ETIME 2021 Proceedings E-Book

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 4. ANALYSIS OF SPINDLE 4.1 STATIC ANALYSIS OF HIGH- SPEED MOTORIZED SPINDLE A high- speed spindle that will be used in a metal cutting machine tool must be designed to provide the required performance features. It is capable for increasing productivity and reducing production costs. Compared to conventional spindles, motorized spindles are equipped with built-in motors for better power transmission and balancing to achieve high-speed operation. Used software for this project work bench 4.1.1 MODELOF THE SPINDLE 4.1.2 MESHINGOF SPINDLE MODEL Fig: 4.1 Model of Spindle Fig: 4.2 Meshing of Spindle Model 4.1.3 BOUNDARYCONDITIONSAPPLIED ON SPINDLE Fig: 4.3 Boundary conditions applied on the spindle 4.1.4 TOTAL DEFORMATION OF THE SPINDLE 4.1.5 EQUIVALENT STRESS OF THE SPINDLE AT DIFFERENT SPINDLE SPEEDS Fig:4.4 Total deformation of spindle Fig:4.5 Equivalent stress of the spindle 166 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 4.1.6 EQUVALENT STRAIN OF THE SPINDLE Fig:4.6 Equivalent strain of the spindle 4.2 MODAL ANALYSIS OF SPINDLE FOR DIFFERENT MATERIALS- 4.2.1 TOTALDEFORMATION 1 4.2.2 TOTALDEFORMATION 2 Fig:4.7 Frequency of the spindle at mode 1 Fig:4.8 Frequency of the spindle at mode 2 According to the counter plot fig:4.50, the maximum deformation at free end of the spindle is 6.8924, and frequency is 111.15Hz. 4.2.3 TOTAL DEFORMATION 3 Fig:4.9 Frequency of the spindle at mode 3 167 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 5. RESULTS AND DISCUSSIONS 5.1 STATIC ANALYSIS RESULT TABLE Table: 5.1Static Analysis Result Table Material Speed (RPM) Deformation (mm) Stress (N/mm2) Stra in AISI 1050 Steel 8000 0 .016773 20.988 0.00010238 12000 0 .037739 47.224 0.00023037 Aluminum alloy 7075 16000 0 .067092 83.954 0.00040954 8000 0 .019258 7.3917 0.00010309 Carbon fiber 12000 0.04332 16.632 0.00023197 16000 0 .077034 29.567 0.00041239 8000 0.12895 53.266 0.00076096 12000 0.29015 119.85 0.0017122 16000 0.51583 213.07 0.0030439 The above table: 5.1 shows the values of the static analysis of the spindle at different speeds. It is observed that, spindle at 8000 rpm. The values of deformation and strain values ofAISI 1050 steel, andAluminum alloy 7075material are low compare to the carbon fiber. The speed increases then stress and strains values will increase and it depends upon the weight of the spindle. It is concluded that in structural analysisAluminum alloy is more suitable for low-speed spindles. 5.2 MODELANALYSIS RESULT TABLE Table: 5.2 ModelAnalysis Result table Material Mode 1 Frequency Mode 2 Frequency Mode 3 F requency (mm) (HZ) (mm) (HZ) (mm) (HZ) AISI 1050 Steel 6.8928 111.14 6.8924 111.15 5.3796 401.7 AL 7075 11.519 110.31 11.519 110.33 8.9915 3 91.07 13.655 128.79 13.654 128.81 10.658 4 63.26 Carbon fiber The above table 5.2 shows the values of frequency at different modes, for different materials of the spindle. In the above table it is observe that, the values frequency of the carbon fiber material at three models are high when compare to the other materials like aluminum alloy 7075,AISI 1050 steel. It is concluded that in all three modes carbon fiber having the high frequencies compare to the other materials. At these modes the number of cycles or vibrations made by spindle with carbon material is relativelymore when compared to the other materials. High frequency spindles are used for internal grinding applications, where high speed and accurate accuracy is required and also helps in getting high productivityand better surface finish. Hi-FrequencySpindles have Integrated motor design which eliminates gears and pulleys, and makes it, compact. High Frequency Spindles used in the automotive, aerospace, military, tooling, wood, plastic, stone, marble and glass industries CONCLUSION In this project, different materials are analyzed for spindle. AL 7075 and carbon fiber are replaced with steels. Structural and Dynamic analyses is done usingANSYS software. Modal analysis also is done to determine the Frequency at different modes. From structural analysis the stress increase by increasing spindle speeds. we conclude that aluminum alloy is most suitable for low-speed spindles. By modal analysis, carbon fiber is suitable for high-speed spindles than 168 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) steels. For high-speed spindles weight should be taken in to account. By replacing the steel with carbon fiber, the weight, of the spindle decreases. we conclude the suitable material for high-speed motorized spindle is carbon fiber. REFERENCES 1. Y. Lu Y.X. Yao and R.H. Hong \"Finite Element Analysis of Thermal Characteristics of High-speed Motorized Spindle \"Applied Mechanics and Materials Vols. 10-12 pp 258-262 (2008). 2. Y. Lu Y.X. Yao and W.Z. Xie \"Finite Element Analysis of Dynamic Characteristics of High-speed Motorized Spindle\" Applied Mechanics and Materials Vols. 10-12 pp 900-904 (2008). 3. Jenq-Shyong Chen Wei-Yao Hsu \"Characterizations and models for the thermal growth of a motorized high-speed spindle\" International Journal of Machine Tools & Manufacture 43 1163-1170(2003). 4. Chi-Wei Lin a, Jay F. Tua, Joe Kamman \"An integrated thermo-mechanical-dynamic model to characterize motorized machine tool spindles during very high-speed rotation \"International Journal of Machine Tools & Manufacture 43 1035- 1050(2003). 5. Bernd Bossmanns, Jay F. Tu \"A thermal model for high-speed motorized spindles\" International Journal of Machine Tools & Manufacture 39 1345-1366(1999). 6. Deping Liu, Hang Zhang, Zheng Tao and YufengSu \"Finite Element Analysis of High-Speed Motorized Spindle Based on ANSYS\" School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, China (2011). 7. Nagaraj Arakere, Assoc. Prof., Tony L. Schmitz, Asst. Prof., Chi-Hung Cheng \"Rotor Dynamic Response of a High-speed Machine Tool Spindle \"University of Florida, Department of Mechanical and Aerospace Engineering 237 MAE-B, Gainesville, FL 32611. 8. Jin Kyung Choi, Dai Gil Lee \"Thermal characteristics of the spindle bearing system with a gear located on the bearing span 'Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, ME3221, Gusongdong, Yusong-gu, Taejon-shi, South Korea 305-70. 9. Jenq-Shyong Chen, Kwan-Wen Chen \"Bearing load analysis and control of a motorized high-speed spindle \"International Journal of Machine Tools & Manufacture 45 1487-1493(2005). 10. Mohammed A. Alfares, Abdallah A. Elsharkawy \"Effects of axial preloading of angular contact ball bearings on the dynamics of a grinding machine spindle system \"Journal of Materials Processing Technology 136 48- 59(2003). ISBN: 978-0-13-601970-1 169

