Analysis of Energy Distribution in Sinker EDM Process by GRD Journals

GRD Journals- Global Research and Development Journal for Engineering | Volume 1 | Issue 12 | November 2016 ISSN: 2455-5703

Analysis of Energy Distribution in Sinker EDM Process Kumari Nilu Department of Mechanical Engineering Saroj Institute of Technology and Management, Lucknow- 226021, U.P (India) Mr. Abhishek Singh Department of Mechanical Engineering Saroj Institute of Technology and Management, Lucknow226021, U.P (India)

Mr. Amit Kumar Singh Department of Mechanical Engineering Saroj Institute of Technology and Management, Lucknow226021, U.P (India)

Abstract Electro Discharge Machining (EDM) is used for machining electrically conducting /semi conducting, tough and brittle material .This process is best suited for making intricate cavities and contour, dies, section of complex geometry, moulds. The work piece material selected for this study is mild steel and tool is copper electrode. Dielectric flow rate, discharge current, pulse on time, pulse off time is considered as input parameters. In the present work ANOVA analysis is used to study the significance of process variable on Material Removal Rate (MRR) and Tool Wear Rate (TWR) by using simple conduction equations, we can calculate the energy transferred to each for material removal rate and tool wear rate. Also energy transferred to work piece, tool and dielectric fluid can be calculated by using conduction equation, convection equation, energy carried away by debris, and the best suited input parameters can be found for the maximum energy transfer to work piece. After than energy responsible for tool wear were calculated and the optimum parameter are found in order to minimize the tool wear The energy distribution in the electrical discharge machining (EDM) process is most important phenomenon for study the variation of fraction of input discharge energy with the help of thermo-mathematical models during EDM of mild steel by varying the machining parameter current and pulse duration. Keywords- EDM, Conduction, Convection, MRR, TWR

I. INTRODUCTION Electric discharge machining is nonconventional manufacturing process uses spark for material removal.EDM is used for deep cutting, for sharp inside corner complicated shape, mould making tool and die industries, machining of geometrically complex, hard material with accuracy, nonconventional machining process uses sound, light, electrical and chemical form of energy .High accuracy surface finish can be obtain with non-conventional machine where electrical form of energy is used. One of the main advantages of EDM is a consequence of the thermal process. It is based on Eroding material by melting and evaporation, so the hardness of the work piece is no limitation for machining. Even the hardest steel grades can be machined with almost same machining speed as for softer steels. Drilling, milling, grinding and other conventional machining operations are replaced by electric discharge machining. Tool or electrode, work piece dielectric liquid are used for extremely tough and brittle electrically conductive materials in the process of making moulds, dies, section of complex geometry and intricate shapes desired shape is obtained by using spark process is not making actual contact between tool and work piece .The electric spark produces huge amount of heat melting work piece but it must be controlled carefully .The increase in temperature during working of EDM is up to 800-1200â&#x201E;&#x192;. No direct contact between electrode and work piece so no stress is produced. EDM process is used in aerospace automobile and electronic industry to making prototype and production parts of difficult material .For fulfilling this requirement EDM machine has been developed. in the field of medical and surgical instrument, sports aerospace, automobile and electronic industries including automobile and electronic industries automotive R & D areas EDM is used. Super alloys, high-tech ceramics heat resistant steels can be easily machined with EDM.

II. LITERATURE REVIEW H. Singh et al. (2012) study that energy distribution in the Electrical Discharge Machining (EDM) process influences the material removal rate, and other machining characteristics like crater geometry, relative wear ratio and surface roughness. During this process the electrical energy is converted into heat energy and this energy is distributed among the electrode, work piece and the dielectric fluid. The fraction of the energy which is transferred to the work piece is the useful energy and this energy should be maximum, for optimum utilization of energy. This fraction of energy is one of the important parameters used in the existing

