BIO Web of Conferences 97, 00034 (2024) https://doi.org/10.

1051/bioconf/20249700034
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Effect of the hollow electrode on the material removal rate of

titanium alloy (grade 1) in the electrochemical machining (ECM)
process
Montadher M. Maktuf , Raed R. Shwaish and Shukry H. Aghdeab

Production Engineering and Metallurgy Department, University of Technology, Baghdad, Iraq

Abstract. This study examined the material removal rate (MRR) affected by the variables of the
electrochemical process including electrode type, voltage, electrolyte type, electrolyte concentration, and
gap. Titanium alloy was employed as the workpiece, while copper was utilized as the cylindrical electrode.
The input parameters were established according to Taguchi's methodology. An analysis of variance
(ANOVA) using a linear regression model was dependent on making sense of the experiment's findings. the
solid electrode achieved the maximum material removal rate (MRR) value (0.0857) g/min, while the hollow
electrode with (1500 l/hour) flow rate achieved the minimum material removal rate (MRR) value (0.00002)
g/min. the material removal rate (MRR) was directly proportional to the voltage. Maximum material
removal rate (MRR) occurred at a concentration of (75 g/l) for the ( ସ ) electrolyte, while minimum
material removal rate (MRR) occurred at a concentration of (50 g/l) for the ( ସ Ž) electrolyte. It has been
observed that the contributing factors in controlling material removal rate (MRR) were as follows; (66.67%)
for the voltage, (5.89%) for the electrode, (5.72%) for the electrolyte concentration, (3.24%) for the type of
electrolyte, and (3.07%) for the gap.

1 Introduction
One of the most well-known alternative production techniques is electrochemical machining (ECM). Between a cathode
tool and an anode workpiece, an electrolyte solution conducts electricity [1][2]. Sparks will emerge due to low working
temperature and must be avoided to prevent the tool wear rate [3] [4]. Since there is no physical contact between the tool
and the workpiece material, neither mechanical nor thermal stresses will be created. The theory of anodic dissolution,
upon which electrochemical machining (ECM) is based, was developed by Michael Faraday (1791-1867) in the nineteenth
century. The aerospace, medical, automotive, gas turbine, electrical, and petroleum industries are only some of the
commercial sectors that make use of the process [2] [5]. Defects like pitting and low surface roughness are often seen in
the ECM of titanium alloy. Moreover, it is simple to create a passivation film during ECM [6] [8].
Milan Kumar, et al (2014), The effect of voltage, gap, electrolyte concentration rate, and tool feed rate on the material
removal rate(MRR) was studied. AISI 202 was used as the workpiece and EN31 tool steel as the electrode. Through
ANOVA analysis, it was concluded that the electrolyte concentration is the most effective factor in the material removal
rate (MRR) [1]. Noor Abd Al-Hassan, et al (2016), The material removal rate (MRR) and the effects of current, electrolyte
content, and gap size were investigated. The workpiece was constructed of stainless steel 316L, while the electrode was
composed of copper. The conclusion is that The material removal rate (MRR) improves when the parameters (current,
electrolyte concentration rate, and gap) are increased. [12]. Heba Saad Qasim, et al (2019) studied the effect of current,
voltage, and concentration of electrolyte on the material removal rate (MRR) was studied. The workpiece that was used
in the experiments was stainless steel 316 H, while the electrode was composed of copper. The paper focused on the effect
of changing the electrolyte on the material removal rate (MRR). It was concluded that the use of (ƒଶ ସ ) as an electrolyte
gives a higher material removal rate (MRR) than the use of (NaCl) as an electrolyte under similar conditions [7]. A.
Parthiban, et al (2019), The researcher studied the impacts of voltage, gap, and concentration of electrolytes on the metal
removal rate. In addition, three different compositions of substance (SiC) were used with different proportions and particle
sizes. It was concluded that changing the composition of the material in terms of the proportion of materials and particle
size is the most effective factor in the material removal rate (MRR) [10]. Bhiksha Gugulothu, et al (2021), experiment
was done on Al5086/Flyash/Sic hybrid metal matrix composites workpiece to find out the effect of voltage, tool feed rate,
and electrolyte concentration on the material removal rate (MRR). It was concluded that the feed rate of the tool is the
most influencing factor on the metal removal rate (MRR) and the applied voltage is the least influencing factor[11]. In
the past, various researchers have attempted process parameter optimization in ECM. M.V.A. Ramakrishna, et al (2021),

