*Corr. Author’s Address: The Kavery Engineering College, Department of Mechanical Engineering, Salem, Tamil Nadu, India, sduraisivam26@gmail.com 547
Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556 Received for review: 2021-05-17
© 2021 Journal of Mechanical Engineering. All rights reserved.  Received revised form: 2021-09-18
DOI:10.5545/sv-jme.2021.7254 Original Scientific Paper Accepted for publication: 2021-09-24
Performance Study of EDM Process Parameters Using  
TiC/ZrSiO
4
 Particulate-Reinforced Copper Composite Electrode
Duraisivam, S. – Suresh, P. – Mahalingam, S. – Jamuna, E.
Duraisivam Saminatharaja
1,*
 – Suresh Periyakgounder
2
 – Mahalingam Selvaraj
3
 – Jamuna Elangandhi
1
1
The Kavery Engineering College, Department of Mechanical Engineering, India 
2
Sona College of Technology (Autonomous), Department of Mechatronics Engineering, India 
3
Sona College of Technology (Autonomous), Department of Mechanical Engineering, India
Electrical discharge machines (EDM) are widely employed in machining components containing complex profiles of hard-to-cut and machining 
materials. However, the fabrication-of-tool time for the EDM process is excessively high in the traditional machining method, which significantly 
affects the machining rate. Therefore, in this paper, a powder metallurgy (PM) technique is employed to fabricate the tool electrode using 
copper (Cu), titanium carbide (TiC), and zirconium silicate (ZrSiO
4
) for different combinations. An L18 orthogonal array (OA) is planned using 
the following input parameters: three types of tools (Cu, Cu
90
, Cu
80
), peak current (PC) [A], pulse on time (PT) [µs], and gap voltage (GV) [V]. The 
performance of EDM is evaluated through the material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The process 
parameters are optimized using two different techniques: the technique for order of preference by similarity to the ideal solution (TOPSIS) 
and grey relational analysis (GRA). TOPSIS and GRA optimization techniques produce the same optimal parametric solution for less TWR, SR, 
and higher MRR with the combination of the Cu
90
 tool, E8 APC, 15 µs pulse PT, and 75 V GV. Based on the ANOVA table of TOPSIS, pulse on 
time plays a major role, contributing 46.8 % of the machining performance; peak current shows the most significant contribution of 39.3 % of 
the machining performance using GRA values. Furthermore, the scanning electron microscope (SEM) image analyses are carried out on the 
machined workpiece surface to understand the effect of tools on machining quality.
Keywords: powder metallurgy, composite tool, copper, electrical discharge machine, technique for order of preference by similarity to 
ideal solution, grey relational analysis
Highlights
• 	 EDM process parameters (Gap voltage, current, pulse on time) were optimized through the L18 orthogonal experimental design 
method, GRA method, and the TOPSIS method considering responses, such as MRR, TWR, and SR.
• 	 Based on the experiment, MRR and TWR were increased by increasing the reinforcement percentage of composite electrodes.
• 	 It was revealed that the MRR value of the Cu
90
 tool electrode was 0.0319 g/min, which is 1.9 times higher than the other tool 
electrode.
• 	 Pulse on time and peak current have major contribution values (46.8 % and 39.3 %) from the ANOVA table of TOPSIS and GRA.
0  INTRODUCTION
EDM is a widely accepted and promising process 
used in non-traditional machining processes. Due to 
its unique nature of machining characteristics, the 
usage of EDM has been increasing enormously in 
manufacturing sectors, including forging, automobile, 
aviation, and the biomedical and medical industries. 
Moreover, an excellent surface finish and precision 
can be made by means of EDM, in cases in which the 
conventional machining method fails. The stainless 
steel (SS) SS304 has been employed in various 
manufacturing sectors due to its high toughness, 
wear resistance, and corrosion resistance. In the 
EDM process, apart from electrical parameters, other 
parameters, such as tool modification, dielectric 
medium changes, tool rotational assistances and tool 
vibration, play vital roles in improving machining 
performances. Therefore, various research attempts 
were undertaken in the previous decade by researchers. 
In line with that, Sivakumar et al. [1] investigated 
the EDM process parameters for oil-hardening, 
non-deforming tool steel (OHNS) using copper 
and titanium die boride composite electrodes. They 
developed the electrode using a powder metallurgy 
process and optimized the process through response 
surface methodology. Chakmakchi et al. [2] used a 
