Experimental Study Using Different Tools/Electrodes E.G. Copper, Graphite on M.R.R of E.D.M Process and Selecting The Best One for Maximum M.R.R in Optimum Condition
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This document presents research on comparing the performance of copper and graphite electrodes in an electrical discharge machining (EDM) process. Experiments were conducted to determine the effect of process parameters like current, impulse duration, and spark gap on the material removal rate (MRR) of mild steel. Regression analysis was used to develop a model relating the process parameters to MRR. The results showed that at lower parameter levels, graphite electrodes produced a higher MRR. However, as the parameter levels increased, copper electrodes provided a higher MRR. It was concluded that graphite electrodes are best for lower parameter levels and finishing work due to lower MRR, while copper electrodes are suitable for high material removal processes with less emphasis on surface finish
![International Journal of Modern Engineering Research (IJMER)
www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645
www.ijmer.com 1265 | Page
Level of Observation:-
Control parameters Level Observed value
Min. level Max. level
Current
(Amp.)
7 10 M.R.R.(mm3/min)
Impulse Duration
(µs.)
12 18 M.R.R. (mm3/min)
Spark Gap
(mm.)
0.08 0.26 M.R.R.(mm3
/min)
Table -1: Result of experimental value
SL.
NO.
Current
(Amp.)
Impulse
Duration
(µs.)
Spark Gap
(mm.)
A B C Material
Removal Rate
{M.R.R.}
(mm3
/min)
1 7 12 0.08 -1 -1 -1 1.975
2 7 12 0.26 -1 -1 1 2.76
3 7 18 0.08 -1 1 -1 8.38
4 7 18 0.26 -1 1 1 8.38
5 10 12 0.08 1 -1 -1 14.28
6 10 12 0.26 1 -1 1 8.36
7 10 18 0.08 1 1 -1 18.41
8 10 18 0.26 1 1 1 10.17
Here current, Impulse Duration and Spark Gap denoted as A, B and C. Equation (1) can be rewritten as in (2)
Y = Co + Ca*A + Cb*B + Cc*C + Cd*A*B + Ce*A*C + Cf*B*C (2)
Normal equations are:
∑Y = nCo + Ca∑A + Cb∑B + Cc∑C + Cd∑ A*B + Ce*∑A*C+ Cf∑B*C (3)
∑Y*A = Co ∑A + Ca∑A2
+ Cb∑A*B + Cc∑A*C + Cd∑A2
*B + Ce*∑A2
*C +Cf∑A*B*C (4)
∑Y*B = Co ∑B + Ca∑A*B + Cb∑B2
+ Cc∑B*C + Cd∑A.B2
+ Ce*∑A*B*C+ Cf∑B2
*C (5)
∑Y*C = Co ∑C + Ca∑A*C + Cb∑B*C + Cc∑C2
+ Cd∑A.B.C + Ce*∑A*C2
+ Cf∑B*C2
(6)
∑Y.A.B=Co∑A.B+Ca∑A2
B+ Cb ∑AB2
+Cc∑A.B.C+ Cd∑A 2.
B2
+ Ce*∑A2
*B*C + Cf ∑A.B2
.C (7)
Y∑A*C = Co∑A*C +Ca∑A2
*C+ Cb∑A*B*C+ Cc∑A*C2
+ Cd∑A2
.B*C+ Ce*∑A2
*C2
+ Cf∑A*B*C2
(8)
∑Y*B*C =Co∑B*C +Ca∑A*B*C+ Cb∑B2
*C+ Cc∑B*C2
+ Cd∑A.B2
*C+ Ce*∑A*B2
*C+ Cf∑B2
*C2
(9)
Equation of the fitted model for MRR from solving above equations:
MRR = – 64.7089 + [(7.323 * current) + (2.402 * Impulse duration) + (119.229 * Spark gap) – {0.167 *(current *
Impulse duration)} – {13.759 *(Current * Spark gap)} – {1.398 * (Impulse duration *Spark gap)}]
Table -2: Results showing the experimental and predicted value and error
SL.
NO.
Current
(amp.)
Impulse
Duration
(µs.)
Spark Gap
(mm.)
