Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400 Received for review: 2023-01-05
© 2023 The Authors. CC BY 4.0 Int. Licensee: SV-JME Received revised form: 2023-05-04
DOI:10.5545/sv-jme.2023.518 Original Scientific Paper Accepted for publication: 2023-05-30
*Corr. Author’s Address: The Kavery Engineering College, Department of Mechanical Engineering, India, jamunaelagandhi@gmail.com 388
Mechanical and Microstructural Properties of B
4
C/W Reinforced 
Copper Matrix Composite Using a Friction Stir-Welding Process
Elangandhi, J. – Periyagounder, S. – Selavaraj, M. – Saminatharaja, D.
Jamuna Elangandhi
1
 – Suresh Periyagounder
2
 – Mahalingam Selavaraj
3
 – Duraisivam Saminatharaja
1
1
The Kavery Engineering College, Department of Mechanical Engineering, India 
2
Sona College of Technology (Autonomous), Department of Mechatronics Engineering, India 
2
Sona College of Technology (Autonomous), Department of Mechanical Engineering, India
Copper metal matrix composites (CMC) are broadly employed in various applications in the fields of space, aviation, automobile and 
electronics industries. The welding of CMC in using conventional methods is very difficult and expensive due to its crystallographic nature. 
Friction stir welding (FSW) is a more prominent and reliable technique for welding than conventional methods. Therefore, this work is based on 
work with CMC material, which is prepared with a stir-casting technique. Pure copper (Cu) is reinforced with tungsten (W) and boron carbide 
(B
4
C) particles in different combinations and welded using the FSW process to study the mechanical and micro-structural properties. Multi-
objective decision-making methods, such as the technique for order preference by similarity to ideal solution (TOPSIS) and grey relational 
analysis (GRA) are used to find optimal parameter combination. The experiments are planned according to the L 18 orthogonal array (OA) 
using the most influential parameters, such as reinforcement the percentage of B
4
C, tool rotational speed, welding speed, and axial force. 
The performance of outcomes is measured based on the responses such as tensile strength, hardness, and impact strength of the weld joint. 
Based on the results 15 % of B
4
C reinforcement, 900 RPM rotational speed, 15 mm/min welding speed and 6 kN axial forces are optimal for 
better mechanical strength in the welding with TOPSIS and GRA techniques. Additionally, scanning electron microscopic image (SEM) analyses 
were carried out for better understanding of weldments’ microstructure changes. 
Keywords: friction stir welding, copper, metal matrix composite, boron carbide
Highlights
• 	 The CMC materials were produced by the friction stir process and contain pure copper (Cu) as matrix and tungsten (W) and 
boron carbide (B
4
C) as reinforcing material in different concentrations.
• 	 Based on experiments with an L-18 orthogonal array (OA), friction stir welding is used to join the CMC cast using parameters 
such as the percentage of boron carbide reinforcements, tool rotation speed, welding speed and axial force.
• 	 The TOPSIS and GRA techniques are used to determine the optimum combination of parameters.
• 	 The results of the optimisation show that the mechanical strength when welding with the FSW technique increases with the 
increase of the reinforcement percentage in the copper composite.
0  INTRODUCTION
Extensive research attempt has been conducted 
regarding the FSW process due to its enormous 
advantages over traditional welding techniques. The 
FSW process is the most significant and desirable 
technique in solid-state welding because it is crack-
free, fume-free, has less shrinkage and excellent 
mechanical strength, etc. Also, FSW finds a broad 
range of utilization in various sectors, such as 
construction, marine, aircraft, trains, automobile 
industries and fuel tanks to obtain quality welding 
of various parts. Although FSW has many reliable 
features, due to technological growth, it creates 
new challenges and problems, such as micro-
bores, nonhomogeneous welding surfaces, high 
heat-affected zones, and less mechanical strength 
of welding. Nevertheless, the needs for CMC in 
various applications are increasing day by day in the 
manufacturing sector. Therefore, in view of improving 
the welding quality of the composite materials, 
various research attempts have been made in the last 
decade worldwide. 
Zamani et al. [1] carried out experiments with the 
FSW process on aluminium silicon composite work 
material and optimized the process parameters using 
an RSM technique. They planned the design of 
experiment including the transverse speed of tool and 
suggested that the optimal process parameter 
combination was 1300 rpm rotational speed and 70  
m/min transverse speed. Moreover, the effect of 
coupling process parameters increases the machining 
rate significantly. Argesi et al. [2] attempted to join a 
pure copper and aluminium alloy with SiC particles in 
the FSW process. They noted that 50 m/min of 
welding speed and 1000 rpm of rotational speed 
produced higher tensile strength. The application of 
SiC particle increases the hardness of welding strength 
from 160 HV to 320 HV. Sudhagar and Gopal [3] 
carried out experiments with FSW to fabricate the 
surface copper composite using Si
3
N
4
-reinforced 
particles in various concentration levels. They 