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Investigations into Tool Wear Characteristics of Micro Milling Using Pin on Disk and 3D Deform Joshna Gajula1, Sumalatha2, Sunanda3 1,2,3Assistant Professor, Mechanical Engineering, SNIST ABSTRACT The machining process is performed on high and ultrahigh precision machines and miniaturized/ micro machines. In the present work, an attempt has been made to understand the wear phenomena and tool failure in micro tools. To investigate the wear characteristics, a pin on disk wear tests were carried out at different speeds, track diameters and applied loads with tungsten carbide (WC) pin and AISI 410 stainless disk and the data is collected and same with the micro milling. In order to correlate the results obtained during wear tests and the machining experiments, a finite element based model is developed. However, such an assumption cannot be made when dealing with micromachining processes due to size effects caused by work piece material microstructure. Hence in the present work, the simulation of the wear profile of a pin and the disk was performed using the finite element software package 3D DEFORM with the modified Johnson's cook model. The modeling procedure was first validated by using a theoretical solution developed based on pin on disk and micro milling tests. Different set of machining experiments were carried out with same work piece and tool materials, at different operating conditions to verify the proposed model. The results presented in the work will help in understanding the wear characteristics of tool and will help in redesigning the tool to achieve higher tool stiffness, reduce tool wear and improved tool life. Keywords: Deform 3D, Milling, Simulation, AISI 410 Stainless steel 1. INTRODUCTION Micro-milling is widely used in the precision manufacturing industry and is the most suitable for producing complex 3D geometries and shapes. Micro-milling is defined as the downscaling of the conventional milling process involving the use of end mill diameters in the sub-millimetre range has become an established process for manufacturing of three-dimensional meso and micro components in metals and alloys. One of the fundamental contributions to the determination of the accuracy of a milled component is the deflection of the tool due to the cutting forces. It is thus essential to be able to count on reliable models for prediction of cutting forces in micro milling. Cuttingforceprediction in micro scalemachiningis complicated bya numberofissuesthat arefundamentally different from macro scale machining and influence the underlying mechanism of the process. Such issues, often referred to as size effects, are common to all micro cutting processes and are related to the strong reduction of the uncut chip thickness as well as the limited scalability of the work piece material microstructure and tool geometry. Milling is the process of cutting away material by feeding a work piece past a rotating multiple tooth tool cutter at a specified rate and depth of cut. Therefore, Cutting parameters like cutting speed, feed rate, tool geometry and depth of cut are to be determined to carry out milling operation. Stainless steels resistance to corrosion, low maintenance, and relative cheapness makes it a ideal for a range of commercial applications. It is widely used in industrial equipment, automotive and aerospace structures, surgical instruments, storage tanks etc. Stainless steel is an alloy with a minimum of 11.5% chromium content by mass which make it highly resistive to 170 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) corrosion. It is characterized by high plasticity, melting point, large linear expansion factor, which results in high cutting force and temperature, poor machining quality, built up edge and tool wear in cutting practice [8]. Wear in cutting tools is a very complex phenomenon with many variables and different mechanisms. Tool wear can include one or more of several mechanisms [4] such as abrasion, adhesion, melting or delamination depending upon a specific tool and work piece combination, cutting experience and cutting velocity. Tool wear rates are a few orders of magnitude higher than those in sliding wear. The very high temperature and pressure on the tool surfaces and cutting edge may lead to the developments of different wear patterns under different cutting conditions. These tool wear modes are usually known as flank wear on the flank face of the tool, crater wear on the face of the tool and rounding at the nose. The locations and configuration of these tool wear modes are generally influenced by the distribution of the heat generated during cutting, friction and stress distribution at the tool work piece interface [2]. This was more or less the first detailed study on micro end milling process and this study was further extended to incorporate the effects of tool run out on the cutting forces and the estimation of the tool wear and detection of tool breakage in micro end milling process. In this cutting force model it was assumed that typically in micro end milling operations, the feed per tooth to the tool radius ratio is selected to be much higher than that in conventional end milling operations. But this cannot be generalized as it depends on the job in hand and the geometric dimensions of the product needed and the permissible feed and speed of the machine tool. However this condition may be necessary to keep the productivity a little high. This model is merely based on the for conventional end milling operations, except the expression for the chip thickness, which is separately derived considering the path of the tool tip. Experimental results have shown that this model was effective only at higher ratios of feed per tooth to tool diameter [6]. To study the various approaches for simulating cutting forces in orthogonal and oblique cutting operations since theygive a clear overview of the modelling of forces in any machining operation and eventually in milling as well. Earlier cutting force models have been developed and simulated for orthogonal cutting operations [3] who assumed the chip to be a rigid body held in equilibrium by the action of forces across the chip tool interface and shear plane. He also assumed that the shear plane angle would minimize the work done in cutting. Their solution required the construction of a slip-line field pattern and the shearing in the primary deformation zone is assumed to be concentrated on a narrow shear plane. However neither of these models could incorporate the actual work piece behaviour into the model structure in a realistic way. Therefore the predicted results were not quite in agreement with the experimental results obtained using different work piece material combinations. This is mainly due to the difference in the material properties, which have to be included into the relationship of shear plane and friction angle. Also has attempted to include the work material strain hardening properties obtained through tension tests in calculating the shear plane and friction angle. It would not hold for different combinations of tool geometries and work materials incorporated into machining models by applying the more complicated plasticity theory. This requires that no specific form of deformation pattern be assumed prior to solution and work piece material properties should be known as to the ranges of strains, strain rates and temperatures generated during the cutting action [7]. The continuum mechanics and the minimum energy principles are applied to the analysis of chip formation process, taking into account as much as possible of plasticity theory. This again makes this model too complicated and at micro scales even this model too proved to be inaccurate. Nobody really attempted to analyze the Micro end milling process in depth until the remarkable work [1]. In this study a new analytical cutting force model is proposed for micro end milling operations. This model estimates the chip thickness by considering the trajectory of the tool tip while the tool rotates and traverses ahead continuously in the feed direction. ISBN: 978-0-13-601970-1 171