Corresponding author: pme.21.70@grad.uotechnology.edu.iq

© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution
License 4.0 (https://creativecommons.org/licenses/by/4.0/).
BIO Web of Conferences 97, 00034 (2024) https://doi.org/10.1051/bioconf/20249700034
ISCKU 2024

The effect of voltage, gap, tool feed rate, and electrolyte flow rate on metal removal rate was investigated. It was found
that the most influencing factor on the metal removal rate is the voltage and feed rate. The workpiece used was (Al 5086
Alloy) and the copper was the electrode. The rate of metal removal increases with a linear increase with the increase in
the applied voltage and increases with a non-linear increase with the increase in the tool feed rate [9].
Previous studies have included several researchers who have assessed the material removal rate (MRR) of various
materials using diverse data. Several individuals used several electrodes composed of diverse materials to quantify the
material removal rate (MRR) of distinct workpieces. As of now, no research has been conducted to examine the impact
of hollow electrodes with different flow rates on the material removal rate (MRR) of titanium alloy during the ECM
process. The originality in this study stems from the use of a hollow electrode with different flow rates in the
electrochemical operation process. The use of titanium alloy in this study is also considered part of the originality of the
research.
This work aims to examine the possibility of operating titanium alloys, which are considered to be materials that have
weak electrical conductivity, on electrochemical machining using three different electrodes, and then Study the influence
of five machining variables (electrode, voltage, type of electrolyte, concentration of electrolyte, and the gap) on the
material removal rate (MRR) in the electrochemical machining (ECM) of titanium workpiece with the copper electrodes
and finding the best results.

(a) ECM components. (b) ECM machine.

Fig. 1. Electrochemical machines component

2 Experimental Work

2.1 Workpiece
Figure (2) displays a workpiece made of titanium alloy (grade 1) with dimensions of 500 × 350 × 20 mm and a thickness
of 2 mm. The WJM method was used to divide it into 27 pieces, each measuring (20 × 20) mm. The chemical
composition of the titanium alloy is presented in Table (1) as percentages. The table (2) presents the mechanical and
physical characteristics of a titanium alloy plate (Grade 1). The mechanical and physical properties of the electrode and
the workpiece were obtained through tests conducted at the Ministry of Science and Technology, Iraq, Baghdad.

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Fig. 2. Workpiece before cutting.

Table 1. Titanium alloy (grade 1) chemical composition.
Elements Ti % Fe % C% N% H% O%

Results 99.64 0.18 0.08 0.03 0.01 0.06

Table 2. The mechanical and physical properties of titanium alloy plate (Grade 1).
NO. Property value NO. Property Value

1 Hardness (HRC) 65 5 Thermal conductivity 21

(w/m.k)
2 Yield strength 182 6 Electric resistivity 41.7
(MPa) (Ω.m)
3 Tensile strength 539 7 Density (g/ܿ݉ଷ ) 4.51
(MPa)
4 Elongation (%) 25 8 Melting point (Ԩ) 1668േ4

2.2 Tool

The experiment utilized three copper electrodes, a solid electrode, a hollow electrode (H1) with a flow rate of 1000 l/hour,
and a hollow electrode (H2) with a flow rate of 1500 l/hour. A solid electrode with a diameter of 16mm and a length of
150mm was created shown in figure (3). The hollow electrode was fabricated with a 16 mm outer diameter, 8 mm inner
diameter, and 150 mm length, as depicted in Figure (4).

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Fig. 3. Solid electrode copper.

