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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

AND TECHNOLOGY (IJMET)

ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 5, Issue 2, February (2014), pp. 44-51
© IAEME: www.iaeme.com/ijmet.asp
Journal Impact Factor (2014): 3.8231 (Calculated by GISI)
www.jifactor.com

IJMET
©IAEME

MULTI OBJECTIVE OPTIMIZATION OF NEAR-DRY EDM PROCESS
USING RESPONSE SURFACE METHODOLOGY
1

Dr. P. A. Deshmukh,

2

Mr. P. R. Cheke,

3

Mr. R. D. Shelke

ABSTRACT
The correct selection of manufacturing technique is one of the most important aspects to take
into consideration in the majority of manufacturing processes and particularly in processes related to
Electrical Discharge Machining (EDM). It is capable of machining geometrically complex or hard
material components, which are precise and difficult-to-machine such as heat treated tool steels,
composites, super alloys, ceramics, carbides, heat resistant steels etc. being widely used in die and
mold making industries, aerospace, aeronautics and nuclear industries.
This paper investigates near-dry electrical discharge machining to achieve the high material
removal rate and better surface finish simultaneously. In near-dry EDM liquid and air mixture is used
as dielectric medium and in wet EDM only liquid is used as dielectric. Input EDM parameters
considered are discharge current, pulse on time, gap voltage and pulse off time on responses like
material removal rate(MRR) and surface roughness in near-dry EDM. A well-designed experimental
scheme was used to reduce the total number of experiments. Design of experiment were conducted
with the L9 orthogonal array based on the Taguchi method. Multi-objective optimization is carried
out with the help of Response Surface Methodology (RSM) to optimize both the responses at same
time. It was experimentally found that, near-dry EDM exhibits the advantage of good machining
stability at low discharge energy thus results in better surface finish.
Keywords: Near-Dry EDM, Wet EDM and MRR.
1. INTRODUCTION
Electric Discharge Machining (EDM) is a thermo–electric process in which material removal
takes place through the process of controlled spark generation. It is one of the most popular nontraditional machining processes being used today. EDM has achieved a status of being nearly
indispensable in the industry because of its ability to machine any electrically conductive material
irrespective of its mechanical strength. Despite its advantages, environmental concerns associated
44
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

with the process have been a major drawback of EDM. Hydrocarbon oil based dielectric fluids used
in EDM are the primary source of pollution from the process. Replacing liquid dielectric by mixture
of gas and liquid is an emerging field in the environment-friendly EDM technology. Near dry EDM
is a modification of the conventional EDM process in which the liquid dielectric is replaced by a
mixture of gas and liquid medium. The flow of high velocity gas into the gap facilitates removal of
debris and prevents excessive heating of the tool and work-piece at the discharge spots. Several
experimental studies made in this field have brought out some of the essential features of the process.
In this study, near-dry EDM milling is investigated to understand the effect of discharge current,
pulse on time, pulse off time and discharge voltage on responses like MRR and Surface roughness.
2. LITERATURE REVIEW
Shih et al [2] investigated the dry and near-dry EDM milling to achieve the high MRR and
fine surface finish for roughing and finishing operations, respectively. Oxygen gas and copper
electrode was used in dry EDM, whereas nitrogen and de-ionized water mixture was used in near-dry
EDM operation. A 25-1fractional factorial design is applied to investigate the effect of discharge
current, pulse duration, pulse interval and gap voltage on the MRR and surface finish in both
process. The experiments were conducted on a CNC die-sinking EDM machine using AISI H13 tool
steel as the work material. A rotary spindle, Rotobore RBS-1000, with through-spindle flushing
capability is mounted on the EDM head. The input liquid flow is set at 5 ml/min. Negative polarity,
i.e. electrode as cathode, is used in the experiment, due lower wear on cathode at low discharge pulse
duration and smoother discharge crater on anode.
It was found that, high MRR were achieved in dry EDM where as fine surface finish were
obtained in near-dry EDM. Oxygen is to promote the MRR in dry and near-dry EDM due to
exothermal oxidation. Near-dry was proven beneficial for the finishing operation. Because liquid
phase is dispersed in gas medium is hypothesized to enhance the electrical field thus result is large
discharge gap and stable discharge at low energy input.
Pradhan et al [6] investigate three process parameters like discharge current, pulse duration
and pulse off time. Response surface methodology was used to investigate the relationship and
parametric interaction of variable and significant coefficient were obtained at 5% level by ANOVA.
Experiment were conducted on Electronica Electroplus PS 50ZNC Die Shrinking Machine. Copper
electrode of 30 mm diameter and 15x 15 mm2 AISI-D2 tool steel with 4 mm thickness work-piece
was used.
It was found that, model for MRR were developed for three parameters namely, pulse
current, discharge time and pulse off time for EDM process using RSM. It was also found that all
three machining parameters and their interactions have significant effect on MRR
Tomadi et al [7] was investigate the influence of themachining parameters such as peak
current, power supply voltage, pulse on time and pulse off time on out put responses Surface quality,
Electrode wear and material removal rate.
Result are analyzed by using STATISTICA software. Design of experiments (DOE) technique and
ANOVA analysis were used for experimental work. Tungsten Carbide has been selected as the workpiece and copper tungsten as a electrode material.
It was found that, for surface roughness, the most influential factors were voltage followed by
the pulse off time, while the peak current and pulse on time was not significant at the considered
confidence level. For material removal rate, pulse on time factor was most influential followed by
voltage, peak current, and pulse off time. For electrode wear, it was observed that the most
influential factor were pulse off time, followed by the peak current factor.