titanium alloy (Ti) as an electrode for machining the 
cobalt-chromium (Co-Cr) alloy and Ti6Al7Nb through 
the EDM process. The EDM process parameters were 
analysed using the evaluations of morphological and 
electrochemical changes in the workpiece, and the 
results were validated with copper electrodes. They 
identified that Ti electrodes have less degradation 
effect on the workpiece than copper electrodes did. 
Yadav et al. [3] used geometry-modified electrodes 
(e.g., slotted, helical, and tubular) in the EDM 
process. The influences of process parameters on the 
EDM performance were studied with the electrodes. 
They noted that the removal of machined products 
from the inter-electrode gap (IEG) for all tools had 
increased the machining rate and surface roughness 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
548 Duraisivam, S. – Suresh, P. – Mahalingam, S. – Jamuna, E.
of work materials. Taherkhani et al. [4] investigated 
the EDM process parameters using Al
2
O
3
 particles 
mixed dielectrically in various concentration ranges 
on titanium alloy. The significant enhancement in 
machining surface was due to the prevention of oxides 
lever formation in the dielectric medium. Also, the 
presence of oxygen and carbon elements leads to 
uniform power distributions, which control crack 
formations over the machining surface. Phan et al. [5] 
experimented with an aluminium electrode in EDM 
process to determine its suitability on the titanium 
alloy. They optimized the process parameters using 
Taguchi method and obtained the maximum MRR 
0.0239 g/min with less error. Ilani et al. [6] and [7] 
fabricated a tool in the technique of fused deposition 
modelling and employed EDM to improve the 
machining performance. The result was a tool using 
the surfactant stirred dielectrics such as with powder 
mixed and non-powder mixed electrolyte. They noted 
a 77 % improvement in surface roughness with this 
novel electrode. Also, this type of electrode is cost 
effective and makes the EDM functions easier for 
the production of complex geometries. Phan et al. [8] 
coated aluminium chromium nickel on an aluminium 
electrode to investigate the EDM parameters 
for titanium alloy. The experiments’ results of a 
coated electrode are compared with a non-coated 
aluminium electrode. The coating of the aluminium 
in the electrode increases the material removal rate 
significantly; the coated electrode produces 24 % less 
TWR than the uncoated electrode does. Shaikh and 
Ahuja [9] conducted the experiments with electrodes, 
such as silver coated tungsten and electroless nickel 
coated electrodes, in the EDM process. They noted 
that the electroless nickel-coated electrode has a20 
% higher machining rate than the silver-coated 
tool, which is because the electroless nickel coating 
increases the current distribution on the electrode. 
Walia et al. [10] studied the influences of a copper 
and titanium carbide mixed composite electrode on 
EDM with EN31 die steel. The copper composite 
electrode result reveals that the roundness of the 
hole was reduced around 25 % due to the electrode’s 
conductance change. They mentioned that significant 
performance results in terms of MRR and surface 
roughness were obtained with the composite electrode 
than the plain copper electrode. Sahuand Mahaptra [11] 
prepared a aluminium, silicon, and magnesium mixed 
composite electrode through selective laser sintering 
method. They considered titanium as a workpiece 
and conducted the experiments using various tools, 
including composite, graphite, and copper electrodes. 
They obtained higher TWR and excellent surface 
roughness with the composite electrode than other 
tools. Mahipal Reddy et al. [12] employed a3D 
printing (i.e., direct metal laser sintering) to fabricate 
the aluminium composite electrode used in the EDM 
of steel alloy. The experiment results were compared 
with the commercial electrodes and performances 
were evaluated by means of MRR, TWR, and 
Servient et al. [13] used a rotary type tool in EDM 
of work material: high-speed steel through air mixed 
glycerine dielectric medium. The tool rotation speed, 
gas pressure, current, and dielectric flow rate were 
considered for the process parameters on the study of 
machining rate, overcut and surface roughness. They 
noted the improvement in the machining rate and 
surface roughness with the rotary tool electrode. Padhi 
et al. [14] used the additive manufacturing tool for 
machining the D2 steel using EDM. They coated the 
electrode with acrylonitrile-based polymer by fusion 
deposition method, which increased the electrical 
conductance of the electrode and increased the 
