Study of water assisted dry wire-cut electrical discharge machining

Transcription

1 Indian Journal of Engineering & Materials Sciences Vol. 1, February 014, pp Study of water assisted dry wire-cut electrical discharge machining S Boopathi* & K Sivakumar Department of Mechanical Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode , India Received 9 October 01; accepted 16 September 013 In the modern manufacturing industries, one of the challenges is to reduce the environmental impacts by the machining processes. In this article, the minimum quantity of tap water mixed with compressed air is used as a dielectric fluid in wirecut electrical discharge machining (WEDM) which promotes the green manufacturing environment. Four input process parameters have been considered such as the pulse width (PW), discharge current (I), air inlet pressure (P) and flow rate (F) of mixing water to study the parametric effects on the material removal rate (MRR) and surface roughness (R a ). High speed steel (HSS) is used as a work material which is one of the key materials to manufacture the cutting tools of the conventional machining process. Central composite design (CCD) of response surface methodology (RSM) has been used to conduct the design of experiments and to develop the regression models for the output parameters. It was observed from response surface analysis that PW, I and F are the significant process parameters and optimum responses (maximum MRR and minimum R a ) have been achieved at the moderate air pressure (5 bar). Keywords: Dry WEDM, High speed steel, Water assisted air dielectric, Material removal rate, Surface roughness, Central composite design Most of manufacturing industries are expecting the high performance of the machine tools. So that, many of the manufacturing researches are focused to improve the performance of the machine tools by changing the essential factors such as change of working medium, pulse shape, work material and tool materials. However, minimization of environmental impacts has also been an important role for manufacturers all around the world, especially after the introduction of ISO environmental management system standards 1. WEDM is one of the important machine tools to cut the high toughest material with the high aspect ratio and precisions. Dielectric fluid is used to flushout the eroded materials and to provide the dielectric strength in the cutting zone of WEDM process. The liquid dielectric medium provides good machining performance like material removal rate and surface finish. However, liquid dielectric fluid evaporates and emits the smokes during thermal erosion process. The smokes contain carbon monoxide, nitrogen oxide, xylene, formaldehyde and toluene 1,. These are harm-full and affect the health of WEDM operators. Thus, the replacement of liquid dielectric fluid is essential to reduce the environmental impacts. *Corresponding author ( boopasangee@gmail.com) In this vision, some experimental studies were performed to improve the performance of a dry EDM/WEDM by assisting the ultrasound, magnetic and rotation of the electrode and work piece 3-5. Kao et al. 6 conducted the experiments in near-dry EDM and reported that MRR is improved by using the minimum quantity of liquid with air as a dielectric fluid. The mathematical models were also developed for dielectric strength, spark gap, dynamic viscosity and water mixture ratio based on liquid and air properties 6. Tao et al. 7 conducted many experiments based on pure gases and mixing of liquid and gas like air, oxygen, nitrogen and helium, de-ionized water, and kerosene 7. The experiments were conducted in near-dry EDM and reported 8 the effect of the pulse width and pulse interval on the machining rate and surface roughness. They also reported that the effect of different gases and liquid mixtures on the MRR and surface roughness in the near-dry EDM. Fujiki et al. 9 developed the computational fluid dynamics (CFD) model of dielectric fluid flow to predict the air-liquid mist flow rate, MRR and R a in near-dry EDM milling. It was observed that only a few researchers attempted to optimize the input process parameters in the near-dry EDM/WEDM to improve the MRR and surface finish. Sourabh and Choudhury 10 developed an empirical model for MRR and R a using a response