45
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

Iqbal et al [9] investigate machining parameter like voltage, rotational speed of electrode and
feed rate over a responses MRR, EWR and surface roughness on AISI 304 stainless steel as
workpiece material and copper was used as a electrode material. RSM was used for interactions
between the three controllable variables on MRR, EWR and Ra. Significant coefficients were
obtained by performing ANOVA at 95% significance level. It was found that voltage and rpm have
effect on MRR, EWR and surface roughness.
3. PLANNING OF EXPERIMENT
Oil hardened non shrinking steel material having size 5 x 50 x 50 mm with hollow copper
alloy electrode with10 mm diameter were used. Separate work piece used for each experiment. PS
50ZNC (die-sinking type) of EDM machine used for experimentations. Commercial grade EDM oil
(specific gravity= 0.763, freezing point= 94˚C) and air through a hallow tube used as dielectric fluid
with a pressure of 0.1 kgf/cm2 and 0.5 kgf/cm2 respectively. Circular shaped hollow copper tool with
internal flushing of air used to flush away the eroded materials from the sparking zone. In this
process, machining time and duty cycle is kept constant 7 min and 0.75. Four factors tackled with a
total number of 9 experiments were performed. The surface roughness measurement using contact
type C3A MahrPerthenPerthometer (stylus radius of 5 µm ) were done. The design scheme and
machining parameters and their levels are shown in Table1. Design matrix and results for MRR and
surface roughness as shown in table 2. Machine setup for near-dry EDM as shown in Figure1.

Figure1:-Near Dry EDM Setup

Table 1 Design Scheme of machining parameters and their levels
Levels
Parameters
Unit
Level-I
Level-II Level-III
2
3
4
Discharge current ( Ip )
amp
50
100
150
Pulse on time ( Ton )
µs
Pulse off time ( Toff )
Gap voltage ( Vg )

position
volt

46

10
40

11
45

12
50
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

Table2. Experimental design matrix & results
Exp. No.

Ip

Ton

Toff

Vg

MRR ( g/ min )

Ra ( µm )

1
2
3
4
5
6
7
8
9

1
1
1
2
2
2
3
3
3

1
2
3
1
2
3
1
2
3

1
2
3
2
3
1
3
1
2

1
2
3
3
1
2
2
3
1

0.0160
0.0180
0.0190
0.0220
0.0240
0.0260
0.0300
0.0480
0.0280

2.68
1.87
2.74
1.94
2.51
4.32
3.44
3.12
3.59

4. RESULT & DISCUSSION
4.1) Results for material removal rate
The coefficients of model for MRR are shown in Table 3. The parameter R2 describes the
amount of variation observed in MRR is explained by the input factors. R2 = 87.92 % indicate that
the model is able to predict the response with high accuracy.

Terms
Term
Constant

Table 3. Estimated Regression Coefficients for MRR
Coef
SE Coef
T

P

0.025667

0.002222

11.549

0.007

Ip

0.006733

0.003443

1.956

0.190

Ton

0.000833

0.002722

0.306

0.788

Toff

-0.004333

0.004304

-1.007

0.420

Vg

0.002000

0.004304

0.465

0.688

Ip*Ton

-0.003000

0.006667

-0.450

0.697

Toff*Vg

-0.004200

0.004217

-0.996

0.424

S = 0.0666708

R-Sq = 87.92%

R-Sq(adj) = 84.86%

Adjusted R2 is a modified R2 that has been adjusted for the number of terms in the model. If
unnecessary terms are included in the model, R2 can be artificially high, but adjusted R2 (84.86 %.)
may get smaller.
The standard deviation of errors in the modeling, S= 0.0666708.Comparing the p-value to a
commonly used α-level = 0.05. ANOVA for MRR in near-dry EDM for factors is shown in Table 4.
which clearly indicates that the Ip has greatest influence on surface roughness(SR), followed by Toff,
Vg and Ton . The p-values for Ip, Ton, Toff and Vg are 0.043, 0.58, 0.320 and 0.488 respectively,
depicted in Table 4.