machining rate significantly. Mathai et al. [15] adopted 
the planetary tool movement on EDM to investigate 
the process parameters for titanium alloy. Along with 
this planter movement, they fabricated square holes 
with two types of electrodes materials (i.e., copper 
and graphite). Also, they noted that the copper tool 
produced better machining rate and surface finish 
than the graphite electrodes did. Wang et al. [16] tried 
two types of electrodes (i.e., cylindrical and helical) 
in a micro-EDM process on titanium alloy. The 
helical electrode increases the debris removal passage 
between tool and electrode, which increases the 
current flowability. This phenomenon ensures the high 
machining rate and better surface finish on the micro 
holes. Vincent and Kumar [17] used copper and brass 
rotary electrodes with EDM on En41b steel. They have 
noted less tool wear rate on the copper electrode than 
the brass electrode due to the current fluctuation on 
the IEG. Also, based on the analyses of variance, pulse 
on time and pulse off time played major role on the 
machining performance. Singh et al. [18] investigated 
the EDM performance using an air-associated rotary 
tool on high chromium die steel. They compared 
the experimental results with non-air assisted EDM 
under the same parameter setup. According to this, a 
high machining rate and less overcut was found on 
the air-assisted tool than the normal tool. Along with 
various techniques employed in EDM to enhance its 
performances (e.g., powder mixed dielectric [19], tool 
coating [20] and optimization of process parameters), 
using various techniques such as TOPSIS, Taguchi-
data envelopment analysis-based ranking, Taguchi–
grey relational analysis by the researchers [21] to [24]. 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
549 Performance Study of EDM Process Parameters Using TiC/ZrSiO4 Particulate-Reinforced Copper Composite Electrode 
The aforementioned literature clearly indicates 
that the various research methodologies have been 
followed by the researchers to enhance the EDM 
process. However, research on powder metallurgy-
based tools on the EDM process is sparse. Although 
some researchers have considered PM tools in 
EDM, all the methods show poor surface finish and 
machining rate due to the improper reinforcements 
with Cu [25] to [27]. Titanium carbide and zirconium 
silicate particles possess an excellent affinity with Cu 
material due to their crystallographic nature. Hence, in 
this research, two electrodes in different reinforcement 
combinations (i.e., 90 % Cu, 5% TiC 5 % ZrSiO
4
(Cu
90
) 
and 80 % Cu, 5% TiC 5 % ZrSiO
4
(Cu
80
)) are prepared 
using PM technique. The results of these tools are 
compared with plain Cu electrodes. With these three 
tools, EDM and its process parameters are optimized 
using TOPSIS and GRA methods. Furthermore, 
scanning electron microscope (SEM) image analyses 
are carried out for the better understanding of the 
effect of PM-based tools on machining performances.  
1 EXPERIMENTAL SETUP
The experiments are conducted using a ZNC EDM 
machine, shown in Fig. 1. The tool electrode was 
prepared based on the powder metallurgy technique 
and hot extrusion method employed to diminish the 
porosity of the composite. The materials Cu- TiC- 
ZrSiO4 are used for the tool electrode preparation 
with various weight ratios, as shown in Table 1. The 
procedures for producing tool electrodes are followed 
from the literature [28] and explored in Fig. 2. The 
grain sizes of reinforcement particles are considered 
lower than 75 μm for all electrode samples. The 
composite electrodes of diameter 10 mm and 5 
cm length are prepared. When considering various 
application of SS, in this attempt 5 mm thick SS 304 
materials are used as work material. 
Fig. 1.  EDM setup
The machining parameters levels and experimental 
planning with outcomes are shown in Tables 2 and 3. 
L18 OA is planned with three tool electrodes: PC, PT, 
and GV. The SEM pictures of PM-based electrodes 
(i.e., Cu, Cu
90
, and Cu
80
) are shown in Figs. 3 to 5. 
The performances of EDM are estimated in terms of 
MRR, TWR, and SR. The commercially available 
dielectric medium kerosene is used for flushing 
between the tool and electrode. The machining times 
fixed as 30 minutes for all experiments, and levels of 
parameters are selected based on the literature [28]. 
Every completion of experimental workpieces and 
electrodes are cleaned using acetone to remove debris 
from the machining zone of workpiece. Before and 
after machining weights of tools and workpieces are 
Fig. 2.  Powder metallurgy-based electrodes