2 76 INDIAN J. ENG. MATER. SCI., FEBRUARY 014 surface method. Jia et al. 11 investigated that the near-dry milling EDM process to machine the satellite alloys and important output parameters of MRR, R a and tool wear were optimized using response surface method. Recently, a systematic experimentation 1 using Taguchi L8 orthogonal array has been performed to understand the influence of processing parameters and helium gas dielectric on MRR, TWR, oversize and depth achieved. It was observed that helium gas is a significant role to reduce the thermal damage on machined surfaces, lower material deposition on tool and optimum oversize of machined hole 1. It is witnessed from aforementioned literatures that very few studies tried in the dry and near-dry EDM process and there is hardly any parametric study found in dry and near-dry WEDM process to cut the hard or alloy materials. It was also observed from the literature that dry WEDM process has very low MRR and poor surface finish. Higher thermal load, wire breakage, low MRR and surface finish, welding of wire tool with the work piece are the problems faced during the dry WEDM experiments. Mixing of the minimum quantity of liquid with compressed air or gas as the dielectric medium is one of the solutions to overcome the issues faced by dry WEDM process. In this study, tap water assisted dry WEDM process has experimentally been performed using the CCD. A hydro-pneumatic circuit has been constructed to conduct the experiments in the existing WEDM machine. Regression models have been developed to plot the response surfaces which are used to study the influence of process parameters on MRR and R a. Experimentation Experimental set-up The tap water assisted dry WEDM experiments have been performed on automatic fuzzy controlled CNC wire-cut EDM machine (Model-DK770CH). WEDM machine tool descriptions and machining conditions are summarized in Table 1. A hydropneumatic circuit (Fig. 1) was constructed to mix the minimum quantity of tap water with compressed air. It consists of a compressor, a water reservoir, bi-axial hose, a nozzle, flow control valves and the pressure gauges. It can be used to control the tap water flow rate and air pressure into the cutting zone. Flow rate of mixing water with the air has been measured by collecting amounts of water in the vessel with respect to time. It can be changed while varying the air pressure of the reservoir. The two separate hoses (bi-axial) of 8 mm and 3 mm diameter are used to supply the air medium and water respectively. The compressed air and tap water are mixed together at the end of the bi-axial hoses. Then, water mixed air is passed through the mm outlet diameter of the nozzle. Thus, these are employed to provide the eco-friendly machining environment with cooling effect in the cutting zone and to flush-out the eroded materials. The material chosen for this study was HSS which is a key material to manufacture the cutting tool of conventional machine tools. 6 mm thickness as a work piece and pure molybdenum wire of 0.18 mm diameter as a wire tool are used in these experiments. Tap water assisted dry WEDM process is shown in Fig.. Experimental procedure CNC program was made to cut a square profile of 5 mm 5 mm and the total length of cut is 0 mm. The time taken to cut the 0 mm length has been noted during the experiments. It is converted into Table 1 Water assisted dry WEDM machining conditions WEDM machine specification Wire tool Work piece Dielectric fluid Model Microcomputer controller Input power supply Input voltage Material Diameter Wire speed Material Thickness Composition Model-DK770CH CNC-E3 (MCJ) 03 Phase-AC, 380 V, 50 Hz 100 V (fixed) Molybdenum wire 0.18 mm 360 m/min (6 m/s) HSS - tool steel 6 mm Mixing of tap water with compressed air Fig. 1 Hydro-pneumatic circuit for water assisted dry WEDM