47
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

Table4.Analysis of Variance for MRR
Seq SS
Adj SS
Adj MS

Source

DF

F

P

Regression

6

0.000647

0.000647

0.000108

2.43

0.320

Linear

4

0.000594

0.000299

0.000075

1.68

0.406

Ip

1

0.000468

0.000170

0.000170

3.82

0.043

Ton

1

0.000004

0.000004

0.000004

0.09

0.580

Toff

1

0.000048

0.000045

0.000045

1.01

0.320

Vg

1

0.000073

0.000010

0.000010

0.22

0.488

Interaction

2

0.000053

0.000053

0.000027

0.60

0.626

Ip*Ton

1

0.000009

0.000009

0.000009

0.20

0.697

Toff*Vg

1

0.000044

0.000044

0.000044

0.99

0.424

Error

2

0.000089

0.000089

0.000044

Total

8

0.000736

4.2) Results for surface roughness
The coefficients of model for surface roughness are shown in Table 5. The parameter R2
describes the amount of variation observed in surface roughness is explained by the input factors. R2
= 95.85 % indicate that the model is able to predict the response with high accuracy. Adjusted R2 is a
modified R2 that has been adjusted for the number of terms in the model. If unnecessary terms are
included in the model, R2 can be artificially high, but adjusted R2 (82.62 %.) may get smaller. The
standard deviation of errors in the modeling, S= 0.330911.
Table 5. Estimated Regression Coefficients for Ra in near-dry EDM finishing
Terms
Coef
SE Coef
T
P
Term
Constant
2.9122
0.1103
26.402
0.001
Ip

0.7207

0.1709

4.217

0.052

Ton

0.4317

0.1351

3.195

0.086

Toff

-0.7958

0.2136

-3.726

0.065

Vg

-0.7208

0.2136

-3.375

0.078

Ip*Ton

-1.1150

0.3309

-3.369

0.078

Toff*Vg

0.4880

0.2093

2.332

0.145

S = 0.330911

R-Sq = 95.65%

R-Sq(adj) = 82.62%

Comparing the p-value to a commonly used α-level = 0.05. ANOVA for surface roughness for
factors is shown in Table 6.which clearly indicates that the Ip has greatest influence on surface
roughness, followed by Vg, Ton and Toff. The p-values for Ip, Ton, Toff and Vg are 0.042, 0.059,
0.065 and 0.057 respectively, depicted in Table 6.
48
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

Source

Table6.Analysis of Variance for Ra in near-dry EDM
DF
Seq SS
Adj SS
Adj MS
F

P

Regression

6

4.82075

4.82075

0.80346

7.34

0.125

Linear

4

2.98217

4.80770

1.20193

10.98

0.085

Ip

1

1.36327

1.94760

1.94760

17.79

0.042

Ton

1

1.11802

1.11802

1.11802

10.21

0.059

Toff

1

0.34082

1.52004

1.52004

13.88

0.065

Vg

1

0.16007

1.24704 1

1.24704 1

11.39

0.057

Interaction

2

1.83859

1.83859

0.91929

8.40

0.106

Ip*Ton

1

1.24323

1.24323

1.24323

11.35

0.078

Toff*Vg

1

0.59536

0.59536

0.59536

5.44

0.145

Error

2

0.21900

0.21900

0.10950

Total

8

5.03976

Response Optimization
Goal

Lower

Target

Upper

Weight

Import

MRR

Maximum

0.016

0.048

0.048

1

1

Ra (µm)

Minimum

1.830

1.830

4.320

1

1

Global Solution

Starting Point
Ip

2

Ip

2.86869

Ton

50

Ton

50

Toff

10

Toff

10

Vg

40

Vg

50

Predicted Responses
MRR

0.03409

Desirability
Upper
1.000000

Ra (µm)

1.82651

0.565267

Composite Desirability

49

0.751843
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME
Optimal
High
D
Cur
0.75184 Low

