Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330 Received for review: 2021-03-13
© 2021 Journal of Mechanical Engineering. All rights reserved.  Received revised form: 2021-05-28
DOI:10.5545/sv-jme.2021.7161 Original Scientific Paper Accepted for publication: 2021-06-18
*Corr. Author’s Address: Department of Mechanical Engineering, Muthayammal Engineering College, Rasipuram-637408, Namakkal (Dt), India, boopasangee@gmail.com. 322
Experimental Investigation of a Cryogenically Cooled Oxygen-
mist Near-dry Wire-cut Electrical Discharge Machining Process
Sampath, B. – Myilsamy, S.
Boopathi Sampath
1,*
 – Sureshkumar Myilsamy
2
1
Muthayammal Engineering College, Department of Mechanical Engineering, India 
2
Bannari Amman Institute of Technology, Department of Mechanical Engineering, India
In this paper, a novel method of cryogenically cooled (low-temperature nitrogen gas) wire tool is used during the oxygen-mist near-dry wire-cut 
electrical discharge machining (NDWEDM) process to cut Inconel 718 alloy material. The current, pulse-width, pulse-interval, and flow rate are 
the controllable variables for response characteristics, such as the material removal rate (MRR) and wire wear ratio (WWR). The Box-Behnken 
method is applied to design the experiments to collect the observations from experiments. The mathematical models for each response were 
developed using significant individual, interaction, and quadratic terms by the sequential sum of the square test. The response surfaces were 
developed. It was revealed from the analysis that 52.92 % of current, 24.63 % of Pulse-width, 12.81 % of pulse- interval and 5.75 % of flow 
rate contributed to MRR, while 14.89 % of current, 9.75 % of pulse-width, 62.20 % of pulse-interval, and 5.44 % of flow rate contributed 
to WWR. The pulse-width has more contribution on MRR due to the long period of spark between the wire and work materials. It was also 
observed that the pulse-interval has more effect on WWR due to the more ideal period (high spark-pause-time) between two consecutive high-
temperature sparks in the wire tool. The wear of the wire tool has been analysed using scanning electron microscopy (SEM) photographs. The 
desirability principles were first applied to obtain multi-objective solutions with a combination of process parameters to achieve the optimal 
values of both responses. The predicted combination of results has been validated by data that were collected from confirmation experiments.
Keywords: cryogenically cooled, oxygen-mist, near-dry, wire-cut EDM, MRR, WWR, Box-Behnken method
Highlights
• 	 A novel method of cryogenically cooled (low-temperature nitrogen gas) wire electrode tool in the oxygen-mist near-dry wire-cut 
electrical discharge machining (NDWEDM) process was experimented with to cut the Inconel 718 alloy material. 
• 	 Wire wear ratio and material removal rate of cryogenically cooled near-dry WEDM process was first investigated in this research.
• 	 It was revealed that the pulse-interval has more effect on wire wear ratio due to a more ideal period (high spark-pause-time) 
between two consecutive high-temperature spark in the wire tool. 
• 	 The wear of the wire tool has been analysed using Scanning Electron Microscopy test photographs.
• 	 The desirability principles were first applied to obtain the multi-objective solutions to optimize both responses.
0  INTRODUCTION
In an unconventional machining process, the 
relationships between manufacturing parameters and 
environmental impact are developed to analyse the 
material removal mechanics, tool change, minimum 
rejections in production, and the effects of cutting-
fluid flow [1]. The environmental impact of machining 
processes should be analysed for minimizing 
environmental impacts by the modification of 
existing technology and the development of new 
manufacturing methods [2]. In these aspects, 
research into the modification of EDM and WEDM 
processes was developed to make a trade-off between 
machining performance and machining pollutions 
[3]. The analytical relationship of EDM processes 
was developed to reveal the wear of the tool and 
workpiece, the dielectric fluid flows, and toxicity 
and flammability [3] and [4]. The inferences of 
cooling electrode wear and surface roughness of the 
workpiece have been investigated by changing process 
parameters, such as voltage, pulse-width, current, and 
pulse-interval [5] and [6]. The parametric analysis of 
dry electric discharge machining of mild steel was 
investigated, and response models were developed 
using response surface methodology [7]. Generally, 
the machining performance of the dry EDM process is 
very low compared to the conventional process. It was 
revealed that the tool wear of the dry EDM process 
is significantly reduced by cryogenic cooling of the 
electrode and workpiece [8]. The mechanism of the 
gas-liquid-powder mixture in EDM was investigated 
in both dry and near-dry processes to improve material 
erosion. The cryogenically tested brass wire produces 
a 22.55 % greater material removal rate (MRR) 
compared to an untreated brass wire [9]. A parametric 
study was performed using a molybdenum wire tool 
and tool steel workpiece with an air dielectric to 
investigate the influence of air-mist pressure, voltage, 
pulse-duration, pulse-width, and current on the MRR 
and Ra using the Taguchi technique [5] and [10]. 
Later, the oxygen gas near-dry WEDM experiments 
were conducted using Taguchi’s L27 orthogonal array 
and multi-objective artificial bee colony (MOABC) 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
323 Experimental Investigation of a Cryogenically Cooled Oxygen-mist Near-dry Wire-cut Electrical Discharge Machining Process
algorithm [11] and [12]. Cryo-treated wire electrodes, 
liquid nitrogen, and zinc-coated brass wires were 
investigated to reduce the tool wear rate for the green 
environment [4], [13] to [15]. Recently, the electrical 
conductivity of cryo-cooled molybdenum wire has 
been increased by cryogenic treatments [16]. However, 
no synchronized cryo-treated gas-liquid mixer was 
found in the near-dry EDM and WEDM process.  
In this research, the data from 29 observations 
from cryogenically cooled oxygen-mist near-dry 
WEDM experiments were collected. The collected 
data are used to predict the data for better results of 
the near-dry WEDM process. The significant process 
parameters were identified to improve the quality of 
cutting processes. The desirability approach is used 
to convert the single-objective problem into a multi-
objective optimization problem. The WEDM machine 
manufacturer and operators utilize the optimum 
results to set the optimal process parameters for the 
best machining performances. 
1  EXPERIMENTATION 
1.1  Experimental Setup
The cryo-cooled wire electrode setup was developed 
in numerically controlled (NC) wire-cut electrical 
discharge machining. Liquid nitrogen was stored in 
a dewar flask to maintain the cryogenic temperature. 
The molybdenum wire was cooled on both sides of 
the electrode movements. The oxygen and dielectric 
fluid mixture are used as a working medium in 
the reciprocating WEDM machine. Based on 
trial experiments, the input parameters and their 
significance levels are identified. The billet size of 
718 is 50 mm × 50 mm × 5 mm Inconel 718 is used 
as work material for near-dry WEDM machining 
processes. The experimental setup of cryo-cooled 
near-dry WEDM is shown in Fig. 1. Sub-123 K of 
liquid nitrogen was stored. The 253 K temperature 
and 10 g/s mass flow rate of N
2
 were used to cool the 
molybdenum wire during the cutting process. The 
oxygen and the dielectric fluid mixture were used 
as a dielectric medium in reciprocating the WEDM 
machine. The MRR in [mm
3
/min] can be calculated 
by the volume of materials removed concerning time 
using Eqs. (1) and (2).
      Kerf wire diameter sparking gap    2, (1)
 MRR
thicknessK erfl engtho fc ut
time