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The cutting edges of conventional mills wear out when they lose material and as a result craters are formed and generally the cutting edges break one by one. While in micro end milling the tiny shafts break when either the cutting edge becomes dull because of material loss or the tool is covered with particles of work piece material or clogged chips. The variation in the cutting force pattern with the machining time is veryvital in determining the tool wear in micro end milling operations. Tool life in conventional end milling decreases with increase in axial depth of cut but contradictorily it was observed to increase with increase in axial depth of cut up to a certain extent [5]. In this studythebehaviour of tool wearand tool life characteristics with varying cutting conditions has been investigated and the findings are experimentally justified. DEFORM 3D is a powerful process simulation system used for the analysis of three dimensional flow of complex metal processes. It is a practical and efficient tool to predict the material flow in industrial forming operations without the cost and delay of shop trials [9]. It consists of three steps. They are Pre-process step include defining work piece, tool geometry and process parameters like surface speed, mill diameter and depth of cut. Simulate step include the simulation work of defined operation. Post process step gives the simulated results of the operation. The objective of this paper to develop a simulation model of the wear profile of a pin and the disk was performed using the finite element software package 3D DEFORM with the modified Johnson's cook model especially considering the effect of feed rate and forces. In the present work the modeling procedure was first validated by using a theoretical solution developed based on pin on disk and micro milling tests. Different set of machining experiments were carried out with same workpiece and tool materials, at different operating conditions to verify the proposed model. The results presented in the work will help in understanding the wear characteristics of tool and will help in redesigning the tool to achieve higher tool stiffness, reduce tool wear and to improved tool life. To investigate the wear characteristics, a pin-on-disk wear tests were carried out at different speeds, track diameters and applied loads with tungsten carbide (WC) pin andAISI 410 stainless disk and the data is collected. In order to correlate the results obtained during wear tests and the machining experiments, a finite element based model is developed. Generally, in finite element modeling, the work piece is considered to be homogeneous and isotropic. However, such an assumption cannot be made when dealing with micromachining processes due to size effects caused by work piece material microstructure. 2. EVALUATION OF TOOLAND WORK PIECE PROPERTIES In this section various machines used for the experiment and the properties of the tool and work piece are explained along the process parameters. 2.1 Experimental Setup The setup of the method comprises of a pin with spherical surface as the tip and a circular rotating disk which is placed at a perpendicular with respect to the spherical pin surface. The diameter of the pin is 3mm and the length is 10mm.The disk is made of stainless steel on which the pin is held with a jaw in the apparatus and rotation is provided to disk which causes wear of the pin on a fixed path on disk. The pin is pressed against the surface of the disk with load being applied with the arm attachment provided to the apparatus. Machine is attached with a data acquisition system and WINDUCOM 2010 software which gives result values and graphs. The pin on disc equipment has a computer based controller, used to control the parameters of the pin on disc apparatus. The parameters required to be specified are rotational speed (rpm) and load (Kgs). The values of coefficient of friction and values of frictional force for the given time period are recorded during the experiment. 172 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Table 1: Specifications of Pin on Disc apparatus and experimental conditions P arame ter s Values Pin sizes (mm) Diameter 3 and 8 Wear disc size (mm) Diameter: 50 Wear track diameter (mm) Thickness: 10 Disc rotational speed (rpm) Min: 20 Max: 80 Normal load (Kgs) Min: 500 Experimental conditions: Max: 2000 Min: 1 Density of work piece material used as Disk Max: 5 Density of tool material used as Pin Total run time 7.6 g/cm3 15.63 g/cm3 16 min 30 sec Figure 1: Pin on disc experimental setup In Pin on Disk different experiments were carried out with different speeds, track diameter and loads. Initial and final weights of the disk and the pin were taken to find out the volume loss and wear rate analysis. Pin-on-disk experiments were conducted to evaluate the coefficient of friction and the tribological behaviour of the Tungsten Carbide pin with theAISI 410 stainless steel. Table 2: Pin on Disc Experimental Values Expt. Load Speed Track P in Disk Frictional Wear Coefficient No. (kg) (RP M) dia met er diameter diameter force N loss of friction (µm) 1 1.0 955 (mm) (mm) (mm) 4.5070 27.94 0.451 2 1.0 955 20 3 50 5.243 36.38 0.524 3 2.0 480 20 8 50 12.818 108.70 0.640 4 2.0 545 40 3 50 11.355 47.28 0.560 5 2.0 420 35 8 50 10.620 96.85 0.620 6 2.5 420 45 3 55 11.750 99.65 0.625 45 3 55 ISBN: 978-0-13-601970-1 173