Exp. MRR Pred. MRR Error %Error
1 7 12 0.08 1.975 1.8393 0.1357 6.87
2 7 12 0.26 2.76 2.9945 0.1845 6.27
3 7 18 0.08 8.38 8.56626 0.18626 2.17
4 7 18 0.26 8.38 8.16162 0.21838 2.61
5 10 12 0.08 14.28 14.49414 0.21414 1.48
6 10 12 0.26 8.36 8.16948 0.195052 2.78
7 10 18 0.08 18.41 18.2151 0.1949 1.06
8 10 18 0.26 10.17 10.3806 0.2106 2.03](https://image.slidesharecdn.com/aa3312631267-130605010325-phpapp01/85/Experimental-Study-Using-Different-Tools-Electrodes-E-G-Copper-Graphite-on-M-R-R-of-E-D-M-Process-and-Selecting-The-Best-One-for-Maximum-M-R-R-in-Optimum-Condition-3-320.jpg)
![International Journal of Modern Engineering Research (IJMER)
www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645
www.ijmer.com 1267 | Page
12 13 14 15 16 17 18
0
2
4
6
8
10
12
14
16
18
20
M.R.R.
impulse duration (n-sec)
copper
graphite
Table-5: Impulse duration v/s MRR
Impulse duration (n-sec) MRR (copper) MRR (graphite)
12 1.9745 2.76
15 8.38 8.38
17 14.28 8.36
18 18.41 10.17
VI. Conclusion
1. From the analysis of graph- it can be identified that at the initial stage MRR using graphite electrode is more as compare
to copper electrode .Which implies that at low current, impulse duration and spark gap using graphite electrode is more
economical. But as the value of the parameters increases, MRR with copper electrode increases more rapidly in respect
of graphite electrode.
2. Finally, it can be concluded that graphite electrodes are best suitable for lower values of parameters and mainly for
finishing work as graphite electrode produces better surface finish due to lower MRR and copper electrodes are suitable
for high metal removal process where finish requirements are not significant.
References
Journal Paper:
[1]. Anand Pandey, Shankar Singh, Current research trends in variants of Electrical Discharge Machining: A review, International
Journal of Engineering Science and Technology, Vol. 2(6), 2010, 2172-2191.
[2]. Mr. V. D. Patel, Prof. C. P. Patel, Mr. U.J. Patel, Analysis of Different Tool Material On MRR and Surface Roughness of Mild
Steel In EDM, International Journal of Engineering Research and Applications (IJERA),Vol. 1, Issue 3, pp. 394-397.
[3]. J. Valentincic, D. Brissaud, M. Junkar, EDM process adaptation system in tool making industry ,Journal of Materials Processing
Technology, Journal of Materials Processing Technology ,172 (2006) 291–298.
[4]. Qing GAO, Qin-he ZHANG, Shu-peng SU, Jian-hua ZHANG, Parameter optimization model in electrical discharge machining
process,J Zhejiang Univ Sci A 2008 9(1):104-108.
Book:
[5]. P.K. Mishra, Nonconventional Machining, (Narosa Publishing House, 1997)](https://image.slidesharecdn.com/aa3312631267-130605010325-phpapp01/85/Experimental-Study-Using-Different-Tools-Electrodes-E-G-Copper-Graphite-on-M-R-R-of-E-D-M-Process-and-Selecting-The-Best-One-for-Maximum-M-R-R-in-Optimum-Condition-5-320.jpg)
Experimental Study Using Different Tools/Electrodes E.G. Copper, Graphite on M.R.R of E.D.M Process and Selecting The Best One for Maximum M.R.R in Optimum Condition
- 1. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645 www.ijmer.com 1263 | Page Santanu Dey, 1 Dr. D.C.Roy2 1 Masters of Technology, Department of Mechanical Engineering Jalpaiguri Government Engineering College, Jalpaiguri– 735102 2 H.O.D & Professor of Mechanical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri–735102, India Abstract: EDM is the thermal erosion process in which metal is removed by a series of recurring electrical discharges between a cutting tool acting as an electrode and a conductive work piece, in the presence of a dielectric fluid. Electrical discharge machining (EDM) is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. Its unique feature of using thermal energy to machine electrically conductive parts regardless of hardness has been its distinctive advantage in the manufacture of mould, die, automotive, aerospace and surgical components. Keywords: M.R.R, Current, Impulse Duration, Spark Gap, Regression Analysis. I. Introduction Electrical Discharge Machine (EDM) is now become the most important accepted technologies in manufacturing industries since many complex 3D shapes can be machined using a simple shaped tool electrode. Electrical discharge machine(EDM) is an important ‘non-traditional manufacturing method’, developed in the late1940s and has been accepted worldwide as a standard processing manufacture of