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
389 Mechanical and Microstructural Properties of B4C/W Reinforced Copper Matrix Composite Using a Friction Stir-Welding Process
analysed the mechanical and microstructure properties 
of the weld and also observed that while rotating the 
tool work piece reached recrystallization temperature, 
which significantly hinders the micro-hardness of 
welding. The wear property increases with increased 
reinforcement particles over the surface copper 
composite by about 15 %. Thapliyal and Mishra [4] 
utilized the machine-learning concept to weld the 
copper work material in the FSW process. The most 
influential parameters (i.e., welding speed, rotational 
speed and axial forces) are considered for the 
experiment. They noted a 94 % improved welding 
strength using this optimal combination among 119 
experiments. Harisha et al. [5] welded the copper and 
aluminium 6083 using the FSW process to study the 
optimal process parameter combination. They noted a 
70 % improved tensile strength in the parameter 
combination, such as a rotational speed of 1000 rpm 
and a welding speed of 50 m/min. Nagesh et al. [6] 
welded dissimilar materials, such as copper and brass, 
using the FSW process. They compared the results of 
FSW, such as tensile, hardness, and the impact 
strength of dissimilar welding strength with parent 
metal welding, to explore the detailed nature of 
welding. Senthil et al. [7] studied the FSW process 
parameters for aluminium 6063 composites using the 
response surface methodology (RSM) method. They 
noted the tensile and yield strength of 167 MPa and 
145 MPa, respectively, in the parameter value of 1986 
rpm of tool speed. Uniform microstructure properties 
were also noted with the first optimal parameter 
combination. Karrar et al. [8] studied the effect of 
tools’ rotational and transverse speeds on dissimilar 
welding in the FSW process. They welded the 
aluminium alloy 5083 and copper as work material 
and observed intricate microstructure in the heat-
affected zone. Many intermetallic mixers were seen in 
the welding zone, which leads to nonhomogeneous 
micro-hardness. The maximum tensile strength was 
obtained in 1400 rpm tool speed and 120 mm/min. 
Kolnes et al. [9] prepared a tool for machining 
materials such as aluminium, copper, and stainless 
steel, using TiC, and WC-Co-based ceramic composite 
in the FSW process. The composites are fabricated 
with a powder metallurgy technique, which prevents 
the damage caused by the temperature developed 
through friction. They noted that 80 % of the TiC-
mixed composite electrode produces a fine machining 
surface in the aluminium work material. Sahu et al. 
[10] investigated the FSW welding characteristics for 
magnesium work materials. During the welding 
process, Zn materials are added to improve the 
welding quality. Also, the addition of Zn with work 
materials forms an MgZn alloy, which produces high 
wear strength. Jimenez-Mena et al. [11] attempted a 
dissimilar weld with materials (e.g., aluminium, steel) 
using the FSW process. They reported that 
interlayering of the work material increases when 
increasing the load application on the work material. 
Also, the presence of Co in steel increased the 
toughness of weld and propagated cracks in the 
aluminium plate. Garg and Bhattacharya [12] carried 
the welding on aluminium alloys such as 6061 and 
7075 using the FSW process. They investigated the 
mechanical characteristics such as tensile, flexural, 
and fracture strength of the welding. Copper particles 
are used during the welding as interference, and 2 mm 
tool pin is employed in the tool shoulder. Souza et al. 
[13] carried out experiments in Al-Ce-Si-Mg 
aluminium alloy using the FSW process. The 
maximum tensile stress (102 MPa) noted with lesser 
tool rotational speed using a triangular pin profile 
surface and higher micro-hardness found at higher 
rotational speed. Shettigar et al. [14] conducted the 
experiments in rutile-reinforced aluminium alloy 6061 
composite using the FSW process. They planned the 
experiments with tool, welding speed, and various 
tool profiles shapes in order to obtain better machining 
quality. They conducted the experiment so that 
rotational, transverse speed contributed more to 
welding accuracy and homogeneous reinforcement 
distribution among the welding surface. 
Khojastehnezhad and Pourasl [15] welded the 
aluminium alloy 6061 with copper through FSW 
process along with copper particles. They noted 
defect-less welding in the rotational speed of 950 rpm 
and 50 mm/min welding speed. The observation 
shows the welded composite at the edge has higher 
hardness due to the aluminum and copper bonding. 
Babu et al. [16] investigated the optimal process 
parameter for aluminium alloy 2219 with the FSW 
process to obtain a defect-free machining surface. 
They used a genetic algorithm to find the possible 
parameter combination and suggested that a 1005 rpm 
tool speed at 3º tool angle produces excellent 
machining performance. This optimization technique 
diminishes the machining cost significantly due the 
shorter machining time. Peddavarapu et al. [17] 
prepared the composite using Al-4.5Cu based alloy 
and reinforced it with TiB2 particles; this was 
employed as a work material to study the performance 
of the FSW process. Normal treaded profile tool was 
used as tool. They mentioned that uneven material 
flow, which produces an uneven circumference in the 
welding. Herbert et al. [18] conducted the experiments 
in a Cu- and SiC-reinforced aluminium metal matrix 

