NUMERICAL AND EXPERIMENTAL STUDY ON ENHANCEMENT OF ELECTROCHEMICAL MACHINING PERFORMANCE BY BAFFLED TOOL

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1 Research Paper NUMERICAL AND EXPERIMENTAL STUDY ON ENHANCEMENT OF ELECTROCHEMICAL MACHINING PERFORMANCE BY BAFFLED TOOL 1* V.Sivabharathi, 2 P.Marimuthu, 3 S.Ayyappan Address for Correspondence 1 Associate Professor, Department of Mechanical Engineering, Gnanamani College of Technology, Namakkal , Tamilnadu, India. 2 Principal and Professor, Department of Mechanical Engineering,Syed Ammal Engineering College, Ramanathapuram , Tamilnadu, India. 3 Assistant Professor, Department of Mechanical Engineering,Government College of Engineering, Salem , Tamilnadu, India ABSTRACT: Simultaneous improvement both in material removal rate (MRR) and smooth surface roughness (R a ) of electrochemical machining is achieved through the efficient removal of the products of reaction and joule s heat generated in the interelectrode gap. The high-velocity jet applied in the inter-electrode gap cannot completely remove the sludge, which leads to poor MRR and R a. The turbulence of electrolyte flow is enhanced using serially arranged baffles inside the tool to improve the removal of the sludge. A numerical 3-D flow field has been constructed for the geometrical model of inter-electrode gap and cathode tool, and then the model was simulated. The effect of baffles on the electrolyte flow field has been examined according to the final outcome of numerical simulation. In turbulent flow, maximum MRR of g/min was obtained in comparison to g/min with constant electrolyte. The substantial decrease in R a was also noted in all cutting conditions. It was realized that the tool design with baffles can be used to enhance MRR and good R a value. KEY WORDS: Electrochemical machining (ECM), Computational fluid dynamics (CFD), Material removal rate (MRR), Surface roughness (R a ), Al/VC composite. 1. INTRODUCTION Electrochemical machining (ECM) possess remarkable capability due to its adaptability to a variety of applications in mould and dies, roller and gear, aerospace and automobile industries. ECM is expected to be a capable, prosperous and commercially employed machining technique in the modern manufacturing scenario [1]. ECM has been of industrial interest owing to its considerable advantages viz., insignificant tool wear, stress free and burr-free fresh surfaces, good surface finish and the capability to machine intricate shapes of hard materials [2, 3]. Although the ECM finds some specific applications, its full potential is not yet utilized commercially. It is because of its low MRR and dimensional accuracy. Increasing the accuracy of ECM is the tough job since it involves many complex variables [4]. Many researchers have tried to improve the potential of ECM through some hybrid machining processes. Machining efficiency and precision of ECM was enhanced with laser-assisted jet by merging less- power laser beam and an electrolyte jet [5]. Electrochemical turning (ECT) was combined along with roller burnishing and magnetic abrasive finishing (MAF) to improve the surface quality of machined components [6]. Electrochemical machining and honing processes combined to make electrochemical honing (ECH) technique to produce gears and interior cylinders [7]. The surface roughness of titanium alloys was enhanced by pulsating-electrolyte [8]. Sludge and oxides deposits in the gap of electrodes disturb the electrolyte smooth movement, and their insulating characteristic becomes an obstacle to ions displacement. This overall process affects the efficient machining in ECM thereby resulting poor MRR. Therefore, complete removal of sludge and oxides ensures the better performance of ECM. In this direction, lot of additives i.e. Potassium dichromate (K 2 Cr 2 O 7, Oxygen (O 2 ), Hydrogen peroxide (H 2 O 2 ) and Ferric nitrate (FeNO 3 ) were used in the aqueous NaCl to remove the sludge and oxides [9-12]. Machining of aluminium metal matrix composites (Al-MMCs) is a tough task with conventional and some nonconventional machining techniques. Al-MMCs find its applications in sports equipment, automobile, aerospace industries as a result of their high strengthto-weight ratio. The vanadium carbide (VC) reinforced Al-MMCs demonstrate potential mechanical characteristics especially high strength and hardness. Therefore, it is highly essential to develop appropriate machining methods for Al/VC composites. Electro-discharge machining (EDM) was used to machine Al-MMCs, and machining characteristics were investigated [13]. The drilling and turning characteristics of Al-MMCs were extensively studied [14-17]. Another non-traditional machining technique of laser machining creates heating on the surface of the workpiece, which increases slightly reduced surface quality. The ceramic particles in the metallic matrix will abrade the electrode tool thereby lessen tool life. But Electrochemical machining (ECM), a non-traditional machining process overcomes the difficulties discussed in the other machining performance. ECM is controlled anodic dissolution process that does not wear the tool. Few works [18-22] have been reported in electrochemical machining issues of Al-MMCs. The LM25 Al/VC composite was chosen as no work is available till now to experiment its ECM performance. This research paper discusses the numerical and experimental research on enhancing the MRR and R a of electrochemical machining of Al- VC composites. The experimental investigation was conducted to realize a significance of the effects of process parameters namely an applied voltage (V), electrolyte concentration (EC) and wt % of VC in Al matrix on the ECM performances (MRR and R a ). In several investigations, the response surface methodology (RSM) was implemented as an efficient design of experiments (DOE) strategy in electrochemical machining [9-13, 18, 22]. Therefore, the central composite design (CCD) of RSM was deployed to plan and analyzing the experiments.

