ELECTRIC DISCHARGE MACHINING AND MATHEMATICAL MODELING OF Al-ALLOY-20 % SiC p COMPOSITES USING COPPER ELECTRODE

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1 International Journal of Mechanical and Production Engineering Research and Development (IJMPERD ) ISSN Vol.2, Issue 2 June TJPRC Pvt. Ltd., ELECTRIC DISCHARGE MACHINING AND MATHEMATICAL MODELING OF Al-ALLOY-20 % SiC p COMPOSITES USING COPPER ELECTRODE 1 RAJESH PUROHIT & 2 PRAMOD SAHU 1 Mechanical Engineering Department,Maulana Azad National Institute of Technology, Bhopal, (M.P.) India Engineer,Indian Airlines, India. ABSTRACT For the last few decades Al-SiC particulate composites have found wide spread applications in automotive, aircraft, defense and household appliances. However, these materials are hard to machine due to the abrasive nature of the reinforcements present in them. Electrical discharge machining has been proved to be an important process for machining of these metal matrix composites. The present work reports on the effect of pulse-on time (Ton), pulse current (Ip), and gap voltage (Vg) on metal removal rate (MRR), tool wear rate (TWR) and radial over cut (ROC) during machining of Al-alloy- 20 wt. % SiC p composites. The experiments were conducted on EZNC EDM machine using 20 mm diameter copper electrode. Three level 3 factor full factorial design of experiment technique was used for the analysis. Analysis of variance (ANOVA) was also performed. A mathematical model was also developed to relate the output and input variables. The MRR was found to increase with increase in current and pulse duration. TWR was also found to increase with increase in current. However the TWR was found to first decrease and then increase with pulse duration and gap voltage. KEY WORDS: Metal matrix composites; EZNC EDM, Design of experimental technique; Analysis of variance. INTRODUCTION In the past twenty years, research and development in materials has shifted from monolithic to composite materials, in order to fulfill the global need of lightweight, low cost, high quality, performance and durability materials for diverse applications. Additionally, researchers are turning to particulatereinforced aluminum matrix composites (AMCs) because of their relatively low cost and isotropic properties especially in those applications not requiring extreme loading or thermal conditions (e.g. automotive components). The metal matrix composite (MMC) are a type of composite material with metal as the matrix material, which is reinforced with hard ceramic fiber, whisker or particulates that impart a combination of properties not achievable in either of constituents individually. When at least three materials are present, it is called a hybrid composites. MMCs are well known for their superior mechanical properties

2 Rajesh Purohit & Pramod Sahu 38 over those of un-reinforced alloys. However, in view of difficulties encountered during machining of these composites like high tool wear and high tooling cost with conventional machining, nonconventional machining processes such as the electric discharge machining (EDM) are finding advantages in shaping of theses composite materials. EDM is a method involving electrical discharges between an electrode and a conductive work piece in a dielectric medium. Material is removed from the work piece by a controlled electrical spark between an electrode and the work piece material. The dielectric fluid becomes ionized during the course of discharge. As ionization occurs, the electrons strike the work piece while positively charged ions strike the electrode, increasing the temperature at the surface of the work piece and electrode. The temperature is so high at the surface, often reaching more than 10,000 C, which causes the work piece to melt or vaporize immediately. EDM of LM 25 Al-alloy-SiC composites using copper electrode was done by Karthikeyan et al. (1999) and the effects of volume percent of SiC, current and pulse duration on MRR, TWR and surface roughness were studied. Singh et al. (2004) have studied the effect of current, pulse on time and flushing pressure on MRR, TWR, taper and surface roughness using 2.7 mm diameter electrode. MRR was found to be higher for larger current and pulse on time setting at the expense of taper, ROC and surface finish. TWR was also found to be higher, larger then MRR for larger current setting. The effects of current, volume percent of SiC and pulse duration on MRR, EWR and surface roughness during EDM of 6025Al-SiC composite were studied by Mohan et al. (2004). The pulse duration was found to have inverse effect on material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR). Genatic algorithm was used for optimization of process parameters. Dhar et al. (2007) have studied the effect of current, pulse on time and gap voltage on MRR, TWR and ROC during EDM of Al-4Cu-6Si alloy-10 wt. % SiC p composites using 30 mm diameter brass electrode. It was reported that the MRR, TWR and ROC increases in a non linear fashion with increase in current. MRR and ROC increases with increase in pulse on time. The present work attempt to study the effects of input parameter viz. current, voltage and pulse on time on Tool wear rate, Metal removal rate and Radial over cut during the electro discharge machining of Al-alloy-20 wt. % SiC p composites. The effects were studied using a design of experiment technique with 3 level-3 factor full factorial design. A mathematical model was developed to predict the MRR, TWR and Radial over cut within the operating region. A statistical analysis to verify the results was also done.