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) (a) (b) Figure 2 (a) and (b): Friction coefficient and wear loss at the rotational speed of 955 rpm Fig. 2 shows the variation in friction coefficient for the carbide-steel tribo pair at 955 rpm speed. At speed of 955 rpm more variation in friction coefficient is observed and the wear loss is found to be stabilized after a distance of 400 m. (a) (b) Figure 3 (a) and (b): Friction coefficient and wear loss at the rotational speed of 420 rpm The friction coefficient is found to be more stable at the speed of 420 rpm as compared with 955 rpm. However, the wear loss tends to show an increasing trend without any stabilization. 2.2 Machining Experiments All the experiments are conducted on the three-axis miniaturized machine tool (MMT) as shown in Figure 4. Consisting of linear stages with 0.1 mm resolution and travel range of 150 mm in all three mutually perpendicular directions, namely X,Yand Z.Auniversal motion controller controls the movement of these stages. The machine tool has a high spindle speed with a radial run-out less than 1 mm and rotational speed ranging from 5000 to 100,000 rpm. The spindle speed is controlled by the frequency converter which allows infinitely variable speed within its speed range. The spindle is provided with sealing air which prevents chips/debris from getting into it. The air outlet holes are arranged along the periphery at the bottom of the spindle housing. Since the compressed air is not directed towards the drill point, the condition is to be treated as 'drilling without coolant'. 174 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Figure 4: Micro Milling Experimental Setup Table 3: Specifications of Miniaturized Machine Tool and experimental conditions S.No Specifications Data 1 Make of Linear stages New port corporation, USA 2 Maximum speed ( mm/s) 100 3 On Axis Accuracy (µ m) 2 4 Uni- directional repeatability ( µ m) 0.2 5 Weight (kg) 4.8 6 Spindle speed (rpm) 1,00 ,000 Specificatio ns of Micro- Mill: 1 Diameter of the cutter 0.2 – 0.5 mm 2 Shank Diameter, D 4 mm 3 Effective Flute Length, l 0.8 – 2 mm 4 Total Length, L 45 mm 5 Shoulder angle, q 9º, 15º (a) Schematic representation of a micro milling cutter (b) SEM image of a typical micro milling cutter Figure 5: Micro milling cutters ISBN: 978-0-13-601970-1 175

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Micro-machining experiments were carried out to evaluate the tool wear characteristics and to find the feed force (Fx) and Transverse force (Fy). Fig. x shows the sample with micro channels machined on it. Figure 6: Machined work piece for micromachining The force signals were extracted from the dynamometer by Kistler software and the interface with the force signal is shown in Fig. 7 and Fig. 8 for circular and square pattern respectively. Figure 7: Dynoware window showing variations in cutting force for circular pattern Figure 8: Dynoware window showing variations in cutting forces for square pattern 176 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) The force signals are then extracted after filtering which is shown in Fig. 9 (a) and (b) for Fx and Fy respectively. (a) (b) Figure 9: variation of cutting forces for 0.25 mm/sec in Fx and Fy The peak feed force at 0.25 mm/sec feed is identified as 0.45 N and similarly the maximum transverse force is estimated to be around 0.4 N. Similar force evaluation is done by varying the feed from 0.25 m/sec to 0.4 mm/sec and the results are plotted in Fig10. (a) (b) Figure 10: variation of cutting forces for 0.4 mm/sec in Fx and Fy The maximum feed and transverse forces are found to be about 0.65 N and 0.15 N respectively. An increase in the feed force is observed when the feed is increased from 0.25 mm/sec to 0.4 mm/sec. However, the feed is found to have negative effect on the transverse force which shows a decreased peak force. 3. ANALYSIS OF TOOL WEAR ImageJ is a public domain Java image processing and analysis program inspired by NIH Image for the Macintosh. It can calculate area and pixel value statistics of user-defined selections. It can measure distances and angles. It can create density histograms and line profile plots. It supports standard image processing functions such as contrast manipulation, sharpening, smoothing, edge detection and median filtering. ISBN: 978-0-13-601970-1 177

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Table 4: Tool wear analysis in Image Software, diameter of milling cutter is 5mm, speed 25000 rpm and cutting speed 62.8 m/min S.No Type of Feed Before After Difference in p attern (mm /sec) m achining machining area(µm2) 59582.900 57580.864 2002.036 1. circular 0.25 59582.900 55273.685 4309.215 0.4 59582.900 56371.623 3211.277 2. circular 0.25 59582.900 54428.563 5154.337 0.4 3. square 4. square The SEM images of micro-mill tool before and after machining are shown in Fig 11 for circular pattern machining. It is clearly observed in the figure that the edge of the tool has fractured after machining. (a) (b) Figure 11: SEM images of 0.5 mm Mill for circular pattern (a) & (b) before and after machining Similarly, the cutting tool before and after square pattern machining is observed under SEM and is shown in Fig 12. No tool fracture is observed in case of square pattern machining. (a) (b) Figure 12: SEM images of 0.5 mm Mill for square pattern (a) & (b) before and after machining 4. SIMULATION OF CUTTING FORCES There are different constitutive equations available to model flow stress of the work piece material out of that Johnson-Cook constitutive equation is widely used. The Johnson-Cook equation is based on experientially determined flow stresses as a function of strain, temperature and strain rate in separate multiplicative terms. This equation therefore does not consider the interactions between the terms. The model is relatively easy to apply to FEM and hence has been used in many studies. 178 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Where A = Yield strength of work material (MPa) B = Strain Hardening modulus (MPa) C = Strain rate sensitivity coefficient m = Thermal softening coefficient n = Hardening coefficient € = Strain rate (/s) €o= Reference strain rate (/s) €= Plastic Strain Table 5: J-C model constants forAISI410 stainless steel Constant A B nC m AISI410 450 738 0.388 0.02 0.8 The work piece, Tool material properties are defined in pre process step are shown in table 5 and table 6. Tool material selected is uncoated Tungsten Carbide. Table 6: Properties of Workpiece and Tool Work piece Tool Type of Mesh Tetrahedral mesh Number of nodes Number of Elements 10558 Material 48888 Mesh AISI410 Tungsten carbide Thermal conductivity (w/mk) Heat capacity(j/kgk) 21678 20572 Friction factor 121 50 Youngs modulus (Gpa) Elastic modulus (Gp a) 875 400 Poisson's ration 0 .5 0.5 190 600 73 534 0.33 0.22 (a) (b) 179 Figure 13: Deform 3D Window showing Force in X and Y direction ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Figure 14: Variation of Effective Stress and Strain The cutting forces simulated using Deform 3D in x and y direction are shown in Fig. 13 and the effective stress strain values are shown in Fig.14. Though the FEM analysis were efficient in estimating the machining forces both in the feed and transverse force. This is mainly because ideal conditions were taken for tool and work material whereas in real working condition, the inhomogenity of the material, sharpness of the cutting edges plays critical role. 5. RESULTS AND DISCUSSIONS The cutting forces variation of load distribution between FEA simulation and experimental work are shown in table 7. Table 7: Comparison of Simulation and Experimental results with depth of cut 0.5mm Simulation Experimental Feed (mm/rev) Fx (avg) Fy (avg) Fx (avg) Fy(avg) 0.25 14.3 11.5 0.06 