2 2. COMPUTATIONAL FLUID DYNAMICS (CFD) OF FLOW FIELD 2.1 Governing equations The electrolyte flow field of cathode tool is hard to control accurately due to the difficult nature of the electrochemical, hydrodynamic and thermal composite actions involved during machining [23]. To make simpler the CFD simulation analysis retaining the accuracy requirement, the flow of electrolyte in the inter-electrode gap (IEG) is assumed to be one phase liquid of continuous, incompressible and perfect fluid. The electrolytic products in the IEG due to material removal in anode and cathode are not considered. In the ECM process, the distance of the inter-electrode gap (IEG) is assumed as constant. With reference to the assumptions above and the theory of CFD, the governing equations i.e. mass conservation and momentum conservation of electrolyte flow field for numerical simulation were developed as given below [24] = (1) = (2) = (3) + + = 0 (4) Here, t is considered as the time, u, v and w are the element velocity of electrolyte velocity vectors in x, y and z-axis. μ is the absolute viscosity of the electrolyte p is pressure on flow component, Fx, Fy and Fz represent volume force, Fx = 0, Fy = 0, Fz = -ρg (when the gravity force is only volume force working on flow component with assumption that the electrolyte is perfect fluid) The first three equations are the Navier-Stokes equations, and the fourth is the equation of continuity. The numerical solution of these equations has been carried out within the simulation of flow profiles with the computer program ANSYS- FLUENT. The k-ε model is utilized for finding solution for this problem. This model contains a twoequation model. It avails gradient based hypothesis for producing the relation between the turbulent viscosity and Reynolds stress to the mean velocity gradient [25]. In that, k is the turbulent kinetic energy expressed as variance of fluctuations in velocity. Unit of k is m 2 /s 2. ε is the velocity fluctuations dissipate rate which is called as turbulent eddy dissipation. Unit of ε is m 2 /s 3. + = 0 (5) + = + μ + + (6) μ = μ + μ (7) The k-ε model is assumed as the turbulent viscosity based on dissipation and turbulent kinetic energy. That relation is represented in Eqn. (8). μ = (8) k and ε values are coming directly from the differential equations for turbulent kinetic energy and dissipation rate. Those equations are given in Eqn. (9) and Eqn. (10). ( ) + = μ ( ) + = μ + + (9) [ + ] (10) Value for P k is getting from the relation given in Eqn. (11). = μ + (11) =. ( ) + (12) In the present simulation process, two different models are used. Those models are named as: Model 1 -Circular shaped tool electrode with central through hole. Model 2 -Circular shaped tool electrode with baffles inside the flow passage. The modeling has been created with CATIA V5.0. A cross section of a model of the workpiece is shown in Fig.1. The electrolyte availed for this simulation was aqueous NaCl solution. The tool inlet diameter is 7 mm. The model has been analyzed with an inlet mass flow rate of 10 Kg/min. The Velocity is set on the flow rate limit (15-20 L/min) of the flow without passivation in the ECM process. This center of the hole is maintained on (-7.5,-7.5) coordinate in the plane XZ. Fluid is flowing via the through-hole and flow out through the inter-electrode gap (IEG). The IEG for all models remain constant as 0.1 mm. Fig.1 Circular shaped tool electrode with central through hole (Model 1) Fig.2 Circular shaped tool with baffles inside the flow passage (Model 2) 2.2 Meshing Models are meshed using mesh module in ICEM CFD commercial software. The most important phase of engineering simulation is mesh creation. Many cells may result in long solver runs, while some will

3 end up with inexact results. Meshing technology in ANSYS balance these needs and attains the accurate mesh for all simulation automatically. Meshing methods in ANSYS is constructed as stand-alone and class-leading meshing tools.the meshing quality is relevant to the model geometry and results accuracy can be communicated with orthogonal quality value. When this value is nearer to one, we attain appreciable results because of better quality of mesh. Meshes give bad results if the value approaches zero. Program controlled automatic inflation method is made feasible for meshing. In ANSYS software, mesh methods taken in to account of patch independent methods and patch conforming. Among that patch independent meshing method is adopted for meshing current model geometries. Patch independent method uses top-down approach that means it creates volume mesh and extracts surface mesh from boundaries [25]. Materials used for making this simulation are, Al-VC work piece, Copper tool electrode and the electrolyte used is 20% brine solutions. maximum time steps respectively. Maximum value time step is set 300 or 600 because in some simulation are carried out with both 30s and 60s. Fluid time scale control is fixed as the physical time scale, in that time scale value is given as 0.1s. In that, this simulations were done as an iterative process so first want to set convergence criteria. Root Mean Square (RMS) value is set as convergence criteria. 