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
550 Duraisivam, S. – Suresh, P. – Mahalingam, S. – Jamuna, E.
taken into the account for calculating the MRR and 
TWR, respectively [29]. The surface roughness of the 
machined area is measured using a surface roughness 
testing machine (Surf test SJ-210, Mitutoyo, Japan). 
Furthermore, SEM image analysis is carried out 
on the machined workpiece surfaces for a better 
understanding of the effect of tools on machining.
Table 1.  Weight ratios of electrode
Electrodes 
type
Electrodes  
No
% of reinforcements 
Cu TiC ZrSiO
4
Cu Cu 100 - -
Cu
90
Cu
90
(TiC)
5
(ZrSiO
4
)
5
90 5 5
Cu
80
 Cu
80
(TiC)
10
(ZrSiO
4
)
10
80 10 10
Table 2.  Range of machining parameters
Symbol Machining parameters Unit L-1 L-2 L-3
A Electrode type - Cu Cu
90
Cu
80
B Peak current [A] 8 16 24
C Pulse on [µs] 15 30 45
D Gap voltage [V] 50 75 100
Fig. 3.  Plain Cu electrode (Cu)
Fig. 4.  Cu
90
(TiC)
5
(ZrSiO
4
)
5
 electrode (Cu
90
)
Fig. 5.  Cu
80
(TiC)
10
(ZrSiO
4
)
10
 electrode (Cu
80
)
Table 3.  Experimental planning
Run TE PC PT GV
MRR 
[g/min]
TWR  
[g/min]
SR 
[µm]
1 1 8 15 50 0.0101 0.0533 4.12
2 1 16 30 75 0.0011 0.0253 4.39
3 1 24 45 100 0.0231 0.0538 5.27
4 2 8 15 75 0.0365 0.0451 5.89
5 2 16 30 100 0.0112 0.0423 6.92
6 2 24 45 50 0.0099 0.0266 5.87
7 3 8 30 50 0.0098 0.0451 5.94
8 3 16 45 75 0.0012 0.0296 6.12
9 3 24 15 100 0.0014 0.0091 7.14
10 1 8 45 100 0.0356 0.0478 7.82
11 1 16 15 50 0.0085 0.0225 7.18
12 1 24 30 75 0.0130 0.0489 8.23
13 2 8 30 100 0.0201 0.0589 7.87
14 2 16 45 50 0.0173 0.0149 8.12
15 2 24 15 75 0.0194 0.0412 8.94
16 3 8 45 75 0.0080 0.0072 8.15
17 3 16 15 100 0.0251 0.0188 7.25
18 3 24 30 50 0.0097 0.0419 8.92
1.1  Multi-objective Optimization 
1.1.1 Technique for Order of Preference by Similarity to 
Ideal Solution (TOPSIS)
TOPSIS is an appropriate technique to identify 
the suitable parametric solution from the set-off 
experimental combinations. The procedures followed 
in this method are provided below [30] and [31].
Step 1: Choices of variables, i.e., all the responses 
are employed in the matrix in n attributes and m 
alternatives, which is shown with Eq. (1).