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
390 Elangandhi, J. – Periyagounder, S. – Selavaraj, M. – Saminatharaja, D.
composite, prepared with the stir-casting method and 
employed in the FSW process to find the optimal 
welding range of parameters. They used the combined 
tool profiles (e.g. square and treaded) on the welding 
and analysed the mechanical and microstructure 
properties of welding. The hardness of the welding is 
higher than that of the base metal. Sahu et al. [19] 
optimized the process parameters of FSW using a 
fuzzy logic grey analysis method for aluminium and 
copper welding. They considered the major process 
parameters, such as tool, welding speed, depth of weld 
and shape of tool pin. The microstructures of both 
sides of the metals have fewer defects due to the 
optimal solution of welding. Ahmadkhaniha et al. [20] 
carried out the experiments in the FSW process with 
pure magnesium to find the optimal process parameter 
combination. They applied the L9 OA and analysed 
the effect of all parameter combination using the 
Taguchi method. The harness of magnesium increases 
with increased tool speed. Shirazi et al. [21] examined 
the influences of tool and welding speed on the 
welding strength of aluminium alloy 5456 via the 
through FSW process. They reported the findings, 
which showed that, in addition to the optimum 
parameter, the remaining combinations have a 
substantial impact on the welding quality. Kumar et al. 
[22] experimented with aluminium and copper-based 
composite on the FSW process under various 
machining speeds and welding speeds. They noted 
fewer defects with the welding speed in the range of 
70 mm/min to 100 mm/min. They also suggest that 
the microstructure of welding was significantly 
influenced by the welding and rotational speeds. 
Suresh et al. [23] studied the influences of various 
process parameters on the mechanical and 
microstructure properties of FSW on aluminium alloy 
2219 work material using an RSM technique, which 
was employed to obtain maximum mechanical 
strength. They found the optimal process parameter 
combination of1627 rpm rotation speed, 083 mm/s 
welding speed, and 12.2 kN axial force.
The aforementioned sources were used to explore 
the optimal solution of FSW process parameters 
for various aspects, such as aluminium-based 
composites, copper-reinforced work surfaces, varying 
concentrations reinforcing particles, and the joining of 
copper to other metals, such as aluminium, stainless 
steel, titanium, etc. However, experiments with the 
copper-based composites and their optimization in the 
literature are rare [24] to [26] and there is no evidence 
of hybrid CMC in FSW process. The optimization 
of the process parameters for every machine is 
done carefully to achieve the right output without 
taking major effort. Additionally, optimised values 
generate high accuracy and reduce unneeded time 
and cost for quality. In line with that, the TOPSIS 
and GRA methods are very prominent techniques that 
are successfully employed in other manufacturing 
sectors to reveal the optimal solution [27] to [30]. 
The reinforcement materials, such as W and B
4
C 
particles, provides excellent mechanical strength, 
thermal stability, and high affinity nature with other 
materials. Therefore, in this experiment work, 
material is fabricated with the stir-casting method 
using commercially available pure copper (Cu) as the 
matrix and W and B
4
C particles as reinforcements in 
various concentration levels. Based on L18 OA and 
major influencing parameters, such as the percentage 
of reinforcements, rotational speed, welding speed, 
and axial force are used to conduct experiments. The 
process parameters of FSW are also optimized using 
simple and prominent techniques, such as TOPSIS 
and GRA. Furthermore, SEM analyses are carried out 
on the welding surface to give better understanding of 
microstructure. 
1  EXPERIMENTAL WORK
Commercially available pure copper is considered 
as the base material, W (30µm), B
4
C (50 µm) are 
employed as reinforcements, and three different CMC 
materials are fabricated using a stir-casting furnace 
as shown in Fig. 1. An indigenously created bottom-
pouring and electric-stir casting furnace is employed to 
develop the composite. The Cu rods (25 mm diameter) 
are cleaned thoroughly and cut into small pieces 10 
mm thick. The rods are loaded into a crucible cylinder 
that is coated with stainless steel and the temperature 
is maintained at 1200 ºC during the melting process. 
The molten Cu is stirred well using a stir setup that 
enhances the distribution of reinforcements uniformly 
throughout the composite. Stainless steel coating 
is carried out in the stirrer and crucible, which 
protects the unwanted material amalgamation with 
CMC. The preset volume of preheated W and B
4
C 
particles is mixed with the molten copper to enhance 
the wet ability and mechanical strength with copper 
material. The weight percentages of reinforcement 
and composition of composite are displayed in Table 
1. The well-mixed molten metal is poured into a die 
(100 mm × 100 mm × 6 mm) to obtain the hybrid 
composite.
The fabricated CMC plates are employed to 
study the weldability using the FSW process. The 
CMC work material in the plate is fastened with a 
customized vertical milling machine for the FSW 