3. DISCUSSION ON CFD RESULTS In this chapter, the parameters affecting ECM process are explained with the help of both charts and graphs. This velocity, pressure, turbulent kinetic energy and MRR on inlet mass flow rate are discussed for the two models using the commercial software ANSYS. 3.1 Effect on velocity profile Fig.5 Velocity profile without baffles Fig.3 Meshed tool without baffle Fig.4 Meshed tool with inclined baffle 2.3 Analysis The analysis is done using an ANSYS-FLUENT software. This advanced solver technology provides fast, accurate computational fluid dynamics results. These simulations are set as a steady state problem. The boundary conditions for the problem are given as below. The computational domains should specify first before specifying the boundary conditions. Here in simulation, two solid domains (workpiece and tool) and a fluid domain (electrolyte) are used. Solid domain materials are in the material group conjugate heat transfer solids and consider as pure solids. Inlet conditions Mass flow rate=10 kg/min Flow regime = Subsonic Turbulence = Given intensity and auto computation length Fractional intensity =0.06 Since no heat transfer is required, kinetic energy equation not required Outlet conditions Opening pressure = 0 Pa Flow regime = Subsonic Turbulence = Given intensity and auto computation length Fractional intensity =0.06 After the boundary conditions set up, the solver control is needed to manage. High resolution is taken for advection scheme. The value of 1 and 300/600 is given as minimum and Fig.6 Velocity profile with baffles Figs.5 and 6 are the velocity profiles within the IEG of the models (Model 1 and 2) used for the stimulation. The velocity profiles are plotted for the range 0 to 60 m/s for the present study of the specimens. In Fig.5, the velocity is about 62 m/s nearer the central through hole. Due to stagnation the surrounding of the central through hole has a small variation of velocity. That means the inlet electrolyte with high velocity first gets in touch with the work piece where it discharges the kinetic energy at maximum level in the boundary area which is described as stagnation region, and the velocity is called stagnation velocity. After that, the velocity is diminishing gradually, but it is less than 5 m/s in some region towards the tip of the tool (shown in Fig.5 with blue colour). According to ECM theory, passivation where the metal removal is not actively taken places due to deposition and accumulation of sludge on the workpiece and tool surfaces due the reason of inadequate circulation of electrolyte in between the IEG. When the velocity below 5 m/s, then probably the passivation will occur in the surface which results in prevention of further machining. 3.2 Effect on turbulent kinetic energy (k) Figs.7(a) and 7(b) are the turbulence kinetic energy within the IEG for models 1 and 2, with an inlet mass flow rate of 10 Kg/min. Turbulence in the k- ε model relies on turbulent kinetic energy (k). Turbulent kinetic energy decides the energy in the turbulence. In model 1, near the central through-hole

4 turbulent kinetic energy is less due to stagnation. The adjacent area of the central through-hole has a significant variation of turbulent kinetic energy. That is because of the sudden buildup of high pressure in the stagnation region. (a) Without baffle (b) With baffle Fig.7 Turbulent kinetic energy profile for inlet mass flow rate of 10 Kg/min through tool 3.3 Effect on pressure (a)without baffle (b) With baffle Fig.8 Pressure profile for inlet mass flow rate of 10 Kg/min through tool Fig. 8(a) and 8(b) are pressure distribution within the brine solution only in the IEG for Models 1, 2 with Sl. No. Voltage (V) Parameters Electrolyte concentration (EC) an inlet mass flow rate of 10 Kg/min respectively. The high pressurized electrolyte coming in makes contact initially with the work piece. Here most of the kinetic energy is discharged in that region. 