Ip
4.0
[2.8687]
2.0

Ton
150.0
[50.0]
50.0

Toff
12.0
[10.0]
10.0

Vg
50.0
[50.0]
40.0

Composite
Desirability
0.75184

Ra ( m)
Minimum
y = 1.8265
d = 1.0000

MRR(g/mi
Maximum
y = 0.0341
d = 0.56527

Figure 2. Optimization graph

CONCLUSION
Analysis carried out by using response surface methodology’s (D-Optimal Method) to
optimize two responses simultaneously (to maximize MRR and minimize surface roughness). It is
also observed that, to obtain maximum MRR (0.0341) and minimum surface roughness (1.8265)
simultaneously when employ the discharge current (2.868) and low pulse on time(50), pulse off time
(10) and high discharge voltage (50).
Near-dry EDM proven beneficial for finishing operation because liquid phase is dispersed in
gas medium is hypothesized to enhance the electric field and thus results in a low frequency of spark
and stable discharge at low energy input. The gases in the air prevent the electrolysis and yield better
surface finish.
FUTURE SCOPE
1) Very less work has been reported on MRR improvement. Also on material like water hardened
die steel, molybdenum high speed steel have non tried as a work materials in near-dry EDM
and powder mixed EDM. The same may be tried in future works
2) Hollow tube and eccentric drilled hole type electrode are reported to have positive impact on
MRR due to improved flushing condition. Such designs need investigations for more work
materials to evaluate their case to case effects.
3) Use of near-dry EDM in micro machining.

50
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME

REFERENCES
[1]

[2]

[3]
[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

12]

[13]

[14]

[15]

[16]

Jia Tao, Albert J. Shih, and Jun Ni, “Near-dry EDM Mirror-Like Surface Finish” Jan.(2008)
International Journal of Electrical Machining , Department of Mechanical Engineering,
University of Michigan.
Jia Tao, Albert J. Shih, and Jun Ni, “Experimental Study of the Dry and Near-Dry Electrical
Discharge Milling Processes” Journal of Manufacturing Science and Engineering. (2008) 130,
011002, DOI:10.1115/1.2784276.
GrzegorzSkrabalak, Jerzy Kozak, “Study on Dry Electrical Discharge Machining” Proceedings
of the World Congress on Engineering , June 2010 Volume-III.
Yusuf Keskin, H. SelcukHalkaci, Mevlut Kizil, “An experimental study for determination of the
effects of machining parameters on surface roughness in EDM” International Journal of Advance
Manufacturing Technology.(2006)28:1118-1121, DOI 10.1007/s00170-004-2478-8.
Ko-Ta Chiang,“Modeling and analysis of the effects of machining parameters on the performance
characteristics in the EDM process of Al2O3+TiC mixed ceramic” International Journal Advance
Manufacturing Technology.(2008)37:523-533,DOI 10.1007/s00170-004-1002-3.
Mohan Kumar Pradhan, Chandan Kumar Biswas, “Modeling of machining parameters of MRR
in the EDM in EDM using response surface methodology” National conference on mechanical
science and technology. November 13-14 (2008).
S. H. Tomadi, M. A. Hassan, Z. Hamedon “Analysis of the Influence of EDM Parameters on
Surface Quality, Material removal rate & Electrode Wear of Tungsten Carbide” International
Multi Conference of Engineers & Computer Scientists, March 18-20 2009 Volume-II.
K. Ponappa , S. Aravindan, P. V. Rao, & M. Gupta “The effect of process parameters on
machining of magnesium nano alumina composites through EDM” 02 July 2009, International
Journal of Advance Manufacturing Technology. DOI 10.1007/s00170-009-2158-9.
AkmAsifIqbal & Ahsan Ali Khan, “Modeling & analysis of MRR, EWR and Surface roughness in
EDM Milling through response surface methodology” Journal of Engineering & Applied
science.Vol-5(2010). DOI: 10.3923, pp154-162.
AnandPandey, Shankar Singh “Current research trends in variants of Electrical Discharge
Machining: A review” Journal of Engineering Science and Technology, Vol-2(6), 2010, pp21722191.
S. S. Mahapatra& Amar Patnaik “Optimization of wire electric discharge machining process
parameters using Taguchi method” (2008), International Journal Advance Manufacturing
Technology.
KuldipOjha and R. K. Garg, 2010 “MRR Improvement in sinking electrical discharge
machining: A Review” Journal of Materials & Materials Characterization & Engineering.
Volume -9, No.8, pp709-739.
A. Manna & B. Bhattacharyya “Taguchi &Gauss elimination method: A dual response approach
for parametric optimization of CNC wire cut EDM” 2006, International Journal of Advance
Manufacturing and Technology.
Vishal Kesarwani “Thesis on investigation of electrical discharge machine for optimization of
surface roughness using response surface methodology approach” Department of Mechanical
Engineering, National Institute of Technology, Rourkela, Orisa.
Prof. P. R. Cheke, Prof. D. S. Khedekar, Prof. R. S. Pawar and Dr. M. S. Kadam, “Comparative
Performance of Wet and Near-Dry EDM Process for Machining of Oil Hardned Non Sinking
Steel Material”, International Journal of Mechanical Engineering & Technology (IJMET),
Volume 3, Issue 2, 2012, pp. 13 - 22, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.
Prakash R. Cheke, Prof. D. S. Khedekar, “Experimental Investigation of Machining Parameter
for Wet & Near-Dry EDM Finishing”, International Journal of Design and Manufacturing
Technology (IJDMT), Volume 2, Issue 1, 2011, pp. 28 - 33, ISSN Print: 0976 – 6995,
ISSN Online: 0976 – 7002.
51

