ARTICLE Year : 2012  Volume : 2  Issue : 1  Page : 16 Effect of Process Parameters on Kerf Width in WEDM for HSLA Using Response Surface Methodology Pardeep Gupta^{1}, Rajesh Khanna^{2}, Rahul Dev Gupta^{2}, Neeraj Sharma^{3}, ^{1} Department of Mechanical Engineering, Sant Logowal Institute of Engineering and Technology, Logowal, Punjab, India ^{2} Department of Mechanical Engineering, Maharishi Markandeshwer University, Mullana, India ^{3} Department of Mechanical Engineering, R.P. Inderaprastha Institute of Technology, Karnal, Haryana, India Correspondence Address: Wire electric discharge machine (WEDM) is a spark erosion machining process to cut very hard conductive material with the help of a wire electrode. High strength low alloy steel (HSLA) is a hard alloy with high hardness and wear resisting property. The purpose of this study is to investigate the effect of parameters on kerf width for WEDM using HSLA as workpiece. HSLA is used in cars, trucks, cranes, bridges, roller coasters and other structures that are designed to handle large amounts of stress. It is revealed that kerf width decreases with increase in pulse on time, pulse off time, spark gap voltage and peak current. Kerf width increases with increase in wire tension. In order to evaluate the effect of selected process parameters, the response surface methodology (RSM) is used to formulate a mathematical model which correlates the independent process parameters with the desired kerf width. The central composite rotatable design has been used to conduct the experiments. The analysis of results indicates that the spark gap voltage, pulse on time, peak current and pulse off time have a significant effect on kerf width.
1. Introduction Wire electric discharge machine (WEDM) has been an important manufacturing process for the tool, mould, automobiles and die industries. Due to the ability to make intricate shape and machining of hard material with WEDM, its use is increasing. WEDM has capability to machine any kind of electrically conductive work in the present day. The mechanism of WEDM constitutes the erosion of material due to discrete spark discharge between wire tool and job immersed in a liquid dielectric medium. The microprocessor also constantly maintains the gap between the wire and the workpiece, which varies from 0.025 to 0.05 mm. Very high frequency pulses are generated with the help of DC power supply. The electrical discharge melts or erodes the material in a very small amount which is flushed away by dielectric. The workpiece and wire electrode are separated by deionized water. The deionized water works as dielectric fluid and flushes out the eroded or melted material. WEDM is rarely able to achieve optimal performance due to large number of variables and their stochastic nature. This problem can be solved by determining the relationship between performance of the process and its input parameters using designed experiments. In 1991, Williams and Rajurkar [1] observed that the complex and random nature of the erosion process in WEDM requires the application of deterministic and stochastic techniques. They present the results of their investigations into the characteristics of WEDM generated surfaces on D2 tool steel that higher peak current resulted in a rougher surface and some amount of the wire electrode material from WEDM gets deposited onto the workpiece surface. Gokler and Ozanozgu (2000) [2] have performed experiments on 1040 steel material of thicknesses 30, 60 and 80 mm and on 2379 and 2738 steel materials of thicknesses 30 and 60 mm for investigating the surface roughness. Tosun and Cogun (2004) [3] presented an investigation on the effect and optimization of machining parameters on the kerf (cutting width) and material removal rate (MRR) for AISI 4140 steel in WEDM operations. The experimental studies were conducted varying pulse duration, open circuit voltage, wire speed, and dielectric flushing pressure. The settings of machining parameters were determined by using Taguchi experimental design method. Newman et al. [4] found that WEDM is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes. In their research work, they found that maximum of work is carried on the development and controlling of WEDM, while a little is occurred on the parametric optimization. Puri and Bhattacharya [5] have carried out an experimental investigation for M2 die steel using L27 orthogonal array. The main influencing factors are determined for given machining criteria, such as average cutting speed, surface finish characteristic, and geometrical inaccuracy caused due to wire lag. Also, the optimum parametric settings for different machining situations have been found out. Mamalis et al. [6] reported in their research that requirements of the materials used for WEDM electrodes that will lead to the improvement of WEDM performance. Material used for experimentation is annealed steel with low carbon content. Liao et al. [7] proposed an approach of determining the parameter settings based on the Taguchi quality design method and the analysis of variance for SKD11 alloy steel and brass wire of 0.25 mm diameter as tool electrode. The results showed that the MRR and SF are easily influenced by the table feed rate and pulse on time, which can also be used to control the discharging frequency for the prevention of wire breakage. Hewidy, Taweel and Safty [8] highlighted the development of mathematical models for correlating the various WEDM machining parameters of Inconel 601 material such as peak current, duty factor, wire tension and water pressure with the metal removal rate, wear ratio and surface roughness. In addition, Scott et al. [9] used a factorial design requiring a number of experiments to determine the most favorable combination of the WEDM parameters. They found that the discharge current, pulse duration and pulse frequency are the significant control factors affecting the MRR and SF on sintered NdFeB magnet, titanium, and carboncarbon bipolar plate, while the wire speed, wire tension and dielectric flow rate have the least. I. Cabanes [10] found that the main challenge in WEDM is avoiding wire breakage and unstable situations as both phenomena reduce process performance and can cause lowquality components. They develop a realtime control strategy for increasing the performance of WEDM process. Singh and Garg [11] found that the MRR of H11 steel directly increases with increase in pulse on time (TON) and peak current (IP) while decreases with increase in pulse off time (TOFF) and servo voltage (SV). Till now there is no work carried out using HSLA as a die material. As it is hard, wear resistant and corrosion resistant, so HSLA is chosen as a workpiece for experimentation. To evaluate the effects of machining parameters on performance characteristics, and to identify the optimal performance characteristics under the best settings of machining parameters, a specially designed experimental procedure called Response Surface Methodology has been used. 2. Materials and Methods Process Parameters of Wedm Based on the findings of the many researchers, process parameters for WEDM process based on the quality of the machining are grouped in various categories. The process parameters, their designated symbols and range are given in [Table 1]. {Table 1} The range of all the process parameters is selected for this study based on the results obtained from preliminary experiments. The chemical composition and mechanical properties of HSLA are shown in [Table 2] and [Table 3] respectively.