0.36 0.4 10.6 8.32 1.36 0.61 13.2 10.5 0.05 0.33 11.5 10.9 0.33 1.08 The present work investigated the effect of tool wear on machining process. Further, an attempt has been made to simulate the micro-milling process by Finite Element Method using Deform3D software. The present work can be extended further in future to implement more realistic material parameters in the FEM simulation so that the results can be obtained more close to the experimental data. 6. CONCLUSION The objective is to study the tool wear and tool failure of the micro tools. For the first time an attempt has been made to investigate the micro tool wear in milling. In the present work, pin-on-disk wear tests were carried out at different speeds, track diameters and applied loads with tungsten carbide pin on a stainless steel disk to evaluate the wear and friction data dispersion. Wear test in micro milling process is performed on theAISI 410 stainless steel workpiece with tungsten carbide (WC) pin to determine the tool wear and tool life of the pin. The modeling procedure was first validated by using a theoretical solution developed for pin on disk and micro milling process. The machining experiments were carried out at different operating conditions to verify the proposed model. By understanding the wear, characteristics of tool and the tool geometry can be redesigned to achieve higher tool stiffness, reduce tool wear and to improve tool life. A model for predicting the cutting forces for the material AISI410 has been carried out. The tool wear in milling cutter have been estimated using SEM images and Image J analysis. The experiments of wear and cutting forces are compared with simulation. 180 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 7. REFERENCES [1] Bao. W.Y., and Tansel I.N. \"Modeling micro end milling operations. Part1: analytical cutting force model\" International Journal of Machine Tools and Manufacture, 40(15), 2155-2173. [2] Bhattacharyya .A and Ham .I, \"Analysis of tool wear- part 1: theoretical models of flank wear\". J-Eng. Ind 91(3);790- 796(1969). [3] Lee and Shaffer, \"The theory of plasticity applied to a problem of machining\", journal of applied mechanics,1951. [4] Lim S.C, Ashby M.F, Brunton J.H, \" Wear-rate transitions and their relationship to wear mechanisms\" Acta metallurgica, vol 35, june 1987. [5] Tauhiduzzaman M, \"Analytical modeling, experimental investigations and performance test of mist coolant on micro end milling operations\" 2005. [6] Tlusty.J and Macneil.P, \" Dynamics of cutting forces in end milling\", Ann. CIRP 24, 21 (1975). [7] Wright PK, \"Predicting the shear plane angle in machining from workmaterial strain hardening characteristics\" ,1982. [8] Xie lijing, Ding yue and Wang xibin, , Li lin, \"Study of the mechanisms and simulation of the tool wear process in machining of stainless steel with carbide tools,\" Key laboratory of Fundamental science for Advanced machining, School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing, china, 2008. [9] Yash R. Bhoyar, Prof.P.D. Kamble, \"FiniteElement Analysis on Temperature distribution in turning process using DEFORM- 3D,\" IJRET, Vol.2, Issue 5, May 2013. ISBN: 978-0-13-601970-1 181

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) Optimization of Operating Parameters of Wire EDM Using Design of Experiments Criteria Gondi Konda Reddy1, P.Vijay Anand2, Chandar Rathod3 1Associate Professor, 2,3Assistant Professor 1,2,3Sreenidhi Institute of Science and Technology, Hyderabad-501301 ABSTRACT Traditional machining techniques are being phased out in favour of nontraditional machining processes as the need for high surface quality and machining of complicated form geometries grows. One of the non-traditional machining methods is wire EDM. In many machining operations, material removal rate and surface roughness are critical. This procedure explains the Taguchi optimization approach for optimising WEDM for BRASS cutting settings. Brass is a zinc-based metal alloy. It's a popular material for gears, bearings, and locks. The goal of the project research was to find the best wire EDM process parameters for machining brass-based metals. The following process factors were considered: pulse on, pulse off, servo voltage, and input current, as well as the output responses: material removal rate (MRR), and surface roughness (Ra). The Taguchi L9 orthogonal array is used in the studies. Using signal to noise ratio graphs, the influence of each control component on the performance measure is investigated separately. The research shows that wire EDM process settings may be tweaked to improve material removal rate and surface quality. Taguchi approach is used to obtain the optimal set of process parameters. 1. INTRODUCTION Machining is the removal of raw materials from a workpiece. This is also known as a machine tool-based subtractive manufacturing technique. Machining maybe used to make things out of metals, wood, plastic, ceramics, and composites, among other materials. Computer numerical control (CNC), in which computers are utilised to control the movement and functioning of machines, is now employed in contemporary machining. Electrical discharge machining (EDM) is an unconventional thermoelectric technique that uses a series of discrete sparks between a work and tool electrode submerged in a liquid dielectric media to erode material from the work piece. The dielectric melts and vaporises a little portion of the work material, which is subsequently expelled and washed awayby the electrical discharges. By melting and evaporating the work piece material, the high-frequency sparks continuallyand effectively remove it. Between two electrodes, the dielectric works as a deionizing medium, and its flow evacuates resolidified material debris from the gap, ensuring ideal conditions for spark production. Metal is cut using a specific metal wire electrode in micro wire EDM (WEDM), which is set to go along a preprogrammed route. Researchers in the Soviet Union developed Wire EDM as a method for cutting steel to produce tools in the 1960s, which gave birth to electrical discharge manufacturing. In the United States, an Andrew Engineering Companyengineer called David H. Dulebohn paired Soviet EDM technologywith a computer that followed blueprints using optics. The development of Dulebohn led to the development of the CNC EDM machines that we use today. CNC EDM machines initially became accessible in 1976, and EDM technology and CNC Machining have continued to advance since then. Visit our History of EDM page for a more in-depth look at the history of electrical discharge machining. The metal production, die, and steel sectors have all benefitted from the introduction of wire EDM in the 1960s. It is the most fascinating and diverse machine tool made for industries in the previous fifty years, and it offers several benefits. Amoving wire follows a prescribed path and 182 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) removes material from the work piece in this operation. The basic components of a wire cut EDM machine are a machine proper with a workpiece contour movement control unit (NC unit or copying unit), workpiece mounting table, and wire driven section for precisely moving the wire at constant tension; a machining power supply that applies electrical energy to the wire electrode; and a unit that supplies a dielectric fluid (distilled water) with constant specific resistance. 