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  • 1. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME AND TECHNOLOGY (IJMET) ISSN 0976 – 6340 (Print) ISSN 0976 – 6359 (Online) Volume 5, Issue 2, February (2014), pp. 44-51 © IAEME: www.iaeme.com/ijmet.asp Journal Impact Factor (2014): 3.8231 (Calculated by GISI) www.jifactor.com IJMET ©IAEME MULTI OBJECTIVE OPTIMIZATION OF NEAR-DRY EDM PROCESS USING RESPONSE SURFACE METHODOLOGY 1 Dr. P. A. Deshmukh, 2 Mr. P. R. Cheke, 3 Mr. R. D. Shelke ABSTRACT The correct selection of manufacturing technique is one of the most important aspects to take into consideration in the majority of manufacturing processes and particularly in processes related to Electrical Discharge Machining (EDM). It is capable of machining geometrically complex or hard material components, which are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. being widely used in die and mold making industries, aerospace, aeronautics and nuclear industries. This paper investigates near-dry electrical discharge machining to achieve the high material removal rate and better surface finish simultaneously. In near-dry EDM liquid and air mixture is used as dielectric medium and in wet EDM only liquid is used as dielectric. Input EDM parameters considered are discharge current, pulse on time, gap voltage and pulse off time on responses like material removal rate(MRR) and surface roughness in near-dry EDM. A well-designed experimental scheme was used to reduce the total number of experiments. Design of experiment were conducted with the L9 orthogonal array based on the Taguchi method. Multi-objective optimization is carried out with the help of Response Surface Methodology (RSM) to optimize both the responses at same time. It was experimentally found that, near-dry EDM exhibits the advantage of good machining stability at low discharge energy thus results in better surface finish. Keywords: Near-Dry EDM, Wet EDM and MRR. 1. INTRODUCTION Electric Discharge Machining (EDM) is a thermo–electric process in which material removal takes place through the process of controlled spark generation. It is one of the most popular nontraditional machining processes being used today. EDM has achieved a status of being nearly indispensable in the industry because of its ability to machine any electrically conductive material irrespective of its mechanical strength. Despite its advantages, environmental concerns associated 44
  • 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME with the process have been a major drawback of EDM. Hydrocarbon oil based dielectric fluids used in EDM are the primary source of pollution from the process. Replacing liquid dielectric by mixture of gas and liquid is an emerging field in the environment-friendly EDM technology. Near dry EDM is a modification of the conventional EDM process in which the liquid dielectric is replaced by a mixture of gas and liquid medium. The flow of high velocity gas into the gap facilitates removal of debris and prevents excessive heating of the tool and work-piece at the discharge spots. Several experimental studies made in this field have brought out some of the essential features of the process. In this study, near-dry EDM milling is investigated to understand the effect of discharge current, pulse on time, pulse off time and discharge voltage on responses like MRR and Surface roughness. 2. LITERATURE REVIEW Shih et al [2] investigated the dry and near-dry EDM milling to achieve the high MRR and fine surface finish for roughing and finishing operations, respectively. Oxygen gas and copper electrode was used in dry EDM, whereas nitrogen and de-ionized water mixture was used in near-dry EDM operation. A 25-1fractional factorial design is applied to investigate the effect of discharge current, pulse duration, pulse interval and gap voltage on the MRR and surface finish in both process. The experiments were conducted on a CNC die-sinking EDM machine using AISI H13 tool steel as the work material. A rotary spindle, Rotobore RBS-1000, with through-spindle flushing capability is mounted on the EDM head. The input liquid flow is set at 5 ml/min. Negative polarity, i.e. electrode as cathode, is used in the experiment, due lower wear on cathode at low discharge pulse duration and smoother discharge crater on anode. It was found that, high MRR were achieved in dry EDM where as fine surface finish were obtained in near-dry EDM. Oxygen is to promote the MRR in dry and near-dry EDM due to exothermal oxidation. Near-dry