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thermo-physical models of EDM process. Due to apparent incongruities and conflicting data early researchers conjectured the same value of fraction of energy transferred to electrodes for all machining parameters in their models for numerically calculating the volume and geometry of the crater formed. This assumption is one of the reasons of error in the models from the experimental data. So this study is planned to experimentally study the variation of this fraction of input discharge energy with the help of thermo-mathematical models during EDM of Tungsten-Carbide by varying the machining parameters current and pulse duration. The data calculated in this study can be further used in the existing thermos physical models, expecting to bring the models preciously more close to the real conditions. This data will also be helpful for numerically calculating the optimum parameters using optimum value of the fraction of energy transferred to the electrodes especially work piece. The results obtained showed that the energy effectively transferred to the work piece varies with the discharge current and pulse duration from 6.5% to 17.7%, which proves that the fixed value assumed in the models is not in line with real EDM process. Akira Okada et al.(2000) determined the energy distribution using graphite tool electrode by measuring temperature at different point in work piece, tool and dielectric and later on putting these values in conduction, convection equations. The convection energy is very less compared to that of conduction, so is neglected. It was concluded that MRR depends upon energy density and tool wear depends upon adhesion of heat resolved carbon from machining fluid. With increase in discharge current energy transferred to work-piece increases. Kerosene performs better than de-ionized water as a dielectric in terms of energy transferred to electrodes. Energy transferred to various parts at different parameter are represented graphically.

III. EXPERIMENT DETAILS Table 1: Mild steel is chosen as work piece having diameter =9.85mm and Copper as a tool having diameter =9.45mm.Isopropyl alcohol is used as dielectric fluid. Properties Work piece(Mild steel) Tool or electrode (copper) Melting point ( ) 1425℃ to 1540℃ 1083℃ Boiling point( ) 2862℃ 2570℃ Density ( ) 7.83 g/ cm3 8.9 g/ cm3 272kJ/kg 207 kJ/kg Latent heat of fusion( ) 6090 kJ/kg 4730kj/g Latent heat of vaporization ( ) Specific heat (C) 0.465 J/g ℃ 0 .385 j/g℃ Thermal conductivity (K) 53.6 w/mk 385 w/mk

A. Experimental Set-Up and Procedure In this experiment used mild steel as a work piece and cooper as a tool (electrode) both are cylindrical shape experiment were conducted by using sink EDM. Dielectric fluid used for cooling as well as flushing of wear material during experiment called as EDM oil, sometime used ordinary fluid such as a kerosene , water etc. but in my experiment used isopropyl alcohol as a EDM oil. Here used Teflon as a insulating material for work piece and tool so that no energy is transmitted radially through the work piece and electrode during experiment. Table 2: Fixed Parameters Voltage 60V Pulse off time 10 µs Straight or positive polarity Polarity Work piece – Anode (positive) Electrode – Cathode (negative)

The temperature at different location of work piece, electrode, and dielectric fluid was measure by j-type thermocouple having range 0 to 600 degree Celsius. Thermocouple attached with temperature indicator having least count one degree Celsius. The Thermocouples were inserted in the space provided in the Teflon insulation at points 1,2 around work piece and 3,4 around electrode at distance of L1, L2, L3 as shown in Fig.2 . T1 and T2 are the temperature of work piece at upper and lower end and T3 and T4 are temperature of electrode at lower and upper end as shown in Fig.1. Also Thermocouples were fixed in the suitable arrangement to measure the temperature of dielectric fluid at different locations, Td1 Td2 are the temperature measured in dielectric fluid. Table 3: Variable parameters Discharge current (A) 2 10 18 Pulse duration (µs) 50 150 250

Fixed parameter are those which does not varies with every experiment while variable parameter are those parameter which varies with every experiment so as to find the Optimum parameters where there is a better utilization of energy and material removal rate as shown in Tables 2and 3 respectively. By using different variable parameter on sink EDM with mild steel and cooper as a work piece and electrode respectively to perform individual experiment. Temperatures of the individual measuring points were measured with the help of Thermocouples before each experiment as well as after different machining duration of the process. The time of machining has been noted on the monitor of the electrical discharge machine or stop watch, and the observations are given in Tables 4 and 5. The material removal rate MRR, in mm3/min. has been calculated at the time where steady state temperature is obtained using the results of Tables 4 and 5. The MRR at different current density and at

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different pulse duration after achieving the steady state condition is given in Table 4. Material removal rate was calculated by measuring the Weight before and after individual experiment by which calculate weight loss after per unit time which may be converted into volume per unit time by dividing loss weight per unit time with material density.