1. Computerized Numerical Control (CNC) Consider this \"The Brains.\" 2. Power Supply Gives the spark a boost of vigour. Consider this \"The Muscle.\" 3. Mechanical Section Wire drive mechanism, worktable, workstand, and taper unit (This is the machine tool itself.) Consider this \"The Body.\" 4. Dielectric SystemThe water reservoir, which provides and maintains filtration, water condition (resistivity/ conductivity), and water temperature. Consider this \"The Nourishment.\" Working Principle of Wire Cut EDM Process: WEDM's material removal technique is quite similar to that of traditional EDM, which uses an erosion effect caused by electrical discharges (sparks). A sequence of discrete sparks between the workpiece and a moving wire electrode submerged in a liquid dielectric media erode the workpiece material in WEDM. The dielectric then ejects and flushes awayminute quantities of the work material melted and vaporised bythe electrical discharges. An electrostatic field of sufficient strength is generated when an appropriate voltage is built up across the wire tool and the workpiece, producing cold emission of electrons from the wire tool. The electrons that have been freed are speeding towards the anode. The electrons clash with the molecules of the dielectric fluid after achieving sufficient speed, breaking them into electrons and positive ions. Other electrons in the dielectric fluid molecules may be dislodged as a result of the electrons created.As a result, the two electrodes are connected by a thin column of ionised dielectric fluid molecules.Acompression shock wave is formed as a result of this spark, and a very high temperature is developed in the range of 8,000°C-12,000°C, or as high as 20,000°C. The minute electrode material melts and vaporises at this high temperature, and the molten metals are evacuated by a mechanical blast, leaving tiny craters on both the wire tool and the workpiece, as seen in Fig 1.2. However, workpieces attached to the positive terminal erode at a far higher pace than those connected to the cathode (wire tool). This is because the quantity of heat created at the anode location is quite high due to the conversion of electron kinetic energy into heat energy. WEDM's material removal method is quite similar to the traditional EDM technique, which uses an erosion effect caused by electrical discharges to remove material (sparks). A succession of discrete sparks between the workpiece and a moving wire electrode bathed in a liquid dielectric medium erode the workpiece material during WEDM. The dielectric ejects and flushes away minute quantities of work material melted and vaporised by the electrical discharges. An electrostatic field of sufficient strength is generated when an appropriate voltage is built up across the wire tool and the workpiece, producing cold emission of electrons from the wire tool. The electrons that have been freed are speeding towards the anode. The electrons clash with the molecules of the dielectric fluid after achieving sufficient speed, breaking them into electrons and positive ions. Other electrons in the dielectric fluid molecules may be dislodged as a result of the electrons created.As a result, the two electrodes are connected by a thin column of ionised dielectric fluid molecules.Acompression shock wave is formed as a result of this spark, and a very high temperature is developed in the range of 8,000°C-12,000°C, or as high as 20,000°C. The minute electrode material melts and vaporises at this high temperature, and the molten metals are evacuated by a ISBN: 978-0-13-601970-1 183

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) mechanical blast, leaving tiny craters on both the wire tool and the workpiece, as shown. However, workpieces attached to the positive terminal erode at a far higher pace than those connected to the cathode (wire tool). This is because the quantity of heat created at the anode location is quite high due to the conversion of electron kinetic energy into heat energy. 2. EXPERIMENTAL SETUP The experiments were carried out using a Pune-based Excetek EX400 Wire EDM machine tool. In the current research investigation, a 0.25 mm diameter zinc coated brass wire with a tensile strength of 900 N/mm2 was employed as a cutting tool for experimental examination. The studies employed WEDM process parameters such as pulse-on time, pulse-off time, input current, and servo voltage. The goal of this study is to use the Design of Experiments approach to analyse the output characteristics of a Wire Electrical Discharge Machine, such as material removal rate (MRR) and surface roughness (Ra). An orthogonal array was created using Taguchi's Design of Experiments in order to undertake experimental analysis with the fewest possible test runs (DoE). Mini-tab ver.19 was used to determine the orthogonal array, and the resulting L-9 orthogonal array is displayed in Table 2. The procedures for calculating the L-9 orthogonal array in Minitab version 19 are given below: 1. Open Minitab ver.19software 2. Click on Stat ? DoE ? Taguchi ? Create TaguchiDesign 3. A tab opens indicating Taguchi's design where we need to select the levels of design and number offactors 4. Select 3 level design ? Number offactors=3 5. Then click on options and select L-9 ?OK 6. Now a worksheet opens and the orthogonal array L-9 islisted. Minitab is a statistic programme created in 1972 by scholars Barbara F. Ryan, Thomas A. Ryan, Jr., and Brian L. Joiner at Pennsylvania State University. It originated as a simplified version of NIST's OMNITAB 80 statistical analysis application. Statistical analysis software like Minitab automates computations and graph production, allowing the user to concentrate more on data analysis and interpretation. It may be used with other Minitab, Inc. products. TABLE 1: Standard L-9 OrthogonalArray Run Pulse On Time (m secs) Pulse Off Time (m secs) Input Current (Amps) Servo Voltage(volts) 11 1 11 21 2 22 31 3 33 42 1 23 52 2 31 62 3 12 73 1 32 83 2 13 93 3 21 Preliminary experiments were carried out to determine the parameter range. The range is chosen based on the absence of defects. The smallest value is level-1, the highest value is level-3, and the approximate midway value is level-2 for each parameter. 184 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) TABLE 2: Levels chosen for input parameters S.No. Input Parameter Level 1 Level 2 Level 3 1. Pulse On Time (m secs) 6 9 12 2. Pulse Off Time (m secs) 10 15 20 3. Input Current (Amps) 38 41 44 4. Servo Voltage (volts) 5 10 15 The parameters specified in Table 2 are successively allocated to columns of the orthogonal array presented in Table 1, and the resulting orthogonal array is displayed in Table 3. Table 3 shows the L-9 orthogonal array following factor assignment. TABLE 3: L-9 Orthogonal Array after assignment of factors Run Pulse On-Time (m sec) Pulse Off-Time (m sec) Input Current (Amps) Servo Voltage (volts) 16 10 38 5 26 15 41 10 36 20 44 15 49 10 41 15 59 15 44 5 69 20 38 10 7 12 10 44 10 8 12 15 38 15 9 12 20 41 5 FIGURE 3 : EXCETEK EX400 WIRE EDM FIGURE 4: Test Specimen Before Machining ISBN: 978-0-13-601970-1 185