Fig. 4. Hollow electrode copper.

3 Design Of Experiments
The Taguchi technique is one of the most important tools used to study engineering analysis. To get to the data and do
the process, the information must first be assembled logically. The focus is on its benefits since this technique saves time,
cost, and effort when it comes to experimenting. With the help of the quality loss function hierarchy and Taguchi's
techniques, great organizational designs can be made. Taguchi's technique was used with the statistical analysis software
Minitab 20. For this purpose, table (5-1) shows the ECM variables with five factors and three levels and the results of
material removal rate (MRR). In this work, the experiments were done with the L27 orthogonal array (OA). Analysis of
the variance (ANOVA) was used to find out how the most important levels 1,2, and 3 variables affect the performance
variable.

Table 3. Experimental impact of the variables on MRR that was designed in the Taguchi technique.

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NO. of Electrode Voltage (V) Electrolyte Type Electrolyte weight Gap
EXP. (g) (mm)

1 S 10 NaCl 25 0.1
2 S 10 NaCl 25 0.3
3 S 10 NaCl 25 0.5
4 S 20 KCl 50 0.1
5 S 20 KCl 50 0.3
6 S 20 KCl 50 0.5
7 S 30  ସ Ž 75 0.1
8 S 30  ସ Ž 75 0.3
9 S 30  ସ Ž 75 0.5
10 H1 10 KCl 75 0.5
11 H1 10 KCl 75 0.1
12 H1 10 KCl 75 0.3
13 H1 20  ସ Ž 25 0.5
14 H1 20  ସ Ž 25 0.1
15 H1 20  ସ Ž 25 0.3
16 H1 30 NaCl 50 0.5
17 H1 30 NaCl 50 0.1
18 H1 30 NaCl 50 0.3
19 H2 10  ସ Ž 50 0.3
20 H2 10  ସ Ž 50 0.5
21 H2 10  ସ Ž 50 0.1
22 H2 20 NaCl 75 0.3
23 H2 20 NaCl 75 0.5
24 H2 20 NaCl 75 0.1
25 H2 30 KCl 25 0.3
26 H2 30 KCl 25 0.5
27 H2 30 KCl 25 0.1

4 Result And Discussion

As shown in Table (3), five variables were used in this investigation at three levels: the concentration of electrolyte (25,
50, and 75 g/l), the type of electrolyte (NaCl, KCl, and  ସ Cl), the gap (0.1, 0.2, and 0.3)mm, and the electrodes (solid
electrode, hollow electrode (H1) with flow rate 1000 l/hour, and hollow electrode (H2) with flow rate 1500 l/hour). The
variables displayed in Table (3) were created using the Taguchi Technique. Table (4) displays the experimental and
predicted results for a titanium alloy (grade 1) workpiece under the given conditions. Software called Minitab 20 was
utilized for the MRR analysis. To evaluate the precision of the previously mentioned equations, The equations (1) were
utilized to determine the predicted values of MRR. The developed model has demonstrated satisfactory prediction
accuracy. As well as Figures (5) display the comparison between the observed and predicted.
Table 4. Input variables and their levels.
NO. Variables Units Level 1 Level 2 Level 3