Fig. 1: Current, I(A) 2 2 2 10 10 10 18 18 18 Current I(A) 2 2 2 10 10 10 18 18 18

Fig. 2:

Table 4: calculation of material removal rate (initial temperature=34) Pulse Duration Ti(Âľs) L1w(mm) L2w(mm) L3w(mm) T1(oC) T2(oC) Td1(oC) 50 19.73 27.48 57.98 52 42 36 150 20.07 27.75 56.04 55 44 37 250 19.96 27.77 56.79 58 45 37 50 19.79 28.45 56.38 51 42 37 150 19.85 27.61 56.81 55 42 38 250 20.28 27.97 52.53 93 52 38 50 19.29 28.11 58.15 69 45 38 150 19.76 28.17 57.49 85 52 39 250 19.67 28.32 55.64 90 54 39 Table 5: calculation of tool wear rate (initial temperature=34) Pulse DurationTi(Âľs) L1E (mm) L2E(mm) L3E(mm) T3(oC) T4(oC) Td1(oC) 50 20.64 26.50 49.99 59 51 36 150 23.98 24.66 48.59 60 50 37 250 21.63 26.57 49.99 62 51 37 50 21.80 24.72 50.25 58 49 37 150 21.51 25.67 49.03 59 51 38 250 21.46 25.69 49.81 100 69 38 50 20.51 23.74 49.91 69 61 38 150 22.16 26.68 49.25 80 71 39 250 22.53 24.56 49.15 94 70 39

Td2(oC) 34 34 34 34 35 35 35 36 35

Vw (mm3/min) 1.4097 2.2098 0.9797 16.0975 20.7670 19.7670 14.6687 22.6810 25.2893

Td2(oC) 34 34 34 34 35 35 35 36 35

VE(mm3/min) 0.3507 0.5611 0.1804 2.1918 0.8328 1.4466 3.8576 3.3006 0.7014

1) Analysis of Variance (ANOVA) for SN ratios Experiment No. 1 2 3 4 5 6 7 8 9

Table 6: MRR and TWR and their correspondence SN ratio Peak Current Pulse on Time MRR SN Ratio for MRR TWR 2 50 1.4097 2.9825 0.3507 2 150 2.2098 6.8871 0.5611 2 250 0.9797 -0.1781 0.1804 10 50 16.0975 24.1352 2.1918 10 150 20.7670 26.3475 0.8328 10 250 19.7670 25.9188 1.4466 18 50 14.6687 23.3278 3.8576 18 150 22.6810 27.1132 3.3006 18 250 25.2893 28.0587 0.7014

SN Ratio for TWR 9.1013 5.0192 14.8753 -6.8160 1.5892 -3.2070 -11.7263 -10.3719 3.0807

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Fig. 3: Mean effect plot for MRR

The above main effects plot for means shows the relation between the parameters of EDM and MRR. Both the plots show that with increase in process parameters the value of MRR increases. At initial level of parameters, the MRR increases gradually but with further increase in the level of current and pulse on time, the value of MRR increases at a very slow pace. Peak Current is the most dominating factor and it can be seen from the plot that the MRR increases at a higher rate as compared to pulse on time. The MRR increases because, with increase in the value of peak current, the intensity of spark increases and hence large craters are formed on the work piece which results in higher MRR at higher value of parameters.

Fig. 4: Mean effect plot for TWR

The above main effects plot for means shows the relation between the parameters of EDM and TWR. The first plot shows the relation between TWR and Current, which indicates that with increase in current the value of TWR increases. This is due to the fact that the intensity of spark increases with increase in the level of Current and hence the TWR increases. Peak current is the most dominating parameter for TWR. Pulse of time is the second most dominating factor for TWR. Itâ&#x20AC;&#x2122;s seen from the plot that TWR decreases with increase in pulse on time. This is because with increase in pulse on time, the intensity of spark decreases and hence the TWR decreases. Table 7: Response Table for Signal to Noise Ratios for MRR (Larger is better) Level I Ton 1 3.230 16.815 2 25.467 20.116 3 26.167 17.933 Delta 22.936 3.301 Rank 1 2

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Table 8: Response Table for Signal to Noise Ratios for TWR (Smaller is better) Level I Ton 1 9.665 -3.147 2 -2.811 -1.254 3 -6.339 4.916 Delta 16.004 8.063 Rank 1 2 Table 9: ANOVA for MRR Source DOF SS Adj MS F Contribution % I 2 679.12 339.56 41.69 90.16 Ton 2 41.56 20.78 2.55 5.52 Error 4 32.58 8.14 4.32 Total

753.25

It is seen from ANOVA that the contribution of Peak Current is highest and is 90.16% and it is the most dominating factor for MRR followed by Pulse on time with a contribution of 5.52%. Source I Ton Error

DOF 2 2 4

Total

Table 10: ANOVA for TWR SS Adj MS F 7.6330 3.8165 41.69 2.7874 1.3937 2.55 3.8876 0.9719