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
391 Mechanical and Microstructural Properties of B4C/W Reinforced Copper Matrix Composite Using a Friction Stir-Welding Process
process. The work plates are arranged in a butt joint 
design, and the tool is fixed with the tool holder 
against the workpiece, as shown in Fig. 1. 
Fig. 1.  Friction stir process; a) casting furnace, and  
b) casting die with molten CMC
The non-consumable tool used in the experiment 
is made of Tungsten carbide with a shoulder diameter 
of 18 mm. The tool is designed with a hexagon-shape 
pined with length and diameter of 6 mm and 4 mm, 
respectively, for the purpose of stirring the work 
material, as presented in Fig. 2. The rotating tool 
is plunged over the work material and allowed to 
rest for 20 seconds to retain its normal temperature. 
Afterwards, the tool moves over the work material 
along its length to the weld. Due to the high friction 
between the tool and electrode, heat is induced, which 
makes the work materials soften. The shoulder pin of 
the tool blends the softened work material by moving 
it from retreating portion to other side which produces 
a sound weld joint. In this technique, work materials 
welded using both heat and mechanical energy but 
in traditional fusion welding only heat energy is 
employed to weld the metals. The percentage of 
reinforcements, tool rational speed, welding speed 
and axial forces influence the welding nature of FSW 
process. Therefore, these parameters are considered 
to be input controlling factors. L 18 OA is employed 
to investigate the process parameter over the output 
responses. The excellence of welding is evaluated by 
performing different mechanical and micro-structural 
testing, including for tensile, impact and hardness. The 
work materials are sliced into the standard dimensions 
according to ASTM standard through wire cut EDM. 
Based on the ASTM E8 standard, test samples are 
fabricated. Two specimens are cut from every welding 
specimen and two output responses obtained, which 
are averaged and considered in order to assess the 
welding quality. Tables 2 and 3 present the initial 
parameter levels and design of experiments with 
output responses respectively, which are considered 
based on the literature [3]. The micro-hardness of 
welding is measured using a Vickers hardness testing 
machine (TE-JINANWDW100, Jinan Test Machine 
Co. Ltd., China) at different places of welding cross-
sections, and average hardness values are considered 
for evolution. ASTM E23-16a standards are followed 
to evaluate the impact strength of welding, and a 
V-notch has been created in welding specimen at right 
angles to the welding joint.
Fig. 2.  Friction stir welding; a) experimental setup, b) tool,  
and c) work piece 
Table 1.  Composition of CMC 
Plate 
No.
Symbol
Copper 
(Cu)
Tungsten 
(W)
Boron carbide 
(B
4
C)
1 90 % CMC 90 5 5
2 85 % CMC 85 5 10
3 80 % CMC 80 5 15
Table 2.  Input parameter and its levels
Specimen 
No.
Parameter Units
Levels 
L 1 L 2 L 3 
1 Weight % of B
4
C % 5 10 15
2 Rotational speed rpm 900 1200 1500
3 Welding speed mm/min 9 12 15
4 Axial force kN 3 6 9