. (2)
The wire wear ratio (WWR) has been measured 
from the loss of wire materials during the cutting 
process concerning the time, and the initial weight of 
wire is to be taken before machining process [17] (Eq. 
(3)). 
 WWR
weight loss of wire
initialw eight of wire
= . (3)
Based on exploratory experiments, the input 
parameters and their significance levels are identified. 
The levels of each process variable are tabulated 
in Table 1. The near-dry WEDM experiments are 
conducted [18], and the MRR and WWR values 
observed through the experiments are shown in Table 
2.
Fig. 1.  Cryogenically cooled oxygen-mist near-dry WEDM 
experimental set
Table 1.  Parameter and Machine Setting level
Description Symbol Parameter Units Low High Mean
Input parameters 
C Current A 3 5 4
PW Pulse-width µs 15 25 20
PI Pulse-interval µs 45 75 60
F Flow rate ml/min 10 20 15
Dielectric medium Oxygen gas mixed with water
Wire treatment Cryogenic Nitrogen gas during the machining process
Output parameters MRR in [mm
3
/min], and WWR 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
324 Sampath, B. – Myilsamy, S.
1.2  Design of Experiments
The Box-Behnken method is used to conduct the 
experiments by design expert software. The Box-
Behnken design is a self-determining quadratic 
design, which does not contain the partial factorial 
design. The designs have restricted capability related 
to the central composite designs. Five central points 
are repeated to avoid bios errors. The design uses 8 
trails from (2 × 4 = 8) two levels of k parameters, 16 
trails of two factorial design (24
 