was proven beneficial for the finishing operation. Because liquid phase is dispersed in gas medium is hypothesized to enhance the electrical field thus result is large discharge gap and stable discharge at low energy input. Pradhan et al [6] investigate three process parameters like discharge current, pulse duration and pulse off time. Response surface methodology was used to investigate the relationship and parametric interaction of variable and significant coefficient were obtained at 5% level by ANOVA. Experiment were conducted on Electronica Electroplus PS 50ZNC Die Shrinking Machine. Copper electrode of 30 mm diameter and 15x 15 mm2 AISI-D2 tool steel with 4 mm thickness work-piece was used. It was found that, model for MRR were developed for three parameters namely, pulse current, discharge time and pulse off time for EDM process using RSM. It was also found that all three machining parameters and their interactions have significant effect on MRR Tomadi et al [7] was investigate the influence of themachining parameters such as peak current, power supply voltage, pulse on time and pulse off time on out put responses Surface quality, Electrode wear and material removal rate. Result are analyzed by using STATISTICA software. Design of experiments (DOE) technique and ANOVA analysis were used for experimental work. Tungsten Carbide has been selected as the workpiece and copper tungsten as a electrode material. It was found that, for surface roughness, the most influential factors were voltage followed by the pulse off time, while the peak current and pulse on time was not significant at the considered confidence level. For material removal rate, pulse on time factor was most influential followed by voltage, peak current, and pulse off time. For electrode wear, it was observed that the most influential factor were pulse off time, followed by the peak current factor. 45
  • 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME Iqbal et al [9] investigate machining parameter like voltage, rotational speed of electrode and feed rate over a responses MRR, EWR and surface roughness on AISI 304 stainless steel as workpiece material and copper was used as a electrode material. RSM was used for interactions between the three controllable variables on MRR, EWR and Ra. Significant coefficients were obtained by performing ANOVA at 95% significance level. It was found that voltage and rpm have effect on MRR, EWR and surface roughness. 3. PLANNING OF EXPERIMENT Oil hardened non shrinking steel material having size 5 x 50 x 50 mm with hollow copper alloy electrode with10 mm diameter were used. Separate work piece used for each experiment. PS 50ZNC (die-sinking type) of EDM machine used for experimentations. Commercial grade EDM oil (specific gravity= 0.763, freezing point= 94˚C) and air through a hallow tube used as dielectric fluid with a pressure of 0.1 kgf/cm2 and 0.5 kgf/cm2 respectively. Circular shaped hollow copper tool with internal flushing of air used to flush away the eroded materials from the sparking zone. In this process, machining time and duty cycle is kept constant 7 min and 0.75. Four factors tackled with a total number of 9 experiments were performed. The surface roughness measurement using contact type C3A MahrPerthenPerthometer (stylus radius of 5 µm ) were done. The design scheme and machining parameters and their levels are shown in Table1. Design matrix and results for MRR and surface roughness as shown in table 2. Machine setup for near-dry EDM as shown in Figure1. Figure1:-Near Dry EDM Setup Table 1 Design Scheme of machining parameters and their levels Levels Parameters Unit Level-I Level-II Level-III 2 3 4 Discharge current ( Ip ) amp 50 100 150 Pulse on time ( Ton ) µs Pulse off time ( Toff ) Gap voltage ( Vg ) position volt 46 10 40 11 45 12 50
  • 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME Table2. Experimental design matrix & results Exp. No. Ip Ton Toff Vg MRR ( g/ min ) Ra ( µm ) 1 2 3 4 5 6 7 8 9 1 1 1 2 2 2 3 3 3 1 2 3 1 2 3 1 2 3 1 2 3 2 3 1 3 1 2 1 2 3 3 1 2 2 3 1 0.0160 0.0180 0.0190 0.0220 0.0240 0.0260 0.0300 0.0480 0.0280 2.68 1.87 2.74 1.94 2.51 4.32 3.44 3.12 3.59 4. RESULT & DISCUSSION 4.1) Results for material removal rate The coefficients of model for MRR are shown in Table 3. The parameter R2 describes the amount of variation observed in MRR is explained by the input factors. R2 = 87.92 % indicate that the model is able to predict the response with high accuracy. Terms Term Constant Table 3. Estimated Regression Coefficients