{Table 2}{Table 3} 2.1 Experimental Methodology The experimental studies were performed using an Electronica Sprintcut 734 WED machine tool. During the experiments the cutting of the workpiece was done. The size of workpiece is 5 mm × 5 mm × 18 mm. The work material, electrode, and the other machining condition are as follows: Workpiece: High strength low alloy steelElectrode (tool): 250 μm φ, CuZn37 Master Brass wire (900 N/mm 2 tensile strength)Workpiece height: 18 mmConductivity: 20 mhoCutting voltage (V): 80VDieelectric temperature: 35°CInjection pressure set point was at 7 kg/cm 2Peak voltage (VP): Setting 2Servo feed: 2050 units 2.2 Response Surface Methodology For the present work, RSM has been applied for developing the mathematical models in the form of multiple regression equations for the quality characteristics of WEDM process. In applying the RSM, the dependent parameter was viewed as a surface to which a mathematical model is fitted. For the development of regression equations related to various quality characteristics of WEDM process, the secondorder response surface has been assumed as: [INLINE:1] This assumed surface Y contains linear, squared and cross product terms of parameters x i 's. In order to estimate the regression coefficients, a number of experimental design techniques are available. Box and Hunter [12] have proposed a scheme, based on central composite rotatable design, which fits the secondorder response surfaces very accurately. Also, no replication is needed to find error mean square. The error mean square can be found out by replicating the center points. 3. Results The 32 experiments were conducted according to the central composite secondorder rotatable design for investigating kerf width. The experimental data along with the experimental design matrix [13] are given in [Table 4]. {Table 4} For analyzing the data, the checking of goodness of fit of the model is very much required. The model adequacy checking includes test for significance of the regression model, test for significance on model coefficients and test for lack of fit. For this purpose, analysis of variance (ANOVA) is performed. 3.1 Analysis of KERF Width The fit summary recommended that the quadratic model is statistically significant for analysis of kerf width. The pooled ANOVA for kerf are given in [Table 5], [Table 6]. From the pooled ANOVA analysis, the value of R2 and adjusted R2 is over 95%. This means that regression model provides an excellent explanation of the relationship between the independent variables (factors) and the response kerf. The associated Pvalue for the model is lower than 0.05 which indicates that the model is considered to be statistically significant. The lackoffit term is nonsignificant as it is desired. Further APulse on time, BPulse off time, CSpark gap voltage, DPeak current, EWire Mechanical Tension, Interaction between pulse on time and pulse off time, pulse on time and peak current, servo voltage and wire mechanical tension, also the secondorder factors of pulse on time and spark gap voltage having significant effect. The other model terms are said to be insignificant. To fit the quadratic model for kerf appropriate, the insignificant terms are eliminated by backward elimination process.{Table 5}{Table 6} The reduced model results indicate that the model is significant (R2 and adjusted R2 are 98.63% and 97.76% respectively), lack of fit is non significant as Pvalue is 0.5012 (and significant value is less than 0.05). [Figure 1] displays the normal probability plot of the residuals for kerf. It is noticed that the residuals are falling on a straight line, which means that the errors are normally distributed. It satisfies the conditions of normal distribution curve, which is reliable. {Figure 1} [Figure 2] shows the distribution curve between the predicted versus actual. As the residuals are randomly distributed, so it follows a constant variance which is desired. It can be seen that the regression model is fairly well fitted with the observed values. After eliminating the nonsignificant terms, the final response equation for kerf is given as follows: Kerf Width = +5554.5892981.85714*T on 17.44048*T off 7.43452*SV+1.66667*IP+5.18750*WT+0.33532*Ton 2 +0.036429*SV 2 +0.13393*T on *T off 0.021528*T on *IP+0.034821*T off *SV+0.014792*SV*IP0.084375*SV*WT{Figure 2} 4. Discussion The response surface is plotted to study the effect of process variables on the gap current and is shown in [Figure 3], [Figure 4], [Figure 5] and [Figure 6]. From [Figure 3], it is seen that the kerf width decreases with increase in pulse on time. A probable reason for it may be that with increase in pulse on time, discharge energy increases causing evenly distribute the spark which decreases the kerf width. As in [Figure 4], interaction plots of spark gap voltage and pulse off time are illustrated, with the increase of pulse off time and spark gap voltage the kerf width decreases, this is due to the fact that with the decrease of discharge duration, the overcut during discharge also increases as the discharge energy per pulse increases [14] . [Figure 5] shows the interaction plot of spark gap voltage and peak current. The effect of spark gap voltage is already explained, while with the increase of peak current kerf width decreases. The main reason behind this is that higher the peak current, higher will be the spark energy. This high spark energy produces larger amount of debris. The debris sticks on the workpiece trap and may cause unwanted spark. The unwanted sparks result in tool material erosion, which results in less material removal, as the significant amount of spark energy is used in sparking with debris, leading to less kerf width [15] . Interaction plots of spark gap voltage and wire tension are illustrated in 6. The effect of SV is already explained, while with the increase of wire tension the kerf width increases but not at so much significantly.{Figure 3}{Figure 4}{Figure 5}{Figure 6} References