4 EXPERIMENTAL WORKS IN ECM A chance for an increase in the performance of ECM was confirmed from the numerical results. Hence it is decided to prove with experimental results of ECM. The central composite design (CCD) of response surface methodology (RSM) was exercised to develop the experimental work. The CCD was developed and analyzed using Design Expert software [26].The governing predominant process parameters of ECM process are voltage (V) and electrolyte concentration (EC) with reference to the literature [9, 12]. Different grades of composites i.e. Al/ 1 % wt.vc, Al/ 2 % wt.vc, and Al/ 3 % wt VC were included as the third parameter in the DOE. Samples of Al-VC composite with the dimensions of mm size were used. The process and product parameters and its levels are given in Table 1. An inter-electrode gap of 0.1 mm and of 0.1 mm/min was set initially as constant feed rate. Table 1 The process parameters and their values at different levels Level Symbol Process parameter VC Weight fraction of vanadium carbide in aluminium matrix V Voltage (volts) EC Electrolyte concentration (g of NaCl / L of water) MRR is one of the most predominant measures to determine the performance of machining. A higher MRR is generally desired in such operations and is defined as follows: = Table 2 Experimental results Vanadium carbide (VC) ( ) ( ) g/min (13) m-mass of material removal (g) t-machining time (min) Weights were measured by Sartorius (BS 423S) balance with an accuracy of 0.001g. Mitutoyo surface roughness tester is utilized to get the value of the surface roughness (R a ) to the sampling length of 10 mm. Average of the three measurements is taken as the final result. Table 2 consists the results of experiment of the cathode tool with baffles of this investigation. In addition, a scanning electron microscope was utilized to observe the machined surface. Without baffles Performances With baffles MRR R a MRR R a V g/l % g/min µm g/min µm

5 The experiments with the cathode tool of without baffles were separately conducted and its results were compared as shown in Table ANOVA TEST The analysis of variance (ANOVA) and the Fisher s test (F-ratio) have been carrying out to explain the justification of the goodness of fit of the mathematical models [27]. A second order polynomial model is fitted with the following equation. Table 3 and 4 contains the ANOVA analysis results for models MRR and R a. Table 3 Analysis of variance for MRR Source DF Sum of squares (SS) (14) Where, Y u -response, n -number of parameters, b o,b 1 etc., -second order regression coefficients, e u -regression error Mean sum of squares (MS) F-value Regression Linear Square Interaction Residual Error Lack-of-Fit Pure Error Total = (15) The coefficient of determination (R 2 ) -89%. The MRR model F-ratio value of 9.15 explains that model is statistically significant. In this case, square and interaction terms are important. The value of R 2 =89% indicates that the regression model offers an tremendous explanation of the relationship to the variables and the response MRR. The model is fit as shown in Equation.(15). = (16) The coefficient of determination (R 2 ) -94%. The R a model is very stable as the R 2 value is quite good. P

6 Table 4 Analysis of variance for surface roughness (R a ) Source DF Mean sum of Sum of squares (SS) squares (MS) F-value P Regression Linear Square Interaction Residual Error Lack-of-Fit Pure Error Total Fig.9 Comparison of MRR for different case studies Fig.9 confirms that the MRR is better in case of tool with baffles when compared to without baffles. According to the results of ANOVA study, the interactive effect of parameters is playing a significant role in the ECM performance i.e. MRR and R a. Therefore, the contour plots have been drawn as shown in Figs 10, 12 to understand the effect of electrolytes thoroughly EC*V VC*V The surface roughness (R a ) is low in the case of baffled tool as demonstrated in Figure 11. The raise in EC and voltage (V) increases the surface roughness (R a ) extremely. As the percentage of VC increases, surface roughness also increases. Good erosive surface can be seen in the images of Figures 13 (b) because of high voltage (20V) and electrolyte concentration (160 g/l). More vanadium carbide spread can be seen in Figure 13 (b). Surface Roughness (Ra) µm Fig.11 Comparison of surface roughness (R a ) for different case studies EC*V Test Run 3.0 VC*V Ra (without baffles) Ra (with baffles) VC*EC Fig.10 Parametric influence on MRR for baffled tool High voltage leads to high machining current that increases the MRR. This situation could be seen in