= 8), and five repeated 
central points to calculate lack-of-fit. Twenty-nine sets 
of experiments were conducted, and the observed 
responses are tabulated in Table 2. Based on the 
analysis of the variance test, the significant individual 
and interaction and quadratic terms were identified 
[5]. Insignificant terms are eliminated from the model. 
Table 2.  Design of Experiments and observations using Box–Behnken method
Exp. No. C PW PI F MRR WWR
1 3 20 75 15 6.13 0.464
2 5 20 75 15 9.45 0.626
3 4 15 60 20 8.38 0.643
4 4 20 45 10 9.28 0.994
5 4 25 60 10 9.57 0.921
6 4 20 60 15 9.12 0.783
7 4 20 60 15 9.09 0.724
8 4 15 75 15 7.12 0.424
9 5 20 60 20 10.9 0.829
10 3 25 60 15 8.51 0.864
11 3 20 60 10 6.58 0.745
12 4 25 45 15 10.91 0.991
13 4 20 75 10 7.78 0.635
14 3 20 45 15 7.76 0.848
15 4 15 60 10 7.38 0.767
16 4 15 45 15 8.67 0.921
17 4 20 75 20 8.74 0.478
18 5 20 45 15 10.87 1.050
19 5 20 60 10 9.44 0.934
20 4 25 75 15 9.38 0.670
21 5 25 60 15 10.77 0.872
22 4 20 45 20 10.29 0.905
23 5 15 60 15 9.47 0.913
24 4 20 60 15 9.12 0.778
25 4 20 60 15 9.11 0.78
26 4 25 60 20 10.63 0.807
27 4 20 60 15 8.77 0.772
28 3 15 60 15 6.02 0.502
29 3 20 60 20 7.24 0.621
If the response is ‘f(x)’, the independent variables are 
x
1
, x
2
, …, x
n
, and the response model is developed by 
following general Eq. (4). 
fx xx x
i
i
k
ij ij
j
k
i
k
() ... ,   
 
 
 
00
11 1
 
 and i < j, (4)
where k is the number of process variables; β
0
, β
i
, and 
β
ij
 are the model coefficients; ϕ is the statistical error, 
which represents variability by other noises. 
 
2  RESULT ANALYSIS AND DISCUSSIONS  
The sequential sum of the square test was used to select 
the optimum model for the analysis. Initially, the linear 
model is selected [12]. However, the model is not 
significant due to the coefficient of determination (R
2
) 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
325 Experimental Investigation of a Cryogenically Cooled Oxygen-mist Near-dry Wire-cut Electrical Discharge Machining Process
value of MRR and WWR is very low (MRR R
2
 =0.072 
and WWR R
2
 = 0.81). The two factors interaction 
model (2FI) also did not fit with the solution due to the 
R
2
 value of both models is minimum (MRR R
2
 = 0.608 
and WWR R
2
 = 0.075). Then, the quadratic model of 
MRR was selected due to the R
2
 value of 0.998 of 
both responses. The insignificant terms of the models 
were eliminated from quadratic models. The lack of 
fit of the model is insignificant and thus acceptable. 
The cubic models of both responses were not selected 
due to more allies’ terms in the models. The lack of 
fit tests of MRR and WWR are shown in Tables 3 and 
5, respectively. The analysis of the variations of MRR 
and WWR concerning process parameters are shown 
in Tables 4 and 6, respectively. The regression models 
of MRR and WWR were developed to identify the 
inference of process variables as shown in Eqs. (5) 
and (6) respectively.
MRRC PW PI
FC PW
  
  

8 241 5 335 04 50 065
0 0575 0 0595
3
.. ..
..
.. .
.,
51 00 04
0 425
3
2
  


CP IC F
C
 (5)
R
2
 = 99.40 %, Adjusted R
2
 = 99.14 %, and
Predicted R
2
 = 98.18 %.
WWR CP W
PI F
  
  


0 529 0 501 0 061
6 161 10 1 727 10
00
33
.. .
..
.2 201 5 867 10
2 267 10 1 298 10
4
44 2
  
   