3 BOOPATHI & SIVAKUMAR: STUDY OF WATER ASSISTED DRY WIRE-CUT EDM 77 Parameters Table Process parameters and their levels of CCD Unit Levels Pulse width (PW) µs Discharge current (I) A Air inlet pressure (P) bar Mixing water flow rate (F) ml/min are randomly conducted and shown in Table 3. The coded values in terms of actual value for each process variable can be calculated using Eq. (1). Fig. Tap-water assisted dry WEDM process volume of material removal rate using the length of cut (0 mm), height of work piece (6 mm) and thickness of cutting path (0. mm). Surface roughness (R a ) is an important process parameter to measure the quality of machined product. A Mitutoyo surface tester was employed to measure R a. It has cut-off length of 0.8 mm of, 4 mm evaluation length, µm stylus stroke length, 350 µm radius with resolution of 0.01 µm. R a has been measured at the three different places and average values are taken. One-variable at a time approach (OVAT) was used to select the process parameters for the response surface design of experiments. It was observed that pulse-off-time is insignificant parameter due to low impact on response parameters. The gap-voltage parameters could not be used for the DOE process because of fixed parameter in the WEDM machine. The process parameters and their levels used for CCD are shown in Table. Design of experiments using response surface methodology Response surface method is a combination of mathematical statistical method and it can be used to develop the regression model and optimization of engineering problems. It enumerates the relationship between the input parameters and the output responses. In the water assisted dry WEDM process, the sufficient data were collected through CCD. Central composite second-order-rotatable design experiments consists of k factorial design corner points, k axial points for each factor with a distance of (( k ) 1/4 =) (where k is the number of parameters=4) and six repeated center points to estimate the pure error 13. Thus, CCD contains 16 corner points ( k ), 8 axis points ( k) and 6 center points at zero levels. Totally, 30 sets of experiments Coded _value=( Actual Mean) /( Range) (1) A, B, C, and D are the coded values of the parameter PW, I, P, and F respectively. The following transformation equations have been used to obtain the coded values. A PW PW ) = PW ( 0 (a) 0 B = (b) ( I I ) I ( 0 C = (c) P P ) P ( 0 D = (d) F F ) F Where, PW 0, I 0, P 0 and F 0 are the values of pulse width, discharge current, air pressure and mixing liquid flow rate at zero level respectively. PW, I, P, and F are the variation factor of PW, I, P and F respectively. The coded values and actual values of each process variable are shown in Table. The effects of process parameters have been studied to measure the output performance using second order polynomial model 13,14 (Eq. 3). 4 i= 1 4 i= 1 4 Y = c + c X + c X + c X X (3) 0 i i ii i 4 ij i= 1 j= 1 Where c 0 is constant and c i, c ii, and c ij represent the coefficients of linear, quadratic, and interaction terms, respectively. X i and X j are the process variables and Y is the response variable. The relationship between the response variable and input variables can be formulated using Eq. (4). Y = X 1 T [( X X ) ( X Y )] + ε T (4) Where, X is the matrix of the model, X T transpose of the matrix X and ε =error vector. i j is the

4 78 INDIAN J. ENG. MATER. SCI., FEBRUARY 014 Run order Std. order Table 3 Central composite design and experimental observations PW (µs) I (A) P (bar) F (ml/min) MRR (mm 3 /min) R a (µm) Regression Analysis Regression analysis has been performed to find the relationship between input and output parameters. The tests for the significance of regression model, individual model coefficients, and lack-of-fit have been performed to ensure the adequate fit of quadratic models. The analysis of variance (ANOVA) test was performed for calculating the F-Value, Prob. > F-Value, the coefficient of determination (R ), adjusted R, predicted R and the adequate precision (AP). F-value and Prob. > F-value are used to imply statistical significance of linear, quadratic, or interaction terms and regression model. Generally, as the preferred confidence level is set to 95%. Prob. > F-value (<0.05) suggests that the regression model is considered to be statistically significant and the model has a significant effect on the responses. R is defined as the ratio of the expected variation to total variation and is used to measure the degree of fit 13. If R is unity, the regression model is better to fit with actual data and if it is less than one, the model has some Table 4 Regression statistics for fitting model of MRR and R a Statistics MRR reduced quadratic model R a reduced quadratic model R Adjusted R Predicted R Std. Div Adequate precision (AP) error to fit. The adjusted R is usually used to calculate the amount of variations from the mean and to decide the significant term presence in the model 13. Adjusted R is also used to decrease the number of terms in the model. Furthermore, if AP is greater than 4, the model is adequate. At the same time, these models obtained higher values of the R, Adjusted R, and AP. The reduced quadratic models for MRR and R a were found to be the most suitable model based on the analysis of variance (ANOVA) sequential sum of squares test as shown in Table 4.