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
392 Elangandhi, J. – Periyagounder, S. – Selavaraj, M. – Saminatharaja, D.
1.1  Multi Objective Optimization Techniques TOPSIS:
TOPSIS is a popular and very powerful technique 
to separate the correct parametric mixture from the 
restricted investigated combination. The steps for this 
technique are scheduled below. [27]
Step 1: The conclusion matrix having ‘n’ 
characteristics and ‘m’ option and it is characterized 
in Eq. (1).
 A
m
n
mm mn
n
JJ J
JJ J
JJ J













11 12 1
21 22
12
2


 

, (1)
where J
ij
 is the output of i
th 
option with relevance to 
the j
th 
characteristic.
Step 2: The normalization of the matrix is carried 
out with Eq. (2). 
 p
J
J
jn
ij
ij
i
m
ij
 


1
2
12 ,, ,, . (2)
Step 3: For each output, responses have been 
assigned with equal weights to be Wt
j
 (j = 1, 2, …, n). 
The standardized weighted choice matrix M = [m
ij
] 
attained using the Eq. (3).
 M = Wt
j
 p
ij
,  (3)
where 
j
n
j
Wt



1
1.
Step 4: The suitable best solution is assessed 
using Eq. (4) and the worst solution is attained using 
Eq. (5).
Mm jJ mjJj m
mm m
i
ij
i
ij
n



  

 


maxm in
|, || ,...,
,, ..,
1
12
 

,( ) 4
Mm jJ mjJj m
mm
i
ij
i
ij



  

 


minm ax
|, || ,...,
,, ....,
1
12
m m
n


.( ) 5
Step 5: The distributions among every option are 
intended from the best solutions are obtained using 
Eq. (6).
 TM mi m
i
j
n
ij j







1
2
12 ,, ,..., . (6)
The division of option from the worst solution is 
attained using Eq. (7).
 TM mi m
i
j
n
ij j







1
2
12 ,, ,..., . (7)
Step 6: The relations closeness of the dissimilar 
options for the solutions are obtained using Eq. (8).
 k
k
kk
im
i
i
ii





