This document summarizes a research study that investigated near-dry electrical discharge machining (EDM) to optimize material removal rate (MRR) and surface finish. The study used a Taguchi L9 orthogonal array design of experiments to examine the effects of discharge current, pulse on time, gap voltage, and pulse off time on MRR and surface roughness. Response surface methodology was employed to optimize both responses simultaneously. The experimental results found that near-dry EDM achieved a better surface finish compared to wet EDM due to more stable machining at lower discharge energies. MRR and surface roughness were modeled as functions of the process parameters. The models showed the parameters and their interactions significantly affected MRR.

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
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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
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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.
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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
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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.
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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.
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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
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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.
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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
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