5 BOOPATHI & SIVAKUMAR: STUDY OF WATER ASSISTED DRY WIRE-CUT EDM 79 Source Table 5 Analysis of variance test for reduced quadratic MRR model Sum of squares DOF Mean square F-value p-value Prob. > F-value Model PW I P F PW I PW F I P I F I P Residual Lack of fit Pure error Total Regression analysis for MRR The ANOVA table for the reduced quadratic MRR model is shown in Table 5. The F-value model is that imply the model is significant. If (Prob. > F-value) <0.05, the model terms are significant otherwise insignificant. In this case PW, I, F, PW I, PW F, I F, I, P were significant model terms. Term P was kept in the model, even though it is not significant, to preserve model hierarchy 15. Term I P was considered in the model to draw the response surface analysis between the discharge current and pressure. The reduced quadratic model for MRR in terms of the actual parameter values is shown in Eq. (5). MRR = PW I P F PW I PW F I P I F I P (5) Where, MRR (mm 3 /min) is material removal rate (mm 3 /min) and PW (µs) is pulse width, I (A) is discharge current, P (bar) is pressure and F (ml/min) is the mixing water flow rate. The normal residuals plot of reduced quadratic regression model of MRR is shown in Fig. 3. Regression analysis for R a The ANOVA table for R a is shown in Table 6. The F-value (05.83) of regression model implies that the model is significant. The model terms PW, I, F, PW I, PW F, PW and P are significant. The term P was kept in the model, even though Table 6 Analysis of variance test for reduced quadratic R a model Source Sum of squares DOF Mean square F- value p-value Prob. > F-value Model < PW I P F PW I PW F I P I F PW P Residual Lack of fit Pure error Total Fig. 3 Normal plot of residuals for MRR model it is insignificant, to preserve model hierarchy 15. Insignificant term I P was also taken into the model to draw the response surface between I and P. The reduced quadratic model of R a in terms of actual parameter values is shown in Eq. (6). Ra = PW I P F PW I PW F I P I F PW P (6) Where, R a (µm) is surface roughness, PW (µs) is pulse width, I (A) is discharge current, P (bar) is air pressure and F (ml/min) is the mixing water flow rate. The normal residuals plot of reduced quadratic regression model of R a is shown in Fig. 4.

6 80 INDIAN J. ENG. MATER. SCI., FEBRUARY 014 Results and Discussion MRR response surface analysis Response surfaces of MRR were obtained to study the interaction effects on response parameters. At the higher pulse width and discharge current conditions, it was observed from Fig. 5 that MRR is high due increase in spark strength and spark energy in the cutting zone. It can be revealed from Fig. 6 that high MRR is obtained at higher discharge current and Fig. 4 Normal plot of residuals for R a model) Fig. 5 Response surface of MRR (mm 3 /min) versus discharge current (A) and pulse width (µs) moderate pressure combination. In high discharge current conditions, MRR is greatly improved by increasing of inlet pressure up to 5 bar. Further increasing the pressure, MRR is getting decreased by restriction to transfer the sparks between the wire tool and work piece at high pressure force, low spark thickness (0. mm) and low-lying area between the work piece and the wire electrode 16,17. Response surface of MRR versus pulse width and mixing water flow rate is shown in Fig. 7. It was revealed that MRR is improved by increasing flow rate due to lower thermal conductivity and heat capacity of the water air mixture contribute to less heat dissipation during discharge and a larger portion of discharge energy. Thus, maximum MRR ( mm 3 /min) can be obtained at higher levels of pulse width (18 µs) and discharge current (4. A), moderate inlet pressure (5 bar) and maximum flow rate (11 ml/min) of mixing water. It is also observed from response surface plots that PW, I and F are the significant factors and P is a comparatively less significant parameter on MRR. Effects of process parameters on R a It is clearly witnessed from Fig. 8 that R a is decreased by increasing the pressure up to 5 bar, but R a is increased if pressure is further increased. For the requirement of lower surface roughness, the moderate pressure (5 bar) is preferred. At low pressure (1 to 3 bar), R a is higher due the lack of eroded material removal from the cutting zone. At higher pressure level (7-9 bar), R a is also higher due to poor spark transfer efficiency due to increase in air velocity 16,17. From Fig. 9 it can be noted that R a is higher at higher values of the discharge Fig. 6 Response surface of MRR (mm 3 /min) versus air inlet pressure (bar) and discharge current (A) Fig. 7 Response surface of MRR (mm 3 /min) versus mixing liquid flow rate (ml/min) and pulse width (µs)