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) FIGURE 5:TESTPIECES OFBRASSAFTER CU 2.1 Design of Experiments (DoE) based on Taguchimethod: ATaguchi approach is used to simulate the Wire EDM process in order to examine the impacts of cutting parameters on cutting performance variables such as Surface Roughness and Material Removal Rate. For the objective of creating and enhancing product quality, the Taguchi technique, a strong tool for parameter design of performance characteristics, is employed in this study. Process characteristics that impact products are divided into two types in the Taguchi method: control variables and noise factors. The control factors are used to choose the ideal circumstances for design or manufacturing process stability, whereas the noise factors refer to all elements that create variance. Taguchi's S/N ratio is a performance metric for selecting control settings that best cope with noise. The S/N ratio considers both the mean and variability. It is the ratio of the mean to the standard deviation in its most basic form. The S/N equation is based on the requirement for the desired quality feature. In general, there are three scenarios: smaller is better, nominal is best, and larger is better.. The property that a greater number indicates better machining performance, such as Material Removal Rate, is treated as a larger-the-better kind of problem according to Taguchi-based approach. The S/N Ratio, or, may be computed using the formula below: n η=−10���������[1/n ∑1/y^2] j Surface Roughness, for example, is treated as a smaller-is-better kind of issue since the smaller number signals higher machining performance. The S/N Ratio (), or, may be computed using the formula below: η=−10���������[1∑��� y2] n j=1 Where Yij is the measured value of quality characteristic of ith trial and jth experiment and n is number of experiments in a trial. The following are the processes for generating the S/N ratios and mean values for Material Removal Rate in Minitab ver.19: 186 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 1. Open Minitab ver.19 software. 2. Enter the experimental values of Material removal rate in one column. 3. Click on Stat → DoE → Taguchi →Analyze Taguchi design. 4. A tab opens indicating Analyze Taguchi design. Click on required column i.e., Material removalrate→Select→Options→larger is better→OK→Storage→tick on Signal to Noise ratio and means →OK 5. The required S/N ratios and mean values of MRR are presented on the worksheet. 6. To obtain graphs click on Stat → DoE → Taguchi →Analyze Taguchi design. 7. A tab opens indicating Analyze Taguchi design. Click on required column i.e., Material removal rate → Select →Graphs →tick on signal to noise ratio and mean →OK→OK. 8. The required graphs of S/N ratios and mean values are obtained. The following are the methods to acquire the S/N ratios and mean values for Surface roughness in the Minitab ver.19 software: 1. Open Minitab ver.19 software. 2. Enter the experimental values of Surface roughness in one column. 3. Click on Stat → DoE → Taguchi →Analyze Taguchi design. 4. Atab opens indicatingAnalyze Taguchi design. Click on required column i.e., Surface roughness → Select →Options → smaller is better → OK→ Storage → tick on Signal to Noise ratio and means → OK 5. The required S/N ratios and mean values of Surface roughness are presented on the worksheet. 6. To obtain graphs click on Stat → DoE → Taguchi →Analyze Taguchi design. 7. A tab opens indicating Analyze Taguchi design. Click on required column i.e., Material removal rate → Select → Graphs → tick on signal to noise ratio and mean → OK→OK. 8. The required graphs of S/N ratios and mean values are obtained. 9. The response table for mean and S/N ratios can be taken from the sessions tab. 3. RESULTS AND DISCUSSION Table 4 shows the Material Removal Rate data for each run, as well as the signal to noise ratio (S/N) values derived and displayed in the same table. Table 5 shows the average S/N values for each parameter at three levels, as well as the average mean response characteristic. Table 6 shows the average mean response characteristic. For each parameter, the difference between the highest and minimum values () is calculated. The greater the difference in value, the greater the relative influence of the parameter on the quality feature. ISBN: 978-0-13-601970-1 187

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) TABLE 4: Material Removal Rate, S/N and Mean values for each run Pulse Pulse Off- Servo Input MRR S/N Ratio MEAN On-Time Time Voltage C urr en t (mm3/min) (msec) (volts) (A mp) 20 .68856 10.825 (msec) 10 10.825 19 .93461 9.9 25 6 15 38 5 9.925 17 .92501 7.8 75 6 20 41 10 7.875 21.6017 12.025 6 10 44 15 12.025 22 .04181 12.65 9 15 41 15 12.65 20.1079 10.125 9 20 44 5 10.125 23.8764 15.625 9 10 38 10 15.625 21 .41922 11.775 12 15 44 10 11.775 22 .79758 13 .8 12 20 38 15 13.8 12 41 5 TABLE 5: Response table for S/N ratios of MRR Level Pulse On-Time (msec) Pulse Off-Time (msec) Input Current (Amps) Servo Voltage (volts) 1 19.52 22.06 2 21.25 21.13 20.74 21.84 3 22.70 20.28 3 .18 1.78 21.44 21.31 Delta 1 2 Rank 21.28 20.32 0.71 1.53 43 TABLE 6: Response table for Means of MRR Level Pulse On-Time (msec) Pulse Off-Time (msec) Input Current (Amps) Servo Voltage (volts) 1 9.542 1 2.825 2 11.600 1 1.450 10 .908 12.4 25 3 13.733 1 0.600 4.192 2.22 5 11 .917 11.8 92 Delta 1 2 Rank 12 .050 10.5 58 1.142 1.867 43 Table 6 shows that input current is the most important parameter that affects the alloy's Material Removal Rate (MRR), followed by pulse on time and servo voltage. The pulse off time has the least impact. FIGURE 6: The impact of process variables on the average S/N ratio 188 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) FIGURE 7: The influence of process factors on the Mean MRR Figure shows the average S/N values for the process parameters at three levels depicted on a graph. Pulse on time-3, pulse off time-1, input current-3, and servo voltage-1, where 1, 2, 3 refer to the levels, are the best conditions for the highest UTS. Figure 6 shows the mean response of the material removal rate (MRR). It also depicts thesame ideal UTS maximisation circumstances. The average valueof the qualityattributeto be investigated is the mean response. Surface roughness is analysed in the same way, and the results are reported in Tables 7, 8, and 9. Table 9 shows that input current is the most important factor affecting surface roughness (Ra), followed by pulse on time. The pulse off time is the characteristic that has the least impact. TABLE 7: Surface Roughness, S/N and Mean values for each run Pulse On- Time Pulse Off- Time Servo Input Current Surface S/N Ratio MEAN (mSec) (mSec) 6 10 Voltage (V) (Amp) Roughness(μm) 6 15 6 20 38 5 3.5 -10.8814 3.5 9 10 9 15 41 10 2.8 -8.9432 2.8 9 20 12 10 44 15 3.0 -9.5424 3.0 12 15 12 20 41 15 2.9 -9.2480 2.9 44 5 3.2 -10.1030 3.2 38 10 2.6 -8.2995 2.6 44 10 3.4 -10.6296 3.4 38 15 2.5 -7.9588 2.5 41 5 3.6 -11.1261 3.6 TABLE 8: Response table for S/N ratios of Surface Roughness Level Pulse On-Time (Sec) Pulse Off-Time (Sec) Servo Voltage (V) Input current (AMP) 1 -9.789 -10.253 -9.047 -10.703 2 -9.217 -9.002 -9.772 -9.291 3 -9.905 -9.656 -10 .092 -8.916 0.688 10251 1.045 1.787 Delta 4 2 3 1 Rank ISBN: 978-0-13-601970-1 189