3 39 Electric Discharge Machining and Mathematical Modeling of Al-Alloy-20 % SiC p Composites using Copper Electrode EXPERIMENTAL PROCEDURE Machining parameters Three important machining parameters viz. current, voltage and pulse on time were identified and their levels were fixed as shown in Table 1. Response variables In the present work three important response variables viz. material removal rate (MRR), tool wear rate (TWR) and radial over cut (ROC) were measured and studied. Material removal rate (MRR) MRR is expressed as the ratio of the difference of weight of the work piece before and after machining to the machining time. MRR = (W 2 -W 1 )/t (1) Where, W 2 is the weight of the work piece before machining, W 1 is the weight of the work piece after machining t is the machining time Tool Wear Rate (TWR) TWR is expressed as the ratio of the difference of weight of the tool before and after machining to the machining time. TWR = (W 2 -W 1 )/t (2) Where, W 2 is the weight of the tool before machining, W 1 is the weight of the tool after machining, and t is the machining time Radial Over Cut (ROC) ROC is expressed as half the difference of diameter of the hole produced to the tool diameter, i.e. ROC = (D 2 -D)/2 (3) Where, D 2 is hole diameter at top. D is the diameter of the tool electrode

4 Rajesh Purohit & Pramod Sahu Other Parameters Al alloy-20 wt. % silicon carbide particulate composite plates were drilled using 20 mm diameter copper electrode on an EZNC EDM Machine. Positive polarity was maintained for the work piece and negative polarity for the tool. Kerosene oil was used as the dielectric fluid and impulse jet flushing was used to flush away the eroded materials from the sparking zone. Table 2 shows the miscellaneous parameters used during EDM of Al-20 wt. % SiC p composites. Table 1 : Machining parameters and their Level Machining Parameter Symbol Unit Level one Level two Level three Current I Ampere Voltage V Volt Pulse-on time Ton Micro second Table 2 : Miscellaneous parameters used during EDM of Al-20 wt. % SiC p composites Parameters Settings Diameter of electrode Work piece 20 mm. 220mm X 120mm X 7mm Sensitivity 8 Duty cycle 7 T w T Pressure during machining 0.6 Seconds 1.2 Seconds 5 psi DESIGN OF EXPERIMENT Experimental methods are widely used in research as well as in industrial settings, however, sometimes for very different purposes. The primary goal in scientific research is usually to show the statistical significance of an effect that a particular factor exerts on the dependent variable of interest. In industrial settings, the primary goal is usually to extract the maximum amount of unbiased information regarding the factors affecting a production process from as few observations as possible.

5 41 Electric Discharge Machining and Mathematical Modeling of Al-Alloy-20 % SiC p Composites using Copper Electrode A. Three-level full factorial designs The three-level full factorial design is written as a 3 k factorial design. It means that k factors are considered, each at 3 levels. These are (usually) referred to as low, intermediate and high levels. These levels are numerically expressed as 1, 0 and 1. One could have considered the digits 0, 1, and 2 i.e. we can also use the 0, 1, 2 scheme. The reason that the three-level designs were proposed is to model possible curvature in the response function and to handle the case of nominal factors at 3 levels. A third level for a continuous factor facilitates investigation of a quadratic relationship between the response and the factors. The 3 3 factorial design consists of three factors, each at three levels. It can be expressed as a 3 x 3 x 3 = 3 3 design. The model for such an experiment is Here each factor is included as a nominal factor rather than as a continuous variable. In such cases, main effects have 2 degrees of freedom, two-factor interactions have 2 2 = 4 degrees of freedom and k- factor interactions have 2 k degrees of freedom. The model contains = 26 degrees of freedom. Note that if there is no replication, the fit is exact and there is no error term (the epsilon term) in the model. In this no replication case, if one assumes that there are no three-factor interactions, then one can use these 8 degrees of freedom for error estimation. In this model we see that i = 1, 2, 3, and similarly for j and k, making 27 treatments. MODELING OF EXPERIMENTS The purpose of developing the mathematical model relating the response variables and the input process parameters was to facilitate the optimization of the electric discharge machining of aluminum matrix composites. The mathematical model commonly used is represented by: Y = φ(v, I, T) Where Y is the response, φ is the response function and V (gap voltage), I (pulse current) and T (pulse duration) are the process variables. In this study the model chosen was quadratic in nature involving linear and quadratic interactions of process variables. A program was written in MAT LAB to obtain the desired model (Montgomery, 2001). EXPERIMENTAL DATA The experimental readings of the MRR, TWR and ROC for different combination of input parameters are shown in Table 3.