CP WP WP I
PI FP I
.
.. , (6)
R
2
 = 99.40 % , Adjusted R
2
 = 99.16 %, and
Predicted R
2
 = 99.04 %.
The insignificant terms are eliminated from MRR 
and WWR regression models to improve the predicted 
R
2
 and adjusted R
2
. The regression models are used 
to plot the response surface between response and 
process variables. The influences of the interaction 
effects of process parameters have been studied using 
the response surfaces. 
The response surface of MRR for flow rate and 
current is shown in Fig. 2. It is also significantly 
enhanced by increasing the flushing flow rate due to 
the quick disposal of debris from the cutting zone. 
Fig. 3 shows that the response surface of MRR by the 
pulse-width vs current. The MRR is improved by the 
increase in spark current between work materials and 
wire due to high spark strength [19]. It was observed 
that the large increase in MRR is seen from low pulse-
width to high value by enhancing spark strength, as 
shown in Fig. 4 [12]. However, the MRR is increased 
by reducing pulse-interval due to an increase in spark 
ideal time. 
Fig. 2.  Response surface for MRR concerning  
flow rate and current
Fig. 3.  Response surface for MRR concerning  
pulse-width and current
Fig. 4.  Response surface for MRR concerning  
current and pulse-interval

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
326 Sampath, B. – Myilsamy, S.
Table 3.  Lack of fit test for material removal rate model
Source Sum of squares Degree of freedom Mean sum square F-value p-value > F Comments
Linear 2.040 20 0.102 4.383 0.081 Insignificant
2FI 1.513 14 0.108 4.644 0.075 Insignificant
Quadratic 0.215 10 0.022 0.924 0.584 Suggested
Cubic 0.036 2 0.018 0.775 0.520 Aliased
Pure Error 0.093 4 0.023 - - -
Table 4.  Data analysis of material removal rate
Source Sum of squares Degree of freedom Mean square F-value p-value > F Remarks Contribution [%]
Model 54.491 8 6.811 404.036 < 0.0001 Significant 99.39
  Current (C) 29.016 1 29.016 1721.184 < 0.0001 Significant 52.92
  Pulse-width (PW) 13.504 1 13.504 801.052 < 0.0001 Significant 24.63
  Pulse-interval (PI) 7.023 1 7.023 416.571 < 0.0001 Significant 12.81
  Flow rate(F) 3.152 1 3.152 186.962 < 0.0001 Significant 5.75
  C × PW 0.354 1 0.354 21.000 0.0002 Significant 0.65
  C × PI 0.011 1 0.011 0.654 0.4282* Not significant 0.02
  C × F 0.160 1 0.160 9.491 0.0059 Significant 0.29
  C 
2
1.271 1 1.271 75.369 < 0.0001 Significant 2.32
Residual 0.337 20 0.017 - - - -
Lack of fit 0.244 16 0.015 0.656 0.7580 Not significant -
Pure error 0.093 4 0.023 - - - -
Cor total 54.8281 28 - - - - -
Table 5.  Lack of fit test for WWR model
Source Sum of squares Degree of freedom Mean square F-value p-value > F Comments
Linear 0.06 20.00 0.00 4.78 0.070 Insignificant
2FI 0.01 14.00 0.00 0.92 0.601 Insignificant
Quadratic 0.00 10.00 0.00 0.11 0.998 Suggested
Cubic 0.00 2.00 0.00 0.08 0.927 Aliased
Pure Error 0.00 4.00 0.00 - - -
Table 6.  Data analysis of wire wear ratio
Source Sum of squares Degree of freedom Mean square F-value p-value > F Remarks Contribution [%]
Model 0.7747 8.0000 0.0968 411.8384 < 0.0001 Significant 99.40
  Current (C) 0.1160 1.0000 0.1160 493.4670 < 0.0001 Significant 14.89
  Pulse-width (PW) 0.0760 1.0000 0.0760 323.2220 < 0.0001 Significant 9.75
  Pulse-interval (PI) 0.4848 1.0000 0.4848 2061.8105 < 0.0001 Significant 62.20
  Flow rate(F) 0.0424 1.0000 0.0424 180.1662 < 0.0001 Significant 5.44
  C × PW 0.0406 1.0000 0.0406 172.6734 < 0.0001 Significant 5.21
  PW × PI 0.0077 1.0000 0.0077 32.9337 < 0.0001 Significant 0.99
  PI × F 0.0012 1.0000 0.0012 4.9162 0.0384 Significant 0.15
  PI 
2
0.0060 1.0000 0.0060 25.5181 < 0.0001 Significant 0.77
Residual 0.0047 20.0000 0.0002 - 0.60
Lack of fit 0.0023 16.0000 0.0001 0.2360 0.9842 Not significant -
Pure error 0.0024 4.0000 0.0006 - - - -
Cor total 0.7794 28.0000 - - - - -
The minimization of WWR is one of the goals of 
this study. The WWR is minimum at the low value of 
pulse-interval and pulse-width due to fine and soft 
spark in the cutting zone, as shown in Fig. 5. While 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
327 Experimental Investigation of a Cryogenically Cooled Oxygen-mist Near-dry Wire-cut Electrical Discharge Machining Process
the increase in pulse-width, the spark strength is 
significantly increased with material removal rate and 
reduced the WWR. The increase in pulse-interval is 
increasing the WWR due to the high spark pause time 
[5]. Fig. 6 shows the interaction effects of pulse-width 
and current on WWR. While increasing the spark 
current, the WWR value is exploiting due to heave 
spark intensity [20] and [21]. Similarly, the WWR value 
is also slowly increased due to the growing MRR by 
fast flushing debris, as shown in Fig. 7. 
Fig. 5.  Response surface for WWR concerning pulse-width and 
pulse-interval
Fig. 6.  Response surface for WWR concerning pulse-width and 
current
The wire wear ratio has been analysed with 