for MRR Coef SE Coef T P 0.025667 0.002222 11.549 0.007 Ip 0.006733 0.003443 1.956 0.190 Ton 0.000833 0.002722 0.306 0.788 Toff -0.004333 0.004304 -1.007 0.420 Vg 0.002000 0.004304 0.465 0.688 Ip*Ton -0.003000 0.006667 -0.450 0.697 Toff*Vg -0.004200 0.004217 -0.996 0.424 S = 0.0666708 R-Sq = 87.92% R-Sq(adj) = 84.86% Adjusted R2 is a modified R2 that has been adjusted for the number of terms in the model. If unnecessary terms are included in the model, R2 can be artificially high, but adjusted R2 (84.86 %.) may get smaller. The standard deviation of errors in the modeling, S= 0.0666708.Comparing the p-value to a commonly used α-level = 0.05. ANOVA for MRR in near-dry EDM for factors is shown in Table 4. which clearly indicates that the Ip has greatest influence on surface roughness(SR), followed by Toff, Vg and Ton . The p-values for Ip, Ton, Toff and Vg are 0.043, 0.58, 0.320 and 0.488 respectively, depicted in Table 4. 47
  • 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME Table4.Analysis of Variance for MRR Seq SS Adj SS Adj MS Source DF F P Regression 6 0.000647 0.000647 0.000108 2.43 0.320 Linear 4 0.000594 0.000299 0.000075 1.68 0.406 Ip 1 0.000468 0.000170 0.000170 3.82 0.043 Ton 1 0.000004 0.000004 0.000004 0.09 0.580 Toff 1 0.000048 0.000045 0.000045 1.01 0.320 Vg 1 0.000073 0.000010 0.000010 0.22 0.488 Interaction 2 0.000053 0.000053 0.000027 0.60 0.626 Ip*Ton 1 0.000009 0.000009 0.000009 0.20 0.697 Toff*Vg 1 0.000044 0.000044 0.000044 0.99 0.424 Error 2 0.000089 0.000089 0.000044 Total 8 0.000736 4.2) Results for surface roughness The coefficients of model for surface roughness are shown in Table 5. The parameter R2 describes the amount of variation observed in surface roughness is explained by the input factors. R2 = 95.85 % indicate that the model is able to predict the response with high accuracy. Adjusted R2 is a modified R2 that has been adjusted for the number of terms in the model. If unnecessary terms are included in the model, R2 can be artificially high, but adjusted R2 (82.62 %.) may get smaller. The standard deviation of errors in the modeling, S= 0.330911. Table 5. Estimated Regression Coefficients for Ra in near-dry EDM finishing Terms Coef SE Coef T P Term Constant 2.9122 0.1103 26.402 0.001 Ip 0.7207 0.1709 4.217 0.052 Ton 0.4317 0.1351 3.195 0.086 Toff -0.7958 0.2136 -3.726 0.065 Vg -0.7208 0.2136 -3.375 0.078 Ip*Ton -1.1150 0.3309 -3.369 0.078 Toff*Vg 0.4880 0.2093 2.332 0.145 S = 0.330911 R-Sq = 95.65% R-Sq(adj) = 82.62% Comparing the p-value to a commonly used α-level = 0.05. ANOVA for surface roughness for factors is shown in Table 6.which clearly indicates that the Ip has greatest influence on surface roughness, followed by Vg, Ton and Toff. The p-values for Ip, Ton, Toff and Vg are 0.042, 0.059, 0.065 and 0.057 respectively, depicted in Table 6. 48
  • 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME Source Table6.Analysis of Variance for Ra in near-dry EDM DF Seq SS Adj SS Adj MS F P Regression 6 4.82075 4.82075 0.80346 7.34 0.125 Linear 4 2.98217 4.80770 1.20193 10.98 0.085 Ip 1 1.36327 1.94760 1.94760 17.79 0.042 Ton 1 1.11802 1.11802 1.11802 10.21 0.059 Toff 1 0.34082 1.52004 1.52004 13.88 0.065 Vg 1 0.16007 1.24704 1 1.24704 1 11.39 0.057 Interaction 2 1.83859 1.83859 0.91929 8.40 0.106 Ip*Ton 1 1.24323 1.24323 1.24323 11.35 0.078 Toff*Vg 1 0.59536 0.59536 0.59536 5.44 0.145 Error 2 0.21900 0.21900 0.10950 Total 8 5.03976 Response Optimization Goal Lower Target Upper Weight Import MRR Maximum 0.016 0.048 0.048 1 1 Ra (µm) Minimum 1.830 1.830 4.320 1 1 Global Solution Starting Point Ip 2 Ip 2.86869 Ton 50 Ton 50 Toff 10 Toff 10 Vg 40 Vg 50 Predicted Responses MRR 0.03409 Desirability Upper 1.000000 Ra (µm) 1.82651 0.565267 Composite Desirability 49 0.751843
  • 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME Optimal High D Cur 0.75184 Low Ip 4.0 [2.8687] 2.0 Ton 150.0 [50.0] 50.0 Toff 12.0 [10.0] 10.0 Vg 50.0 [50.0] 40.0 Composite Desirability 0.75184 Ra ( m) Minimum y = 1.8265 d = 1.0000 MRR(g/mi Maximum y = 0.0341 d = 0.56527 Figure 2. Optimization graph CONCLUSION Analysis carried out by using response surface methodology’s (D-Optimal Method) to optimize two responses simultaneously (to maximize MRR and minimize surface roughness). It is also observed that, to obtain maximum MRR (0.0341) and minimum surface roughness (1.8265) simultaneously when employ the discharge current (2.868) and low pulse on time(50), pulse off time (10) and high discharge voltage (50). Near-dry EDM proven beneficial for finishing