Contribution % 53.35 19.48 27.17

14.3079

It’s seen form the above table that the contribution of Peak current for TWR is highest and is the major influencing parameter with a contribution of 53.35% while the contribution of pulse on time is only 19.48%. 2) Analysis of Energy The input energy per unit time is as follows: = V*I*DF*η Where V = Input voltage I = Supply current in ampere DF = Duty factor η = Relative frequency 3) For Work Piece Energy loss due to heat conduction into work piece is given by (

)

(

Energy carried away by worn debris of work piece is given by ( ) * (

) )

4) For Electrode Energy loss due to heat conduction into electrode is given by (

)

Energy carried away by worn debris of electrode is given by ( ) * ( Heat convection from dielectric fluid is given by = (Tm – Ta) As = surface area The residual energy Q9 is given below: Input – total energy Current (A) 2 2 2 10 10

Pulse Duration Ti(µs) 50 150 250 50 150

(

) )

Table 11: Energy transfer to Work piece(W) Energy transfer to Electrode(W) Econd Edeb Econd Edeb 1.48556 1.4129 8.1478 0.30762 1.61822 2.2147 10.9446 0.49217 1.91106 0.9819 11.1737 0.15824 1.29142 16.1335 9.8263 1.92253 1.92213 20.8134 8.4112 0.73049

Energy transfer to Dielectric fluid(W) 21.9919 23.8398 23.8398 23.8398 27.6214

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10 18 18 18

250 50 150 250

Win (Input electrical energy) 100.00 100.00 100.00 562.50 562.50 562.50 1038.46 1038.46 1038.46

5.98409 3.48544 4.78227 5.18939

19.8112 14.7015 22.7317 25.3458

32.5680 1.26888 9.0950 3.38369 9.1044 2.89512 26.3741 0.61523 Table 12: Energy distributed into Energy distributed into % of Energy distributed into work piece electrode work piece 2.8984 8.4554 2.89841 3.8330 11.4368 3.83296 2.8929 11.3319 2.89295 17.4249 11.7488 3.09776 22.7355 9.1417 4.04188 25.7953 33.8369 4.58583 18.1869 12.4787 1.75134 27.5140 11.9995 2.64950 30.5352 26.9893 2.94043 Table 13: Energy distribution ratio in fraction Work piece Electrode Dielectric fluid Econd Edeb Econd Edeb 0.0148556 0.0141285 0.081478 0.0030762 0.366532 0.0161822 0.0221474 0.109446 0.0049217 0.283808 0.0191106 0.0098189 0.111737 0.0015824 0.220739 0.0022959 0.0286817 0.017469 0.0034178 0.056762 0.0034171 0.0370016 0.014953 0.0012986 0.051151 0.0106384 0.0352199 0.057899 0.0022558 0.092071 0.0033564 0.0141570 0.008758 0.0032584 0.028417 0.0046052 0.0218898 0.008767 0.0027879 0.058351 0.0049972 0.0244071 0.025397 0.0005924 0.039091

27.6214 27.6214 31.5096 29.5527 % of Energy distributed into electrode 8.4554 11.4368 11.3319 2.0887 1.6252 6.0155 1.2017 1.1555 2.5990

B. The Variations of Energy Distribution Ratios with Discharge Current

Fig. 5:

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Fig. 6:

Fig. 7:

IV. CONCLUSION Following conclusions can be drawn from the analysis of the results: 1) Machining rate increases with the increase in current due to predominant increase in spark energy. Current is the most significant factor for MRR while pulse duration and duty factor has less significant factor for MRR. 2) Energy distributed into electrode is higher than energy distributed into work piece at lower current but it vice versa for higher current, distributed energy include both conduction energy & energy carried away by debris. Energy distribution increase with pulse duration for both work piece and electrode. 3) Energy transfer into work piece increase with increasing current while in case of electrode energy transfer decrease with increasing current. 4) The energy loss due to conduction into electrode is larger than that into work piece regardless of the discharge duration, As the pulse duration is shorter the energy loss due to conduction into electrode and work piece becomes larger. 5) The ratios of energy distributed into electrode and work piece are almost constant regardless of discharge duration. The ratio of energy distributed into work piece becomes larger with an increase of discharge current. 6) Material removal rate mainly depends upon some constant parameter such as thermal conductivity, melting points of material, and dielectric fluid properties , because of low thermal conductivity of material has ability to transfer conduction energy is also low at steady state which result rate of cooling at spark end slower cause higher material removal rate. Material having low melting point required less energy to melt (or evaporate).

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