scanning electron microscopy (SEM) photograph, as 
shown in Fig. 8. It was observed that the wear on the 
wire is linearly along the axis due to the reciprocating 
wire longitudinally. The crater of materials in the 
wire is high at the point ‘P’ due to the sudden supply 
of current to the wire. The path ‘QR’ is sparking 
a portion of the wire, which is in direct with the 
workpiece. The high temperature along the ‘QR’ path 
due to frequent changes of power supply between the 
wire and workpiece causes to increase the wear ratio. 
The path ‘ST’ is a non-spark portion of the wire tool, 
which has the minimum crater of wear. 
Fig. 7.  Response surface for WWR concerning flow rate and pulse-
interval
Fig. 8.  SEM photograph of wire electrode wear
3  MULTI-OBJECTIVE OPTIMIZATION A 
ND VALIDATION OF PREDICTION
In this stage, the combination of experimental 
parameters and their response based on the standard 
ranges defined for the responses are predicted [22]. 
Based on the desirability function, techniques were 
used to predict the best results of both responses. 
This process detects a point that improves the 
desirability function [23]. For validating the developed 
models, some solutions were selected randomly. The 
optimized predicted values of the output responses 
were compared to experimentally obtained values [24]. 
The combination of variables that presents the overall 
optimum desirability (99 %) of response and contour 
plots is displayed in Fig. 8. Considering all the quality 
attributes and using the optimization method with 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
328 Sampath, B. – Myilsamy, S.
Fig. 9.  Comparisons of machining performances between cryogenically cooled near-dry and conventional WEDM
Table 7.  Predicted Results from desirability and validation by confirmation experiments
No C [A] PW [µs] PI [µs] F [ml/min] MRR [mm
3
/min] WWR Description
1 5 25 75 20 10.91 0.59 Desirability Approach
2 5 25 75 20 11.00 0.62 Near-dry WEDM
3 5 25 75 2 litres/min 17.42 0.83 Conventional WEDM 
which the quality parameters were put into standard 
ranges (MRR and WWR), formulation one consisting 
of 25 µs pulse-width, 75 µs pulse-interval, 5 A current, 
and 20 ml/min flow rate was selected as having the 
maximum desirability. The combined optimizing 
responses are predicted as 10.91 mm
3
/min of material 
removal rate, and 0.59 of WWR. 
Confirmation tests were conducted to validate 
the predicted optimum process parameters for best 
MRR and WWR, as shown in Table 7. The multi-op-
timization results were confirmed by the mean ob-
served values of the test. The 5 A current, pulse-width 
25 µs, pulse-interval 75 µs, and 20 ml/min flow rate 
gives 11 mm
3
/min of MRR and 0.62 % of WWR. 
The desirability principles were applied to obtain 
the multi-objective solutions to optimize both respons-
es. It is very useful for machine operators to select the 
best process parameters for minimum WWR and maxi-
mum MRR. These results are used by WEDM ma-
chine manufacturers to fix the best (default) setting for 
cryogenically cooled oxygen-mist near-dry wire-cut 
electrical discharge machining (NDWEDM) process.
4  COMPARISON OF CRYOGENICALLY COOLED  
NEAR-DRY AND CONVENTIONAL WEDM 
The predicted best combinations of input parameters 
were considered for the comparative analysis. In Fig. 
9, the MRR and WWR of cryogenically cooled near-dry 
WEDM are compared with the conventional process. 
The range of input parameters of both processes are 
current 5 A, pulse-width 25 µs, and pulse-interval 75 
µs. The flow rate of oxygen-mist of near-dry WEDM 
is 20 ml/min, and the water flow rate of conventional 
WEDM is 2 l/min. As per the literature, the near-dry 
WEDM is an effective eco-friendly process while 
comparing with conventional WEDM [4], [13] to 
[15]. The MRR of the near-dry WEDM process was 
comparatively lower than the conventional process 
due to the significant flush out of removed material 
from the workpiece. The WWR of the near-dry process 
is lower than conventional WEDM because the heat 
dissipation from the wire is improved by increasing 
the thermal conductivity of the cryogenic cooling wire 
[16]. The minimum WWR promotes the life of reusable 
wire electrode. 
5  CONCLUSIONS
In this research, data were collected from the 
experiments of oxygen-mist cryo-cooled wire near-
dry WEDM were carried out to maintain enough 
temperature in the cutting zone to cut the Inconel 
718 alloy material. The electrical conductivity 
of cryogenically cooled molybdenum wire was 
significantly increased in the near-dry WEDM 
process. It was observed that pulse-width, pulse-
interval, current, and flow rate are significant 
parameters on the material removal rate and wire 
wear ratio. The current and pulse-width are the most 
important factors for material removal rate. Increasing 
the current and pulse-width, the material removal rate 