,, ,..., . 12 (8)
Table 3.  Design of experiment and output responses 
Experiment No. Weight % of B
4
C Rotational speed Welding speed Axial force
Hardness 
[HV10]
Tensile strength 
[N/mm
2
] 
Impact 
toughness [J]
1 5 900 9 3 83 19.25 3.3
2 5 1200 12 6 91 0.03 3.1
3 5 1500 15 9 45 21.45 3.5
4 10 900 12 9 128 75.455 4.1
5 10 1200 15 3 112 77.75 4.0
6 10 1500 9 6 119 63.821 4.2
7 15 900 15 6 157 22.444 3.9
8 15 1200 9 9 85 136.02 4.0
9 15 1500 12 3 100 153.93 3.8
10 5 900 15 9 82 23.25 2.9
11 5 1200 12 3 89 32.51 3.7
12 5 1500 9 6 59 38.24 3.2
13 10 900 9 9 119 68.25 3.9
14 10 1200 15 3 101 82.57 4.5
15 10 1500 12 6 117 38.14 4.2
16 15 900 15 6 148 120.48 4.5
17 15 1200 12 9 95 125.65 4.2
18 15 1500 9 3 113 148.37 4.9

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
393 Mechanical and Microstructural Properties of B4C/W Reinforced Copper Matrix Composite Using a Friction Stir-Welding Process
Step 7: The k
i 
standards values are graded in 
downward order to discover the optimal parameters 
mixture. 
1.2  Grey Relational Analysis Technique
In GRA, output reactions of different elements should 
be reformed into the dimensionless values. Therefore, 
those values are standardized to the variety of zero to 
one using Eqs. (9) to (12) [28]. The tensile, impact, 
and micro-hardness values must be higher, which 
considered better and intended using the Eq. (9); for 
lower, the superior is desirable, which is intended 
using Eq. (10).
 Rs
rs rs
rs rs
i
ii
ii
*
min
maxm in
,  
  
  
 (9)
 rs
rs rs
rs rs
i
ii
ii
*
max
maxm in
,  
  
  
 (10)
where i = 1, ,2, …, m, s = 1, 2, …, n, where m is the sum 
of experiment, n is the sum of the observed data. 
Rs
rs rs
rs rs
i
ii
ii
*
min
maxm in
,  
  
  
 is denoted as minimum - larger than beter and  
rs
rs rs
rs rs
i
ii
ii
*
max
maxm in
,  
  
  
 as maximum - smaller the better. The 
standardized values are added in Eq. (11), which is 
employed to compute the grey relational coefficient 
(GRC).
 
i
oi
S
P
 

 


minm ax
max
£
£
. (11)
Here, 
oi
S  divergence series is attained from 
the orientation series 
0
*
S 
 and comparability series 

i
S
*

. The variety 0 ≤ £ ≤ 1 comprised for the 
distinctive coefficient:
 
¥£ .  


1
1
n
S
P
n
i
 (12)
Grey relational grade ( ¥
i
) is added, summing up 
of grey relational coefficients which corresponds in 
Eq. (12). is assisted to discover the connection of 
situation and comparability ideals.
2  RESULTS AND DISCUSSION
2.1  Effect of Reinforcements on the Microstructure of 
Welding 
SEM is employed to investigate the microstructural 
properties of the welding joints. The macro-size 
welding images of various reinforced specimens 
under different machining conditions are analysed. 
The microstructure of the welding zone and the parent 
metal of the welding using various reinforced work 
materials (e.g., 90 % CMC, 85 % CMC and 80 % 
CMC) are presented in Figs. 3 to 5. The consistency 
of welding joint on all sides of the parent metal is 
found to be better in 80 % CMC materials than other 
reinforced work materials and lesser regularity found 
in 90 % CMC material. The microstructures of welding 
zone for all type of reinforced materials are analysed 
using SEM images. The SEM analysis shows that 
the dissemination of grains due to high temperatures 
enlarges the welding zone on the work material, which 
could be observed as a bright exterior next to the 
parent metal. The microstructures of various welding 
surfaces show that associated coarse grains with 
consistent grain outlines in a welding zone is attained 
by means of the elevated heat of the FSW process [20]. 
Fig. 3 presents the microstructure of welding zone 
and its field emission scanning electron microscopy 
(FESEM) image for 90 % CMC work material. In this, 
90 % CMC material creates minor non-homogeneous 
welding on the parent metal; a small number of 
micro-voids were produced by over welding. Also, 
the distribution of welding is found to be higher on 
this CMC work material than others. Welding through 
85 % CMC work material creates micro-cracks in the 
welds and a few granular fractures were observed, 
which is presented in Fig. 4. The effective diffusion 
of B
4
C, W. and Cu produces extended dendrites in the 
welding zone which lead to micro-crack structures on 
the welding. Fig. 5 shows 80 % CMC work material, 
which provides superior consistent welding zone and 
a very minor amount of slip microstructure obtained 
across the welding surface [16]. White impulsive 
particles are found above the welding surface, which 
is due to the dispersion of Cu and W materials into the 
matrix exterior layer of work material. The elevated 
carbide content in the reinforcement material indicates 
the prominent oxidation at elevated temperature, 
which is leads to the development of molten metal on 
welding zone. 
2.2  Micro-hardness
A Vickers micro-hardness test was conducted for 
various reinforced copper work materials on welding 
regions; the results of the welding presented in Fig. 
6. The graph reveals that the hardness of the 90 % 
CMC work material is the lowest. The micro-hardness 
of welding is generally based on the microstructure 
variations. It is clear from Fig. 6 that the standard 
hardness of welding formed by 80 % CMC work 
material is 3.42 % higher than that of welding by 90 
% CMC work material. Also, the hardness for 80 % 