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) TABLE 9: Response table for Means of Surface Roughness Level Pulse On-Time (Sec) Pulse Off-Time (Sec) Servo Voltage (V) Input Current (AMP) 1 3.100 3.267 2.887 3.433 2 2.900 2.833 3.100 2.933 3 3.167 3.067 3.200 2.800 0.267 0.433 0.333 0.633 Delta 4 2 3 1 Rank Figure 8 shows the average S/N values of surface roughness, whereas Figure 9 shows the mean response of surface roughness. The ideal settings for minimising of surface roughness are pulse on time-2, pulse off time-2, input current-1, and servo voltage-2, as shown in Figures 4 and 5. FIGURE 8: Surface Roughness S/N Ratio Average Effect of Process Parameters FIGURE 9: The influence of process variables on the mean surface roughness 190 ISBN: 978-0-13-601970-1

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) 4.1 Prediction of optimum conditions for thecharacteristics It can be observed from the examination of the S/N ratio and the mean response characteristic that pulses on time-3 provide higher mechanical qualities, such as material removal rate and surface roughness. The material removal rate is better with pulse off time-1, and the surface roughness is better with pulse off time-2. The graphs show that Pulse off time-1 & 2 gives almost equal surface finish whereas Pulse off time-1 gives better material removal rate. Hence pulse off time-1 can be considered as an optimum level of parameter. Input current-3 gives maximum material removal rate and Input current-1 gives minimumsurfaceroughness.Servovoltage- 1givesbettermaterialremovalrateandservovoltage- 2 gives better surface roughness. Table 10 calculates and displays the projected values of quality attributes at the optimal situation. Table 10: At the ideal situation, predicted values of quality attributes S.No. Quality Pulse on time-3 Pulse off time-1 Input current-3 Servo voltage-2 ch aracteristics 13.733 12.825 12.050 12.425 1. MRR 3.167 3.267 2.800 3.100 2. Surface Roughness (Ra) 4. CONCLUSION The goal of this study is to find the best wire electrical discharge machining (WEDM) process parameters for BRASS as a workpiece. Using Taguchi's L9 orthogonal array, which was built based on design of experiments, a number of tests were carried out with a wide variety of process parameters. Taguchi's method was used to determine the best combinations of process parameters for each response characteristic using a single objective optimization strategy. Based on the experimental findings and Taguchi analysis, the following conclusions were drawn: 1. Wire EDM can be used to perform machining process on high-strength material such as BRASS with better material removalrate. 2. TheimportantprocessparametersaffectingtheWEDMofBRASShavebeenidentified as PULSE OFF TIME for response of material removal rate (MRR) 3. TheimportantprocessparametersaffectingtheWEDMofBRASShavebeenidentified as PULSE OFF TIME for response SurfaceRoughness. 4. For MRR and Surface Roughness operation, it was noticed that wire PULSE OFF TIME is most affecting input process parameters ofWEDM. 5. The process parameters of optimal factor/level combination for Material removal rate are obtained by employing Taguchi's method as optimization technique. Pulse on time 12 msecs, Pulse off time 10 msecs, Input current 10 amps, Servo voltage 44 volts are recommended. 6. The process parameters of optimal factor/level combination for surface roughness is obtained by employing Taguchi's method as optimization technique. Pulse on time 12 msecs, Pulse off time 15 msecs, Input current 15 amps, Servo voltage 38 volts are recommended. ISBN: 978-0-13-601970-1 191

Proceedings of the 3rd National E-Conference on Emerging Trends in Mechanical Engineering (ETIME-2021) REFERENCES 1. Singh PN, Raghukandan K, Rathinasabapathi M, Pai BC. Electric discharge machining of Al-10%SiCPas- castmetalmatrixcomposites.Journalofmaterialsprocessingtechnology. 2004 Nov 30;155:1653-7. 2. Kumar, S. Suresh. \"Fabrication and Machining Studies of Al 6351 SiC B4C HybridMetal Matrix Composite.\"(1916). 3. Shandilya P, Jain PK, Jain NK. Modeling and analysis of surface roughness in WEDC of SiCP/6061 Al MMC through response surface methodology. International Journal of Engineering Science and Technology. 2011Jan;3(1):531-5. 4. Shah CD, Mevada JR, Khatri BC. Optimization of process parameter of wire electrical dischargemachinebyresponsesurfacemethodologyonInconel-600.InternationalJournal of Emerging Technology and Advanced Engineering. 2013Apr;3(4):2250-459. 5. Kishore G.C, ArunaDevi.M and Prakash C.P.S \"Parametric Optimization of Wire Electrical Discharge Machining by Taguchi Technique on Composite Material\" InternationalJournalofEngineeringResearch&Technology,Vol.4,Issue09,ISSN:2278- 0181,Sep-2015 6. Sudhakara D, Prasanthi G. Review of research trends: Process parametric optimization of wire electrical discharge machining (wedm). International Journal of Current Engineering and Technology.2014;2(1):131-40. 7. Gadakh. V.S, 2012, Parametric Optimization of Wire Electrical Discharge Machining using Topsis Method, Advances in Production Engineering andManagement 8. DhakadAK,VimalJ.MultiresponsesoptimizationofwireEDMprocessparametersusing Taguchi approach coupled with principal component analysis methodology. International Journal of Engineering, Science and Technology.2017;9(2):61- 74. 9. Liao YS, Huang JT, Su HC. A study on the machining-parameters optimization of wire electrical discharge machining. Journal of materials processing technology. 1997 Nov 23;71(3):487-93. 10. Tsai KM, Wang PJ. Predictions on surface finish in electrical discharge machining based upon neural network models. International Journal of Machine Tools and Manufacture. 2001 Aug1;41(10):1385-403. 11. Chen DC, Jhang JJ, Guo MW. Application of Taguchi design method to optimize the electrical discharge machining. Journal of Achievements in Materials and Manufacturing Engineering.2013;57(2):76-82. 12. Trivedi KM. A REVIEW PAPER ON PARAMETRIC ANALYSIS OF ELECTRIC DISCHARGE MACHINING USING TAGUCHIMETHOD. 13. LajisMA,RadziHC,AminAK.TheimplementationofTaguchimethodonEDMprocess of tungsten carbide. European Journal of Scientific Research.2009;26(4):609-17. 192 ISBN: 978-0-13-601970-1