1 Electrode _ S H1 H2

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2 Voltage V 10 20 30

3 Concentration g/l 25 50 75

4 Electrolyte type _ NaCl KCl ܰ‫ܪ‬ସ Cl

5 Gap mm 0.1 0.3 0.5

Table 5. Experimental and predicted impact of the variables on MRR that was designed in the Taguchi technique.
NO. Electrode Voltage Electrolyte Electrolyte Gap EXP. MRR Pred. MRR
(V) Type weight(g/l) (mm) (g/min) (g/min)
1 S 10 NaCl 25 0.1 0.00004 0.0032
2 S 10 NaCl 25 0.3 0.00003 0.0012
3 S 10 NaCl 25 0.5 0.000023 0.0018
4 S 20 KCl 50 0.1 0.01264 0.0131
5 S 20 KCl 50 0.3 0.009 0.0086
6 S 20 KCl 50 0.5 0.0083 0.0081
7 S 30  ସ Ž 75 0.1 0.0857 0.0599
8 S 30  ସ Ž 75 0.3 0.0546 0.0554
9 S 30  ସ Ž 75 0.5 0.03 0.0549
10 H1 10 KCl 75 0.5 0.000027 0.0032
11 H1 10 KCl 75 0.1 0.00003 0.0012
12 H1 10- KCl 75 0.3 0.000021 0.0018
13 H1 20  ସ Ž 25 0.5 0.0055 0.0072
14 H1 20  ସ Ž 25 0.1 0.0043 0.0027
15 H1 20  ସ Ž 25 0.3 0.00223 0.0021
16 H1 30 NaCl 50 0.5 0.0449 0.0408
17 H1 30 NaCl 50 0.1 0.0348 0.0363
18 H1 30 NaCl 50 0.3 0.0331 0.0357
19 H2 10  ସ Ž 50 0.3 0.000013 0.0032
20 H2 10  ସ Ž 50 0.5 0.00002 0.0012
21 H2 10  ସ Ž 50 0.1 0.000066 0.0018
22 H2 20 NaCl 75 0.3 0.0086 0.0103
23 H2 20 NaCl 75 0.5 0.00346 0.0058
24 H2 20 NaCl 75 0.1 0.0092 0.0052
25 H2 30 KCl 25 0.3 0.01 0.0263
26 H2 30 KCl 25 0.5 0.0207 0.0218
27 H2 30 KCl 25 0.1 0.03866 0.0212

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dLJƉĞŽĨĞůĞĐƚƌŽĚĞ

Fig. 5. Experimental and Predicted values of MRR for ECM process.

5 Measurement Of Material Removal Rate (Mrr)

The material removal rate (MRR) can be described as the ratio of the change in weight of the machined item before and
after machining to the material and machining time. The weight of the workpiece was determined using a high-accuracy
weight balance that has a range of (0.01-220) g and the accuracy of this device is (±0.0003) as shown in Figure 6. Equation
1 shows the calculation of the (MRR).
MRR = (wb-wa)/MT (g/min) …… (1)
MRR = material removal rate.
Wb = weight of the workpiece before machining (g).
Wa = weight of the workpiece after machining (g).
MT =machining time (min).

Fig. 6. Balance device.

6 The Effect Of Machining Parameters On Material Removal Rate (Mrr):

The results of surface roughness at different electrodes, voltage, the weight of electrolyte, type of electrolyte, and gap
values are given in Table (4).

Figure (6), the material removal rate (MRR) in a solid electrode rises between (0.00002 -0.0857) g/min, with a mean
MRR of (0.02227) g/min. Additionally, the MRR increases (0.00002-0.0449) g/min with the mean of MRR (0.0138)
g/min in a hollow electrode with a flow rate of 1000 l/hour. Additionally, the MRR increases (0.00001-0.0386) g/min
with the mean of MRR (0.01) g/min in a hollow electrode with a flow rate of 1500 l/hour. It can be explained that
increasing the flow rate may lead to a turbulent flow of electrolytes and may cause damage to the (MRR).
Also, it can be seen that the voltage is directly proportional to (MRR). Regarding the electrolyte, the material removal
rate increase occurred with ammonia chloride compared to sodium chloride and potassium chloride. Also, the increase in

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electrolyte concentration (25-75) g/l leads to a rise in the material removal rate (MRR). This can be explained because
ammonia chloride achieves the maximum dissolution rate for the workpiece, and the increase in electrolyte concentration
leads to faster chip removal due to increased electrical conductivity.
As shown in Figure (6), the gap is inversely proportional to the MRR, as the MRR decreases as the gap increases from
(0.1-0.5) mm.

Fig. 7. Main effects plot for material removal rate (MRR).