operation because liquid phase is dispersed in gas medium is hypothesized to enhance the electric field and thus results in a low frequency of spark and stable discharge at low energy input. The gases in the air prevent the electrolysis and yield better surface finish. FUTURE SCOPE 1) Very less work has been reported on MRR improvement. Also on material like water hardened die steel, molybdenum high speed steel have non tried as a work materials in near-dry EDM and powder mixed EDM. The same may be tried in future works 2) Hollow tube and eccentric drilled hole type electrode are reported to have positive impact on MRR due to improved flushing condition. Such designs need investigations for more work materials to evaluate their case to case effects. 3) Use of near-dry EDM in micro machining. 50
  • 8. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 44-51, © IAEME REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] 12] [13] [14] [15] [16] Jia Tao, Albert J. Shih, and Jun Ni, “Near-dry EDM Mirror-Like Surface Finish” Jan.(2008) International Journal of Electrical Machining , Department of Mechanical Engineering, University of Michigan. Jia Tao, Albert J. Shih, and Jun Ni, “Experimental Study of the Dry and Near-Dry Electrical Discharge Milling Processes” Journal of Manufacturing Science and Engineering. (2008) 130, 011002, DOI:10.1115/1.2784276. GrzegorzSkrabalak, Jerzy Kozak, “Study on Dry Electrical Discharge Machining” Proceedings of the World Congress on Engineering , June 2010 Volume-III. Yusuf Keskin, H. SelcukHalkaci, Mevlut Kizil, “An experimental study for determination of the effects of machining parameters on surface roughness in EDM” International Journal of Advance Manufacturing Technology.(2006)28:1118-1121, DOI 10.1007/s00170-004-2478-8. Ko-Ta Chiang,“Modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al2O3+TiC mixed ceramic” International Journal Advance Manufacturing Technology.(2008)37:523-533,DOI 10.1007/s00170-004-1002-3. Mohan Kumar Pradhan, Chandan Kumar Biswas, “Modeling of machining parameters of MRR in the EDM in EDM using response surface methodology” National conference on mechanical science and technology. November 13-14 (2008). S. H. Tomadi, M. A. Hassan, Z. Hamedon “Analysis of the Influence of EDM Parameters on Surface Quality, Material removal rate & Electrode Wear of Tungsten Carbide” International Multi Conference of Engineers & Computer Scientists, March 18-20 2009 Volume-II. K. Ponappa , S. Aravindan, P. V. Rao, & M. Gupta “The effect of process parameters on machining of magnesium nano alumina composites through EDM” 02 July 2009, International Journal of Advance Manufacturing Technology. DOI 10.1007/s00170-009-2158-9. AkmAsifIqbal & Ahsan Ali Khan, “Modeling & analysis of MRR, EWR and Surface roughness in EDM Milling through response surface methodology” Journal of Engineering & Applied science.Vol-5(2010). DOI: 10.3923, pp154-162. AnandPandey, Shankar Singh “Current research trends in variants of Electrical Discharge Machining: A review” Journal of Engineering Science and Technology, Vol-2(6), 2010, pp21722191. S. S. Mahapatra& Amar Patnaik “Optimization of wire electric discharge machining process parameters using Taguchi method” (2008), International Journal Advance Manufacturing Technology. KuldipOjha and R. K. Garg, 2010 “MRR Improvement in sinking electrical discharge machining: A Review” Journal of Materials & Materials Characterization & Engineering. Volume -9, No.8, pp709-739. A. Manna & B. Bhattacharyya “Taguchi &Gauss elimination method: A dual response approach for parametric optimization of CNC wire cut EDM” 2006, International Journal of Advance Manufacturing and Technology. Vishal Kesarwani “Thesis on investigation of electrical discharge machine for optimization of surface roughness using response surface methodology approach” Department of Mechanical Engineering, National Institute of Technology, Rourkela, Orisa. Prof. P. R. Cheke, Prof. D. S. Khedekar, Prof. R. S. Pawar and Dr. M. S. Kadam, “Comparative Performance of Wet and Near-Dry EDM Process for Machining of Oil Hardned Non Sinking Steel Material”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp. 13 - 22, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359. Prakash R. Cheke, Prof. D. S. Khedekar, “Experimental Investigation of Machining Parameter for Wet & Near-Dry EDM Finishing”, International Journal of Design and Manufacturing Technology (IJDMT), Volume 2, Issue 1, 2011, pp. 28 - 33, ISSN Print: 0976 – 6995, ISSN Online: 0976 – 7002. 51