forming tools to produce plastics moldings, die castings, forging dies and etc. New developments in the field of material science have led to new engineering metallic materials, composite materials, and high tech ceramics, having good mechanical properties and thermal characteristics as well as sufficient electrical conductivity so that they can readily be machined by spark erosion. At the present time, Electrical discharge machine (EDM) is a widespread technique used in industry for high precision machining of all types of conductive materials such as: metals, metallic alloys, graphite, or even some ceramic materials, of whatsoever hardness. Electrical discharge machine (EDM) technology is increasingly being used in tool, die and mould making industries, for machining of heat treated tool steels and advanced materials (super alloys, ceramics, and metal matrix composites) requiring high precision, complex shapes and high surface finish. Traditional machining technique is often based on the material removal using tool material harder than the work material and is unable to machine them economically. An electrical discharge machining (EDM) is based on the eroding effect of an electric spark on both the electrodes used. Electrical discharge machining (EDM) actually is a process of utilizing the removal phenomenon of electrical-discharge in dielectric. Therefore, the electrode plays an important role, which affects the material removal rate and the tool wear rate. There are two main types of EDM- • The ram type. • The wire-cut type. This project is based on the ram type EDM. Ram type E.D.M • The electrode/tool is attached to the ram that connected to the positive pole. • The work piece is connected to the negative pole. • The work is then positioned so that there is a gap between it and the electrode. • The gap is then flooded with the dielectric fluid. • The spark Temperatures generated can range from 7,760° to 11,650° Celsius. II. Objective Of The Project In this research work the main objective is to compare two electrodes e.g. (Copper & Graphite) using in EDM machining and selecting the best electrode on basis of highest Metal Removal Rate (MRR) and surface finish. Equipments used for EDM process: One mild steel metal piece (98.7*87.2*12). Copper & Graphite Electrode. Rustolic E.D.M. 20 Dielectric Fluid. EDM machine. Experimental Study Using Different Tools/Electrodes E.G. Copper, Graphite on M.R.R of E.D.M Process and Selecting The Best One for Maximum M.R.R in Optimum Condition
- 2. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645 www.ijmer.com 1264 | Page III. Observation Table Copper electrode Impulse Spark Gap I U T Time Idle M/C Total 1040 0.08 7 6 12 1.25 25.45 27.10 1050 0.14 8 6 15 1.14 6 7.14 1060 0.20 9 6 17 0.30 8.25 8.55 1070 0.26 10 6 18 0.36 6.40 7.26 Graphite electrode Impulse Spark Gap I U T Time Idle M/C Total 1040 0.08 7 6 12 1.40 18.24 20.04 1050 0.14 8 6 15 0.23 6 6.23 1060 0.20 9 6 17 0.48 14.10 14.58 1070 0.26 10 6 18 0.58 11.58 12.16 Sample Calculation:- M.R.R = depth of hole (h) = 1mm dia of the hole (d) = 8mm Volume of the hole = = * = 50.26 M.R.R = M/C Time=25.45min = 1.975 IV. Regression Analysis Based on the experimental data gathered, statistical regression analysis enabled to study the correlation of process parameters with the MRR. In this study, for three variables under consideration, a polynomial regression issued for modeling. The coefficients of regression model can be estimated from the experimental results. The effects of these variables and the interaction between them were included in this analyses and the developed model is expressed as interaction equation: Y=a+bX1+cX2 +……. + nXm (1) Where a, b, c. Etc are co-efficient of their corresponding parameter. The unknown coefficients are determined from the experimental data. Since, EDM process is non-linear in nature, a linear polynomial will be not able to predict the response accurately, and therefore the second-order model (quadratic model) is found to be adequately model the process.