the first and second plot of Figure 10. It is clearly shown in the second and third plot, the proportion of VC particles presence in the specimen does not affect the MRR. Since vanadium carbide (VC) is an inert particle, it is not affected by an electrolytic reaction. But its surrounding aluminium metal is dissolved when the current is supplied to the inter-electrode gap. These suspended particles were flushed away by the high-velocity turbulent flow of electrolyte jet. It is noticed that the raise in electrolyte concentration (EC) enhance MRR. The increase of concentration leads to the improvement in the electrolyte conductivity. But the concentration above certain limit acts as hindrance to the mobility of ions which minimises MRR. The concentration up to 140 g/l is adequate to get appreciable MRR according to the first and third plot of Figure MRR < > Hold Values V 15 EC 160 VC VC*EC Fig.12 Parametric influence on surface roughness (R a ) for baffled tool Fig.13(b) illustrates that the smooth surface has been achieved by supplying a turbulent electrolyte by means of baffles inside the tool. Fig.13(a) presents the pattern of a machined surface obtained in an electrolyte condition without baffles. This observation signifies that baffled tool affect the machined surface finish. Figs.9 and 11 demonstrates the variation of the surface roughness (Ra) and MRR with baffles inside the tool. When the electrolyte is constant, the highest Ra is 4.95 μm and the MRR is g/min. Baffles was introduced to ECM to generate turbulent electrolyte in lieu of a constant electrolyte, MRR changed to g/min. But the R a is changed slightly to 4.94 μm. The lowest MRR is observed as g/min in constant electrolyte with Ra < > Hold Values V 15 EC 160 VC

7 machining conditions of 10 V, 190 g/l and the specimen of 3 % VC. In the same conditions, MRR is raised to g/min in baffled tool. The substantial decrease in R a is also noted. ECM process follows the principle of electrolysis contains chemical reactions, energy, mass, and momentum transfer. When a voltage is supplied in between, electrodes, the metallic ions of the anodic dissolution transferred from the anode surface to the electrolyte by electric force. As a result hydroxide is formed which is not soluble. The hydrogen and oxygen gases are also generated on the cathode and anode surface respectively. The gas bubbles and Joule heat produced in the gap of electrodes results in variation of the electrolyte conductivity. Alteration in conductivity of electrolyte with flow path influences the potential distribution. In ECM, the electrolyte medium is supplied in between electrode gap to flush out the machined products and Joule heat is also dissipated. In a baffled tool, the electrolyte flow separation happens and produces some reverse flow and areas of high turbulence have been generated. The turbulent electrolyte is favourable for bringing down the difference of the electrolyte conductivity in the electrodes gap. It promotes machined surface homogeneously [8]. It is observed that the R a value reduces while the electric potential voltage raises [28]. Hence, a remarkable surface profile has been attained with the turbulent flow of electrolyte. Various studies have described that a pulsating electrolyte flow is favourable to the effective transfer process [29]. The poor turbulent electrolyte results in rough surface and enhanced MRR. Fig.13 SEM images ECM machined Al/VC composites 5. CONCLUSIONS This work, electrochemical machining allied with a turbulent electrolyte flow has been used as a way to machine Al/VC composite. Flow pattern analysis of electrochemical machining with baffled tool is giving better information about the turbulence and velocity distribution, etc. in the inter electrode gap. In this analysis, Copper tool has been used to machine Al/VC composite work piece with the help of brine solution as electrolyte. Two tools with different design were modeled and analyzed. All models are meshed using mesh module with an orthogonal quality of more than 0.9 which ensure these models will give good results. All models are analyzed with the mass flow rate of 10 Kg/min. In a baffled tool, high mixing and turbulence are generated, which enhance the heat transfer rate and is advantageous for diminishing the variation of the electrolyte conductivity gap. The smaller variation in conductivity of electrolyte and potential leads to smooth surface. In turbulent electrolyte, the higher MRR of g/min was obtained in comparison to g/min with constant electrolyte. 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