7 BOOPATHI & SIVAKUMAR: STUDY OF WATER ASSISTED DRY WIRE-CUT EDM 81 Fig. 8 Response surface of R a (µm) versus air inlet pressure (bar) and discharge current (A) Fig. 9 Response surface of R a (µm) versus discharge current (A) and pulse width (µs) current and pulse width due to increasing debris material grain size. At the high discharge-current and pulse width condition, the material erosion speed is high. Response surface of R a versus pulse width and mixing liquid flow rate is shown in Fig. 10. It can be illustrated that the R a is increased with the increase in mixing water flow rate. The low flow-rate of mixing water with air promotes better surface finish. Further increasing flow rate, the surface finish is reduced due to increase in the rate of the erosion process. Low pulse width and discharge current, and moderate pressure level settings are preferred for better surface finish. The optimum surface finish (0.86 µm) can be obtained from lower levels of pulse width ( µs) and current (1.8 A), moderate pressure (5 bar) at the maximum flow rate of tap water (3 ml/min). It was also observed that PW, I and F are the significant factors and inlet air pressure is comparatively less significant parameter on R a. Fig. 10 Response surface of R a (µm) versus mixing liquid flow rate (ml/min) and pulse width (µs) Conclusions In this study, parametric analysis of the water assisted dry WEDM process has experimentally been performed using hydro-pneumatic circuit. Regression model of MRR and R a were developed with high R (> 99%) using central composite design of experiments and following conclusions were obtained from the regression analysis. (i) Pulse width, discharge current and flow rate of mixing water are the significant process parameters for both response parameters (MRR and R a ). The inlet pressure is an insignificant parameter. However, inlet air pressure has an essential role to flush-out the eroded material from the cutting zone. (ii) The maximum MRR ( mm 3 /min) can be obtained at higher levels of pulse width (18 µs) and discharge current (4. A), moderate inlet pressure (5 bar) at the maximum flow rate (11 ml/min) of mixing water. The minimum R a (0.86 µm) can be obtained at lower levels of pulse width ( µs) and discharge current (1.8 A ), moderate inlet pressure (5 bar) at the minimum flow rate of tap water (3 ml/min). (iii) At the low pressure inlet (1 to 3 bar), minimum MRR and poor surface finish were obtained due to lack of removal of eroded material from the cutting zone and insufficient dielectric strength. At the high pressure inlet (7 to 9 bar), minimum MRR and poor surface finish were also obtained due to the high thermal load and improper transfer of sparks between the wire and work-piece. Thus, at a moderate inlet pressure (5 bar),

8 8 INDIAN J. ENG. MATER. SCI., FEBRUARY 014 MRR and surface finish is good due to proper spark transfer and sufficient dielectric strength in the cutting zone. (iv) It was also observed that MRR is improved by mixing of minimum quantities of tap water with compressed air due to lower thermal conductivity and heat capacity of water and air mixture contribute to less heat dissipation during discharge and a larger portion of discharge energy. Acknowledgments Authors are extremely thankful to All India Council for Technical Education (AICTE), New Delhi, for sponsoring the project work. References 1 Byrne G & Scholta E, Ann CIRP, 4 (1993) Ho K H, Newman S T, Rahimifard S & Allen R D, Int J Mach Tools Manuf, 44 (004) Leao F N & Pashby I R, J Mater Process Technol, 40 (004) Xu M G, Zhang J H, Li Y, Zhang Q H & Ren S F, J Mater Process Technol, 09 (009) Govindan P & Joshi S S, Int J Mach Tools Manuf, 50 (010) Kao C C Tao J & Shih A J, Int J Mach Tools Manuf, 47 (007) Tao J, Shih A J & Ni J, J Manufact Sci Eng, 130 (008) Tao J, Shih A J & Ni J, Int J Elect Mach, 13 (008) Fujiki M, Ni J & Shih A J, Int J Mach Tools Manuf, 49 (009) Sourabh S K & Choudhury S K, Int J Mach Tools Manuf, 49 (009) Jia Y, Kim B S, Hu D J & Ni J, Int J Mach Mach Mater, 7 (010) Govindan P, Agrawal R & Joshi S S, Int J Manuf Technol Manage, 4 (011) Montgomery D C, (John Willy & Sons Inc), Haddad M J & Tehrani, A F, J Mater Process Technol, 199 (008) Mathew J & Sivapirakasam, S P Int J Hygiene Environ Health, 4 (010) Boopathi S & Sivakumar K, Int J Adv Manuf Technol, 67 (013) Boopathi S & Sivakumar K, Eur J Sci Res, 75 (01)