7 Analysis Of Variance (Anova)

The analysis of variance (ANOVA) results are shown in Table (5) along with the sources of the variation, degree of
freedom (DF), total sum of the squares (Adj SS), average square (Adj MS), F-value, which shows which variables
contribute to the output, P-values that are below 0.05, which are considered to be significant, and P-values that are more
than 0.05, which are not important. The material removal rate was the subject of an analysis of variance (ANOVA), which
took into consideration the details listed in the table.

Table 6. ANOVA table for MRR for machining variables.

Source DF Adj SS Adj MS F-Value P-Value
Electrode 2 0.000699 0.000349 2.86 0.087
Voltage 2 0.007844 0.003922 32.08 0.000
Electrolyte 2 0.000388 0.000194 1.59 0.235
type
Weight of 2 0.000679 0.000339 2.78 0.092
electrolyte
Gap 2 0.000140 0.000070 0.57 0.576
Error 16 0.001956 0.000122
Total 26 0.011704

8 Regression Model
Coefficients were employed to build the mathematical model, and then regression equations for process variables were
used to create a mathematical connection between the input variables and material removal rate to correlate MRR. This
enabled us to assess the Surface Roughness Model's level of regression. This was done to evaluate the level of regression
in the material removal rate Model. According to the equations for regression, equation (1) presents the regression formula
of MRR of process parameters.

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MRR= 03.601+0.498 S-0.754 H1+0.256 H2 - 2.970 V10+1.129 V20 + 1.840 V30 - 0.168 NaCl-0.172 KCl+0.340
ܰ‫ܪ‬ସ ‫݈ܥ‬-0.286 W25-0.603 W50 +0.889 W75-0.081 G0.1+0.107 G0.3-0.026 G0.5 … (1)

9 Model Summary
The statistics that compare the different models in terms of how well they fit the data are shown in the model summary
that shows in Table (6). The R-Square (R-Sq) value is the amount of variation in the observed outputs that can be assigned
to the model. An R-square that has been altered to take into account the number of terms in the model is referred to as
"adjusted R-square" (R-Sq (adj)). The ability of the model to predict brand-new data is shown by the R-square that was
predicted, also known as R-sq (pred). R-square (R-sq) and adjusted R-square (R-sq (adj)) values that are higher than those
that are lower indicate a better match. The table gives information on the models for material removal rate.

Table 7. Definition of model MRR.

S R-sq R-sq(adj) R-sq(pred)
0.0110566 83.29% 72.84% 52.41%

10 Conclusion
This study investigated the impact of material removal rate (MRR) on various input variables of the electrochemical
process, such as electrode type, voltage, electrolyte type, electrolyte concentration, and gap. The workpiece in this
process was made of titanium alloy, while copper was used as the electrode. The input parameters were determined
based on Taguchi's methodology. The experiment's findings were interpreted using both analysis of variance (ANOVA)
and a linear regression model. Decisions can be made based on the aforementioned experimental findings that have been
evaluated.
1- The maximum value of the material removal rate is (0.0857) g/min, while the minimum material removal rate
value was (0.00002) g/min.
2- The maximum material removal rate (MRR) value was obtained when using a solid electrode and the
minimum material removal rate (MRR) value was obtained when using a hollow electrode (H2) with a flow
ratio of 1500 l/hour.
3- Increasing the voltage leads to an increase in material removal rate ( MRR).
4- Maximum material removal rate (MRR) occurs at a (75) g/l concentration of (ܰ‫ܪ‬ସ ‫ )݈ܥ‬electrolyte, and minimal
surface roughness is achieved at a (50) g/l concentration of ( ସ Ž) electrolyte.
5- It has been observed that voltage is the most effective or contributing factor in controlling MRR, with a
percentage contribution of (66.67%). While the electrode (having a percentage contribution of 5.89%), the type
of electrolyte (having a percentage contribution of 3.24%), and the electrolyte concentration (having a
percentage contribution of 5.72%). While the gap has a minimum percentage contribution of 3.07%

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