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
551 Performance Study of EDM Process Parameters Using TiC/ZrSiO4 Particulate-Reinforced Copper Composite Electrode 
 E
m

RRRR
RRRR
RRRR
RRRR
n
n
n
mmm
11 12 13 1
21 22 23 2
31 32 33 3
123
…
…
…

…
m mn
















, (1)
where R
ij
 is the presentation of i
th
 alternative with 
respect to j
th
 attribute.
Step 2: Eq. (2) has been used for the normalization 
of matrix values, which can convert all values in a 
single form of units. 
 r
R
R
jn
ij
ij
i
m
ij
 


1
2
12 ,, ,, . (2)
Step 3: Weights for the output responses are 
assigned using Eq. (3) as W
j
(  j = 1, 2, …. ,n). The 
preferences for outcome responses are assigned based 
on the requirement.
 Y = W
j
 r
ij
, (3)
where, 
j
n
j
W



1
1. 
.
Step 4: Suitable (best) ideal result is estimated 
using Eq. (4) and the worst ideal result is attained 
through Eq. (5). 
   
YY ij jJ im
yyy y
i
n

 
 
 
 


max
|| ,, ,
,,, .., ,
12
123
 (4)
   
YY ij jJ im
yyy y
i
n

 
 
 
 


min
|| ,, ,
,,, .., .
12
13 2
 (5)
Step 5: The value differences among the 
parameters are evaluated with the ‘suitable ideal’ 
solution is calculated using Eq. (6).
 tY yi m
i
j
n
ij j







1
12 ,, ,. ,. (6)
The deviation of experimental results from the 
‘worst–ideal’ solution is calculated using Eq. (7).
 tY yi m
i
j
n
ij j







1
12 ,, ,. ,. (7)
Step 6: Eq. (8) used to find the closeness of 
various parameters solution which is presented below. 
 P
t
tt
im
i
i
i i





,, ,, . 12 (8)
Step 7: Obtained preference values (P
i
) are 
ordered in a downward manner to identify the best 
parameter solution. 
1.1.2  Grey Relational Analysis Technique (GRA)
With the GRA method, the output responses of different 
units should be converted into a homogeneous form 
(i.e., unit-less number). Therefore, the experimental 
results are converted from zero to one through the 
below-mentioned equations [30] and [31]. The output 
values (i.e., MRR, TWR and SR values) are estimated 
using Eqs. (9) and (10), respectively:
 YP
yP yP
yP yP
i
ii
ii
*
min
maxm in
,  
  
  
 (9)
where i = 1, 2, …, m, P = 1, 2, …, n,
 yP
yP yP
yP yP
i
i
ii
*
max
maxm in
,  
  
  
 (10)
where i = 1, 2, …, m, P = 1, 2, …, n.
Here, the equation contains m means the total 
number of experiments and n means received data. 
Eq. (11) is employed to estimate the grey relational 
coefficient (GRC) with the normalized values:
 kN
Q
i
oi
 

 


minm ax
max
.


 (11)
Here, Δ
oi
(Q) divergence series is chosen from 
the reference sequence k(N) and comparability 
sequence k
i
*
(N). The range 0 to 1 has been used for 
the distinguished coefficient k
i
.
 T
n
jN
i
P
n
i
 


1
1
. (12)
The weight values of each output response are in 
summation with GRC to find the grey relational grade 
(GRG) T
i
 is displayed in Eq. (12).

