061- SiC p -Gr MMC Figure 4.7 shows the residual plot for over cut. Figure 4.8 shows the interaction plot for S/N ratio of overcut. The interaction plot was made to pictorially reflect the interactions of the process parameters on overcut. In the full-interaction plot, two panels per pair of process parameters were shown. It shows that overcut is maximum in the combination value of medium voltage, higher electrolyte concentration and higher frequency.
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 284 Figure 4.8 Interation Plot for the S/N ratios of overcut of the drilling Al 6061- SiC p -Gr MMC 4.4 Confirmatory Test for the drilling of Al 6061-5% SiC p -5%Gr The experimental data obtained are compared with the values predicted by the developed model and presented in Table 4.4 and 4.5. Table 4.4 shows the S/N ratio of the predicted MRR and the actual MRR. Based on the Confirmatory test, the MRR is improved by 63.15 % with respect to the initial parametric setting. Therefore, the parametric combination suggested for the higher MRR is the machining voltage of 6 V, electrolyte concentration of 30 g/l and frequency of 40 Hz. Table 4.4 Confirmatory test table for MRR of drilling Al 6061- SiC p -Gr MMC Optimal combination levels of machining Initial levels of parameters machining parameters Prediction and Experiment Improvement Level V 1 E 1 F 1 V 1 E 3 F 2 MRR (mg/min) 0.19 0.31 63.15 % Table 4.5 shows the comparison of the S/N ratio of the predicted overcut with the actual overcut. Based on the Confirmatory test, the Overcut is improved by 63.95 % with respect to the initial parametric setting. The parameter combination suggested for the lesser overcut is machining voltage of 8 V, electrolyte concentration of 30 g/l and frequency of 50 Hz. Table 4.5 Confirmatory test table for overcut of drilling Al 6061- SiC p -Gr MMC Initial levels of machining parameters Optimal combination levels of machining parameters Prediction and Improvement experiment Level V 1 E 1 F 1 V 2 E 3 F 3 Overcut (µ m) 212.46 76.6 63.95 % 5. Conclusions The Present investigation is focused on optimization and analysis electrochemical micro machining of Al 6061- SiC p -Gr metal matrix composites machining parameters. From the study of result in EMM was using Taguchi s techniques and ANOVA. The following can be concluded from the present study. 1. Based on the confirmation test, the improvements of the MRR from the initial machining parameters to the optimal machining parameters are about 63.15 %. 2. The optimal values for maximum MRR were machining voltage of 6 V, an electrolyte concentration of 30 g/l and a frequency of 40 Hz.
B.Babu et al /Int.J. ChemTech Res. 2015,8(8),pp 278-285. 285 3. Based on the confirmation test, the improvements of the Overcut from the initial machining parameters to the optimal machining parameters are about 63.95 %. 4. The optimal values for minimum Overcut were machining voltage of 8 V, an electrolyte concentration of 30 g/l and a frequency of 50 Hz. 5. The results of ANOVA, the Voltage and Frequency are the significant machining parameters for affecting the MRR. Similarly the electrolyte concentration and Frequency are the significant machining parameters for affecting the Over cut. 6. References 1. Malapati Manoj Kumar Reddy, Influence of Pulse Period and Duty Ratio on Electrochemical Micro Machining (EMM) Characteristics, International Journal of Mechanical Engineering and Applications. Vol. 1, No. 4, 2013, pp. 78-86. 2. Dharmalingam, S, Marimuthu, P, Raja, K, Pandyrajan, R & Surendar S 2014, Optimization of process parameters on MRR and overcut in electrochemical micro machining on metal matrix composites using grey relational analysis, International Journal of Engineering and Technology, vol. 6, no. 2, pp. 519-529. 3. K. Chandrasekaran, P.Marimuthu and K.Raja, Prediction model for CNC turning on aisi316 with single and multilayered cutting tool using box behnken design (research note), IJE Transactions A: Basics Vol. 26, No. 4 (April 2013) 401-410. 4. Dharmalingam, S, Marimuthu, P & Raja, K 2014, Machinability study on Al- 10% TiC composites and optimum setting of drilling parameters in electrochemical micro machining using grey relational analysis, Int. Journal of Latin American Applied Research, vol. 44, no.4, pp. 331-338. 5. R.Thanigaivelan, RM Arunachalam, optimization of process parameters on machining rate and over cut electro chemical micro machining using grey relational analysis, Journal of scientific and industrial research,vol. 72, January2013, pp. 36-42. 6. Dharmalingam, S, Marimuthu, P, Raja, K, Nithyapathi, C, Babu, B & Siva, M 2014, Experimental investigation on electrochemical micro machining of Al-10%wt SiCp based on Taguchi design of experiments, Int. Journal Review of Mechanical Engineering, vol. 8, no. 1, pp. 80 88. 7. B.Babu, K.Raja, S.Dharmalingam, S.Udhataraj, V.Vairamani, Electrochemical Micro Machining on Hybrid Metal Matrix Composites, International Journal of ChemTech Research, Vol.8, No.2, pp 508-518, 2015. 8. T.Florence, S.Dharmalingam, V.Ragupathy, P.Satishkumar, Machinablity study on Electrochemical Machining A Review, International Journal of ChemTech Research, Vol.7, No.6, pp 2596-2600, 2015. 9. P.Satishkumar, S.Dharmalingam, K.Raja, K.Lingadurai, G.Padmanaban, 2015, Investigation on Electrochemical Micro Machining of Al 6061-6% wt Gr based on Taguchi design of experiments, International Journal of ChemTech Research, Vol.7, No.01, pp 203-211. *****