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
394 Elangandhi, J. – Periyagounder, S. – Selavaraj, M. – Saminatharaja, D.
CMC work material at parent material is shown to 
be higher compared to the welding using 90 % CMC 
work material, due to the enhancement of carbide and 
W in the parent metal [20]. The standard hardness of 
80 % CMC work material is 2.8 % more than that of 
90 % CMC work material work material. The welding 
and parent metal hardness are 108 HV and 113 HV, 
respectively, when 80 % CMC work material. The 
Fig. 3.  SEM image of 90 % CMC welding zone
Fig. 4.  SEM image of 85 % CMC welding zone
Fig. 5.  SEM image of 80 % CMC welding zone

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
395 Mechanical and Microstructural Properties of B4C/W Reinforced Copper Matrix Composite Using a Friction Stir-Welding Process
2.3  Tensile Properties
The average tensile strength of welding by different 
CMC materials is shown in Fig. 7. It is observed that 
the 90 % CMC materials creates 20 N/mm² tensile 
strength. The tensile strength of 85 % CMC and 80 
% CMC materials welding produce 68 N/mm² and 
119.2 N/mm² respectively, which is superior to the 
90 % CMC materials. It is observed that all wedding 
samples create the higher tensile strength than 90 % 
CMC in all factors of welding parameters due to the 
increasing of reinforcements [31]. The cross-sections 
of welding for different CMC materials are presented 
in Fig. 8.
addition of 15 % B
4
C reinforcements on 90 % CMC 
metal requires more time to melt than 85 % CMC 
metals that make the microstructure alteration. It 
is implicit that standard hardness when using of 85 
% CMC creates 2.56 % higher hardness compared 
to 80 % CMC materials. The alteration of cooling 
rate in welding zone modifies the crystal metal 
microstructure headed for an austenitic structure [21]. 
Also, the crystal microstructure is inflated with the 
increase in temperature, which becomes softer when 
welding. Hence, the standard hardness of welding was 
found to be less important than the welding and parent 
metal excluding 90 % CMC metals welding. 
Fig. 6.  Micro-hardness representation
Fig. 7.  Tensile strength representation

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
396 Elangandhi, J. – Periyagounder, S. – Selavaraj, M. – Saminatharaja, D.
a) 
b) 
c) 
Fig. 8.  SEM image of welding cross-sections;  
a) 90 % CMC, b) 85 % CMC, and c) 80 % CMC
2.4  Impact Strength
Fig. 10 presents the impact strength for the different 
CMC welding samples under different parameter 
levels. It is apparent that addition of B
4
C with CMC 
excites the creep strength in work material, which 
led to the elevated toughness. Of the various CMCs 
used as work material, the 80 % CMC work metal 
produces the maximum toughness of 4.39 J, and its 
cracked surface is shown in Fig. 9c. 80 % CMC work 
metal produces 68 % upper toughness than that using 
of welding on 90 % CMC work metal. The SEM 
image in Fig. 9a shows the broken surfaces with 80 
% CMC work metal welding specimen. It is apparent 
from the image that the sample shows the cleavage 
surface and mild micro-dimples as seen through white 
marks [22]. The 85 % CMC work metal produces 
the second-highest impact toughness of 4.6 J among 
a) 
b) 
c) 
Fig. 9.  SEM image of fractured cross section;  
a) 90 % CMC, b) 85 % CMC, and c) 80 % CMC