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
552 Duraisivam, S. – Suresh, P. – Mahalingam, S. – Jamuna, E.
2  RESULT AND DISCUSSION
2.1  Influences of Input Parameters on MRR
The influences of the input parameters (i.e., electrode, 
peak current, pulse on time and gap voltage on MRR) 
are presented in Fig. 6. The experiments are conducted 
using three different tools, displayed in Table 3. The 
graphs are drawn according to the mean values of 
MRR against the input parameter values. It is clear 
from the figure that using composite tools exhibits 
higher MRR when compared to the plain copper 
tool, which produces 0.0319 g/min MRR. This value 
is 1.9 times higher than the existing composite tool 
used in the EDM process. The PM-based composite 
tools possess uneven surfaces at the end face tool with 
porosity. Hence, the passing of electric current has 
fast movement between the inter-electrode gap, which 
ensures higher MRR with the composite electrode 
[32]. Also, MRR is increased with the increasing 
percentage of titanium carbide and zirconium silicate 
in the composite tools. The softness of the composite 
tool is increased by the presence of zirconium silicate, 
which leads to high inter-metallic gaps among the 
particles. This phenomenon leads to better current 
conductance in the tool electrode and leads to the 
higher MRR. 
Fig. 6.  Influences of input parameters on MRR
Moreover, from the figure, it is observed that 
increasing the peak current increases the MRR. It is a 
common fact that increasing the current with no flow 
disturbance in the electrode can produce the narrow 
power supply in the machining zone, which causes 
higher MRR [33]. The same trend of higher MRR has 
been obtained with the increasing of pulse on time and 
gap voltage. The timing of current passage and flow 
ability increases at higher level, which leads to the 
higher MRR for all tools. 
2.2  Influences of Input Parameters on TWR
The effect of input parameters on TWR is displayed in 
Fig. 7. The figure shows that PM-based tools produce 
lower TWR (0.0234 g/min) when there is an increase 
in the percentage of titanium carbide and zirconium 
silicate. Increasing the percentage of compositions 
increases the wear resistance among particles and 
increases the porosity of the tools. Therefore, the 
connectivity of the current is disbursed when it is 
applied to the machining zone [34]. This character 
of tool electrodes leads to less TWR on PM tools at 
higher levels of parameter combinations. However, the 
percentage of titanium carbide and zirconium silicate 
at the middle stage electrode (i.e., 5 % TiC and 5 % 
ZrSiO
4
) shows the increased TWR with increasing 
of parametric range. It is because titanium carbide 
provides the additional energy to the electrode to pass 
the current by its conductivity nature. Therefore, the 
middle stage of composite electrodes produces the 
higher TWR. , due to the high spark energy of tool, 
higher TWR has been obtained with the higher peak 
current, pulse on time and gap voltages. 
Fig. 7.  Influences of input parameters on TWR
2.3  Influences of Input Parameters on SR
The effect of input parameters on the SR is displayed 
in Fig. 8. The SR shows the increasing trend with 
increases in parameters values. Better surface finish is 
observed with plain copper tool, producing the surface 
finish in the range of 6.16 µm to 7.04 µm, which is 
lower than other PM-based composite tools. 
The PM composite tool produces crater surfaces, 
and it becomes the cause of higher MRR. The higher 
craters exhibit less surface finish and elements of the 
tool transferred over the machined surfaces. Hence, 
the surface finish of the machined area leads to the 
poor quality with PM composite tools than plain 
copper tool [35]. Also, the increasing of peak current, 
pulse on time, and gap voltage cause increasing spark 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
553 Performance Study of EDM Process Parameters Using TiC/ZrSiO4 Particulate-Reinforced Copper Composite Electrode 
energy on the machining zone, which leads the excess 
material removal on the work material [36]. The 
SEM image of the machined area are shown in Figs. 
9 and 10 for first and second optimal combinations. 
Furthermore, the machined products (debris) are 
deposited over the crater surface due to the improper 
flushing and form the recast layer on the machined 
surface.
Fig. 8.  Influences of input parameters on SR