6 Rajesh Purohit & Pramod Sahu 42 Table 3 : Observation Table S. No. Input parameters V T on I Time Taken (min.) Upper Dia(d 1 ) (mm) Lower Dia(d 2 ) (mm) Tool wear (Grams) TWR x10-5 (gm/sec) ROC (mm) M.R. Grams) MRR x 10-5 (gm/sec)

7 43 Electric Discharge Machining and Mathematical Modeling of Al-Alloy-20 % SiC p Composites using Copper Electrode ANALYSIS OF VARIANCE A factorial ANOVA can examine data that are classified on multiple independent variables. It can show whether there are significant main effects of the independent variables and whether there are significant interaction effects between independent variables in a set of data. Interaction effects occur when the impact of one independent variable depends on the level of the second independent variable. For the above data related to Material removal rate, Sum of Square (SS) values and Mean Square (MS) values are calculated and corresponding F and P values were obtained. MATHEMATICAL MODELING OF EXPERIMENTS Let x1, x2, x3 denote the variable values of levels for the factors- Gap Voltage (V), Pulse Duration (T on ) and Current (I) respectively. Based upon the experimental design the possible values of either x1, x2 or x3 are 1, 0 and 1. The various combination of such sets of readings correspond to a variety of experiments as shown in Table 3. With the aid of computer program developed in MAT LAB, the mathematical formulae for the experiments were determined subject to same work piece and other machining conditions. TWR = * x * x * x * x1 * x * x2 * x * x3 * x * x1 * x * x1 * x * x2 * x3 MRR = * x * x * x * x1* x * x2 * x x3 * x * x1 * x * x1 * x * x2 * x3 ROC = * x * x * x * x1*x * x2*x * x3*x * x1*x * x1*x * x2*x3 RESULTS Main effects plot for Material Removal Rate (MRR), Tool Wear Rate (TWR), Radial Over Cut (ROC) are shown in Figures 1, 2 and 3 respectively. The summary of ANOVA for MRR, TWR and ROC are shown in Table 4, 5 and 6 respectively. Metal Removal Rate (MRR) The MRR is found to increase in an almost linear fashion with increase in current for constant gap voltage and Pulse on time. MRR is also found to increase slightly with increase in Pulse duration as shown in Fig. 1 and is in agreement with the literature reported in (5). Tool Wear Rate (TWR) TWR is also found to increase with increase in current as shown in Fig. 2, since high current results in higher thermal loading on both electrodes (tool and work-piece) leading to higher amount of material being removed from either. It is found to first decrease and then increase with pulse duration. A similar trend is noticed with gap voltage.

8 Rajesh Purohit & Pramod Sahu 44 Radial Over Cut (ROC) From Fig 3, it is evident that an increase in current increases the radial over cut. An increase in pulse duration also increases the radial over cut due to the prolonged presence of sparks. However the ROC decreases with increase in gap voltage. Table 4 : Summary of ANOVA for Material Removal Rate Source Degrees of freedom SS MS F value P value Regression Residual Error Total Table 5 : Summary of ANOVA for Tool Wear Rate Source Degrees of freedom SS MS F value P value Regression Residual Error Total Table 6 : Summary of ANOVA for Radial Over Cut Source Degrees of freedom SS MS F value P value Regression Residual Error Total

9 45 Electric Discharge Machining and Mathematical Modeling of Al-Alloy-20 % SiC p Composites using Copper Electrode Figure 1 : Main effects plot of MRR with Gap Voltage, Pulse Duration and Current respectively Figure 2 : Main effects plot of TWR with Gap Voltage, Pulse Duration and Current respectively Figure 3 : Main effects plot of ROC with Gap Voltage, Pulse Duration and Current respectively

10 Rajesh Purohit & Pramod Sahu 46 CONCLUSIONS 1. The MRR increases with increase in gap voltage, current and pulse duration. 2. TWR increases with increase in current. 3. TWR first decreases then increases with increase in gap voltage and pulse duration. 4. The ROC decreases with increase in gap voltage. 5. The ROC increases with increase in current and pulse duration. ACKNOWLEDGEMENTS The authors are very thankful to A. V. Muley, Akhilesh Karana, Ashish Bewal and Sunil Kumar Kesla (NSIT, New Delhi) for their cooperation in the experimental work. REFERENCES 1. Dhar, S., Purohit, R., Saini, N., Sharma, A. and Hemath Kumar, G. (2007). Mathematical modeling of electric discharge machining of cast Al-4Cu-6Si alloy-10 wt.% SiC p composites. Journal of Materials Processing Technology, 194, Karthikeyan, R., Lakshmi Narayanan, P.R. and Naagarazan, R.S. (1999). Mathematical modeling for electric discharge machining of aluminum-silicon carbide particulate composites. Journal of Materials Processing Technology, 87, Mohan, B., Rajadurai, A., Satyanarayana, K.G. (2004). Electric discharge machining of Al-SiC metal matrix composites using rotary tube electrode. Journal of Materials Processing Technology, , Montgomery, D.C. (2001). Design and Analysis of Experiments, Fifth edition, Wiley, New York. 5. Singh, P.N., Raghukandan, K., Rathinasabapathi, M. and Pai, B.C. (2004). Electric Discharge machining of Al-10 % SiC P as cast metal matrix composites. Journal of Materials Processing Technology, ,