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
329 Experimental Investigation of a Cryogenically Cooled Oxygen-mist Near-dry Wire-cut Electrical Discharge Machining Process
ϕ    statistical error
R
2
   coefficient of determination
FI   factor interaction
F-value   Values from statistical “F” table
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was increasing and same time decreasing the WWR. 
While increasing pulse-interval from 45 µs to 75 
µs, both the material removal rate and WWR were 
decreased. The WWR has been significantly reduced 
at the dielectric fluid flow rate of 20 ml/min. It was 
observed from the SEM photograph that the wire 
wear rate is linear to the axis, and the wear rate is 
high along the spark path of the wire tool. Thus, the 
optimum process parameters were obtained for the 
cryo-cooled molybdenum wire electrode used in the 
oxygen-mist near-dry wire-cut electrical discharge 
machining process. The desirability technique was 
used to find the best solution among the conflict 
behaviour of MRR and WWR. It was observed that the 
behaviour of the parameters against response variables 
is the same as with the response surface method. The 
current 5 A, pulse-width 25 µs, pulse-interval 75 µs, 
and 1 ml/min flow rate give 10.97 mm
3
/min of MRR 
and 0.59 of WWR. The multi-optimization results 
were validated by the mean observation value of 
confirmation experiments. These results are used by 
manufacturers and operators to fix the best (default) 
setting for the cryogenically cooled oxygen-mist 
NDWEDM process.
In near-dry WEDM, the cryogenically cooling of 
wire significantly contributed to reducing WWR than 
to MRR. While comparing conventional WEDM, the 
WWR of near-dry WEDM was very lower. The lowest 
WWR increases the life of reusable molybdenum wire 
tools. As per the literature, the near-dry WEDM is an 
effective eco-friendly process while comparing with 
conventional WEDM. However, the MRR of near-dry 
WEDM is lower than that of the conventional WEDM 
process.
6  ACKNOWLEDGEMENTS
This research was conducted in the Bannariamman 
Institute of Technology, Erode, Tamilnadu, India. for 
the data collection, and interpretation of results to 
submit the article for publication.
7  NOMENCLATURES
PW   pulse-width, [µs]
PI   pulse-interval, [µs]
C   spark current, [A]
F   flowrate, [ml/s]
MRR  material removal rate [mm
3
/min]
WWR  wire wear ratio [-]
f(x)    Function of ‘x’
x
1
, x
2
, …, x
n
 independent variables
β
0
, β
i
, β
ij
  model coefficients

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)6, 322-330
330 Sampath, B. – Myilsamy, S.
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