Fig. 9.  SEM image of 1st optimal combination
Fig. 10.  SEM image of 2nd optimal combination
2.4  TOPSIS
The output values of EDM such as MRR, TWR and 
SR through PM based tools are optimized using the 
TOPSIS technique. Eqs. (1) to (8) have been used to 
obtain the preference value for the experimentations. 
Equal weights are assigned to all output responses 
under ideal conditions. The preferences values (Pi) 
and their ranking orders are represented in Table 
4. The outcomes of the research are converted from 
multi-objective optimization to single attribute 
optimization through combined methods of Taguchi 
and TOPSIS. The furthest preference value is termed 
as optimal parameter solution and the maximum rank 
is considered as the first optimal solution. Therefore, it 
is observed that the 17
th
 experimental run (0.6735) is 
chosen as the best optimal parameter solution for the 
best performance of EDM due to the highest Pi value. 
The experimental runs 4
th 
(0.6714) and 10
th 
(0.6259) 
show the second and third best optimal parameter 
combinations. Hence, the best optimal solution is 
found to be the Cu
90
(TiC)
5
(ZrSiO
4
)
5 
PM-based tool, 
E8 Amp peak current, 15 µs pulse on time and 75 V 
gap voltage using TOPSIS. 
Table 4.  TOPSIS ranking
Experiment 
No.
Yi + Yi –
Pi (Preference 
value)
Rank
1 0.4504 0.2039 0.3116 13
2 0.4836 0.2561 0.3462 12
3 0.3388 0.3187 0.4847 5
4 0.2393 0.4890 0.6714 2
5 0.4100 0.1815 0.3068 14
6 0.3777 0.2520 0.4002 8
7 0.4281 0.1752 0.2904 16
8 0.4933 0.2032 0.2917 15
9 0.4773 0.3111 0.3946 9
10 0.2779 0.4649 0.6259 3
11 0.3970 0.2512 0.3876 10
12 0.4263 0.1713 0.2866 17
13 0.4042 0.2556 0.3874 11
14 0.2920 0.3462 0.5425 4
15 0.3479 0.2664 0.4337 7
16 0.4014 0.3309 0.4519 6
17 0.1972 0.4068 0.6735 1
18 0.4450 0.1545 0.2578 18
2.6  Table of ANOVA for TOPSIS
ANOVA is a prominent method to determine the 
important and insignificant factors. The Pi values of 
PM-based tools are statically analysed using ANOV A, 
and the influences of each parameter over the output 
responses are examined. In addition, the F-test 
outcomes are used to identify the most important 
factor to attain better performance. Table 5 shows that 
pulse on time plays a major role, which contributes 
around 46.8 % to the machining performance. The 
next important factor is the tool electrode, which 
controls the machining performances, contributing 
about 27.7 %. 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
554 Duraisivam, S. – Suresh, P. – Mahalingam, S. – Jamuna, E.
Table 6.  GRG ranking 
Experiment 
No.
GRC
GRG Rank 
MRR TWR SR
1 0.5729 0.5286 1.0000 0.5508 18
2 0.5000 0.7407 0.9470 0.6204 11
3 0.7254 0.5258 0.8074 0.6256 10
4 1.0000 0.5773 0.7314 0.7887 1
5 0.5832 0.5955 0.6325 0.5894 14
6 0.5708 0.7279 0.7336 0.6493 8
7 0.5703 0.5771 0.7259 0.5737 17
8 0.5007 0.6984 0.7067 0.5996 12
9 0.5023 0.9651 0.6148 0.7337 6
10 0.9745 0.5603 0.5657 0.7674 4
11 0.5585 0.7725 0.6117 0.6655 7
12 0.6010 0.5536 0.5398 0.5773 16
13 0.6839 0.5000 0.5624 0.5919 13
14 0.6484 0.8708 0.5465 0.7596 5
15 0.6742 0.6037 0.5000 0.6389 9
16 0.5545 1.0000 0.5446 0.7773 3
17 0.7568 0.8167 0.6063 0.7868 2
18 0.5691 0.5983 0.5010 0.5837 15
Table 7.  Table of ANOVA for GRG
Machining 
parameter 
symbol
DOF SS MS F test % Contri
TE 2 0.0098 0.0049 0.284 8.03
PC 2 0.0479 0.024 17.20 39.30
PT 2 0.0449 0.0225 16.12 36.82
GV 2 0.0068 0.0034 2.43 5.56
E 9 0.0125 0.0014 10.27
Total 17 0.1219 0.0072 100
Fig. 11. Comparison of TOPSIS and GRA ranking
3  CONCLUSIONS
This research work aims to explore the benefits and 
performance measures of powder metallurgy-based 
copper electrodes in the EDM process. Two electrodes 
in different reinforcement combinations (i.e.,  
Table 5.  Table of ANOVA for TOPSIS
Machining 
parameter 
symbol 
DOF SS MS F-test % Contri
TE 2 0.0835 0.0418 2.9863 27.76
PC 2 0.0417 0.0209 1.4913 13.86
PT 2 0.1410 0.0705 5.0434 46.89
GV 2 0.0123 0.0062 0.4406 4.09
E 9 0.1258 0.0140 7.38
Total 17 0.4044 0.0238 100
2.7  GRA
In GRA method, outcomes of EDM (i.e., MRR, TWR, 
and SR) for various tools are normalized using Eqs. 9 
and 10. Eqs. 11 and 12 are used to determine the GRC 
and GRG, respectively, for all conducted experiments. 
Equal weights are assigned for all responses. GRG 
and its rankings are displayed in Table 6. The 
furthest GRG value has been considered the optimal 
parameter solution. Therefore, based on the table, 
the 4
th
 experimental run (0.7887) is the best optimal 
parameter solution, and the 17
th 
(0.7868) and 16
th
 