- 3. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645 www.ijmer.com 1265 | Page Level of Observation:- Control parameters Level Observed value Min. level Max. level Current (Amp.) 7 10 M.R.R.(mm3/min) Impulse Duration (µs.) 12 18 M.R.R. (mm3/min) Spark Gap (mm.) 0.08 0.26 M.R.R.(mm3 /min) Table -1: Result of experimental value SL. NO. Current (Amp.) Impulse Duration (µs.) Spark Gap (mm.) A B C Material Removal Rate {M.R.R.} (mm3 /min) 1 7 12 0.08 -1 -1 -1 1.975 2 7 12 0.26 -1 -1 1 2.76 3 7 18 0.08 -1 1 -1 8.38 4 7 18 0.26 -1 1 1 8.38 5 10 12 0.08 1 -1 -1 14.28 6 10 12 0.26 1 -1 1 8.36 7 10 18 0.08 1 1 -1 18.41 8 10 18 0.26 1 1 1 10.17 Here current, Impulse Duration and Spark Gap denoted as A, B and C. Equation (1) can be rewritten as in (2) Y = Co + Ca*A + Cb*B + Cc*C + Cd*A*B + Ce*A*C + Cf*B*C (2) Normal equations are: ∑Y = nCo + Ca∑A + Cb∑B + Cc∑C + Cd∑ A*B + Ce*∑A*C+ Cf∑B*C (3) ∑Y*A = Co ∑A + Ca∑A2 + Cb∑A*B + Cc∑A*C + Cd∑A2 *B + Ce*∑A2 *C +Cf∑A*B*C (4) ∑Y*B = Co ∑B + Ca∑A*B + Cb∑B2 + Cc∑B*C + Cd∑A.B2 + Ce*∑A*B*C+ Cf∑B2 *C (5) ∑Y*C = Co ∑C + Ca∑A*C + Cb∑B*C + Cc∑C2 + Cd∑A.B.C + Ce*∑A*C2 + Cf∑B*C2 (6) ∑Y.A.B=Co∑A.B+Ca∑A2 B+ Cb ∑AB2 +Cc∑A.B.C+ Cd∑A 2. B2 + Ce*∑A2 *B*C + Cf ∑A.B2 .C (7) Y∑A*C = Co∑A*C +Ca∑A2 *C+ Cb∑A*B*C+ Cc∑A*C2 + Cd∑A2 .B*C+ Ce*∑A2 *C2 + Cf∑A*B*C2 (8) ∑Y*B*C =Co∑B*C +Ca∑A*B*C+ Cb∑B2 *C+ Cc∑B*C2 + Cd∑A.B2 *C+ Ce*∑A*B2 *C+ Cf∑B2 *C2 (9) Equation of the fitted model for MRR from solving above equations: MRR = – 64.7089 + [(7.323 * current) + (2.402 * Impulse duration) + (119.229 * Spark gap) – {0.167 *(current * Impulse duration)} – {13.759 *(Current * Spark gap)} – {1.398 * (Impulse duration *Spark gap)}] Table -2: Results showing the experimental and predicted value and error SL. NO. Current (amp.) Impulse Duration (µs.) Spark Gap (mm.) Exp. MRR Pred. MRR Error %Error 1 7 12 0.08 1.975 1.8393 0.1357 6.87 2 7 12 0.26 2.76 2.9945 0.1845 6.27 3 7 18 0.08 8.38 8.56626 0.18626 2.17 4 7 18 0.26 8.38 8.16162 0.21838 2.61 5 10 12 0.08 14.28 14.49414 0.21414 1.48 6 10 12 0.26 8.36 8.16948 0.195052 2.78 7 10 18 0.08 18.41 18.2151 0.1949 1.06 8 10 18 0.26 10.17 10.3806 0.2106 2.03
- 4. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645 www.ijmer.com 1266 | Page V. Graph & Table 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 0.22 0.24 0.26 0.28 0 2 4 6 8 10 12 14 16 18 20 M.R.R.(mm3/min) spark gap (mm) copper graphite Table- 3: Spark gap v/s MRR Spark gap (mm) MRR (copper) MRR (graphite) 0.08 1.9745 2.76 0.14 8.38 8.38 0.2 14.28 8.36 0.26 18.41 10.17 7.0 7.5 8.0 8.5 9.0 9.5 10.0 0 2 4 6 8 10 12 14 16 18 20 M.R.R. current (amps) copper graphite Table – 4: Current v/s MRR Current (amps) MRR (copper) MRR (graphite) 7 1.9745 2.76 8 8.38 8.38 9 14.28 8.36 10 18.41 10.17
- 5. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol.3, Issue.3, May-June. 2013 pp-1263-1267 ISSN: 2249-6645 www.ijmer.com 1267 | Page 12 13 14 15 16 17 18 0 2 4 6 8 10 12 14 16 18 20 M.R.R. impulse duration (n-sec) copper graphite Table-5: Impulse duration v/s MRR Impulse duration (n-sec) MRR (copper) MRR (graphite) 12 1.9745 2.76 15 8.38 8.38 17 14.28 8.36 18 18.41 10.17 VI. Conclusion 1. From the analysis of graph- it can be identified that at the initial stage MRR using graphite electrode is more as compare to copper electrode .Which implies that at low current, impulse duration and spark gap using graphite electrode is more economical. But as the value of the parameters increases, MRR with copper electrode increases more rapidly in respect of graphite electrode. 2. Finally, it can be concluded that graphite electrodes are best suitable for lower values of parameters and mainly for finishing work as graphite electrode produces better surface finish due to lower MRR and copper electrodes are suitable for high metal removal process where finish requirements are not significant. References Journal Paper: [1]. Anand Pandey, Shankar Singh, Current research trends in variants of Electrical Discharge Machining: A review, International Journal of Engineering Science and Technology, Vol. 2(6), 2010, 2172-2191. [2]. Mr. V. D. Patel, Prof. C. P. Patel, Mr. U.J. Patel, Analysis of Different Tool Material On MRR and Surface Roughness of Mild Steel In EDM, International Journal of Engineering Research and Applications (IJERA),Vol. 1, Issue 3, pp. 394-397. [3]. J. Valentincic, D. Brissaud, M. Junkar, EDM process adaptation system in tool making industry ,Journal of Materials Processing Technology, Journal of Materials Processing Technology ,172 (2006) 291–298. [4]. Qing GAO, Qin-he ZHANG, Shu-peng SU, Jian-hua ZHANG, Parameter optimization model in electrical discharge machining process,J Zhejiang Univ Sci A 2008 9(1):104-108. Book: [5]. P.K. Mishra, Nonconventional Machining, (Narosa Publishing House, 1997)