(0.7773) experimental runs are the next best optimal 
parameter solutions through GRA method. Hence, the 
optimal parameter solution found to be Cu
90
(TiC)
5 
(ZrSiO
4
)
5 
PM-based tool, 8 A peak current, 15 µs 
pulse on time and 75 V gap voltage using GRA. 
2.7  Table of ANOVA for GRG
The GRG results of various tools are statically 
analysed using ANOVA, presented in Table 7. The 
outcomes of results for PM based tools are optimized 
using the GRA method.
Therefore, peak current shows the most 
significant contribution around 39.3 % on machining 
performance. 
The next significant parameter is pulse on time, 
which contributes on performances around 36.8 %. 
The ranking values of TOPSIS and GRA 
technique are presented as a graph in Figure 8, 
which is plotted for experimental run vs. TOPSIS 
and GRA values. The 4
th 
and 17
th
 experimental runs 
show the first two optimal combinations for the best 
performance of EDM using the TOPSIS and GRA 
methods. Moreover, in both techniques, they provide 
the same parametric combination for machining. Also, 
the 10
th
 and 16
th
 experimental runs show the third 
optimal combinations using the TOPSIS and GRA 
methods. 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)11, 547-556
555 Performance Study of EDM Process Parameters Using TiC/ZrSiO4 Particulate-Reinforced Copper Composite Electrode 
Cu
90
(TiC)
5
(ZrSiO
4
)
5
 and Cu
80
(TiC)
10
(ZrSiO
4
)
10
) are 
prepared using a PM technique, and their results are 
compared with a plain Cu electrode. The experiments 
are conducted based on the L-18 OA, and optimization 
techniques (e.g., TOPSIS and GRA) are used to find 
the optimal solution.
The results show that MRR and TWR increase 
with increasing of the percentage of reinforcements 
in the composite electrodes. The Cu
90 
(Copper 
composite) tool electrode exhibits 0.0319 g/min MRR 
and this value is 1.9 times higher when compared to 
the existing tool electrode. The TOPSIS and GRA 
optimization techniques produce the same optimal 
parametric solution for lesser TWR, SR and higher 
MRR. Hence, the 17
th
 experimental run is proposed as 
optimal parameter combination: Cu
90
(TiC)
5
(ZrSiO
4
)
5
, 
E8 Amp peak current, 15 µs pulse on time and 75 V 
gap voltage. In addition, based on the ANOV A table of 
TOPSIS, pulse on time plays a major role, contributing 
around 46.8 % tp the machining performance, and 
peak current shows the most significant contribution 
of around 39.3 % on machining performance using 
GRA values.
Therefore, the Cu
90
composite tool is more 
appropriate for the higher MRR and less TWR. 
Furthermore, experiments can be conducted with 
various concentrations of reinforcements and different 
work materials to understand the behaviour of 
machining.
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