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
397 Mechanical and Microstructural Properties of B4C/W Reinforced Copper Matrix Composite Using a Friction Stir-Welding Process
others. Hence, 10 % B
4
C added CMC work metal 
produces 53 % higher impact toughness compared to 
the 90 % CMC. Fig. 9b presents the broken surface of 
welding with 90 % CMC work metal. According to 
the Fig. 9, 90 % CMC work metal produces a stringy 
microstructure and micro-voids over the broken 
surface. This is due to the easy movement of B
4
C 
from one side to another side by the tool revolutions. 
2.5  TOPSIS
The outcome responses of FSW process (e.g., 
hardness, tensile and impact strength) for different 
CMC work materials are optimized through the 
TOPSIS method. The preference values of outcome 
responses are calculated using Eq. (1) to (8). The 
weights for the responses are assigned equally under 
ideal conditions. The ranking of experimentation is 
presented in Table 4. The outcome responses of the 
experimentation are transformed from multi-attribute 
optimization to single objective optimization using 
Taguchi’s and TOPSIS method combination. The 
uppermost preference value (k
i
) is considered the 
optimal parameter combination, and the highest rank 
is termed “first optimal solution”. Consequently, it is 
observed that the 7
th
 experimental run (0.8376 k
i 
value) 
is selected as the optimal parameter combination 
for the finest performance of FSW process. The 
experimental runs 2
nd
 and 15
th
 presents the next 
suitable optimal parameter solution. Therefore, the 
suitable optimal parameter combination is found to be 
that 15 % B
4
C, 1200 rpm rotational speed, 9 mm/min 
welding speed and 9 kN axial force using TOPSIS. 
Table 4.  TOPSIS ranking
Experiment 
No.
T
i
+
T
i
–
Preference 
value, k
i
Rank
1 0.1749 0.3981 0.6948 4
2 0.1473 0.4558 0.7557 2
3 0.2588 0.3803 0.5950 7
4 0.2323 0.2910 0.5561 11
5 0.2484 0.2657 0.5168 12
6 0.2125 0.3041 0.5887 8
7 0.0869 0.4485 0.8376 1
8 0.4182 0.1156 0.2166 18
9 0.4523 0.1391 0.2352 17
10 0.1791 0.3938 0.6874 5
11 0.1829 0.3610 0.6636 6
12 0.2435 0.3410 0.5834 9
13 0.2173 0.2970 0.5775 10
14 0.2796 0.2366 0.4584 13
15 0.1594 0.3640 0.6954 3
16 0.3512 0.2487 0.4146 14
17 0.3857 0.1429 0.2703 15
18 0.4432 0.1521 0.2555 16
2.6  Table of ANOVA for TOPSIS
Analysis of variance (ANOVA) is the most suitable 
technique to find the significant and nonsignificant 
parameter from the experiments. The ki values of 
various CMC work material under different machining 
Fig. 10.  Impact strength of welding

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
398 Elangandhi, J. – Periyagounder, S. – Selavaraj, M. – Saminatharaja, D.
conditions are mathematically studied using ANOVA 
method, and all individual parameter solution over 
the outcome responses are investigated. Furthermore, 
the F-test results are employed to find the most 
significant parameter to obtain the good performance 
measure. Table 5 makes apparent that composite work 
materials, i.e., the percentage of reinforcements with 
copper material contributes more impact on welding 
characteristics by around 43.89 %. Subsequently, the 
significant factor is axial force that produces 32.68 % 
contribution on the FSW process. 
Table 5.  ANOVA for TOPSIS
Symbol
Machining 
parameter
df SS MS F
% 
contribution
A Rc 2 0.2645 0.1322 37.54 43.89
B Rs 2 0.0808 0.0404 11.48 13.42
C Ws 2 0.0285 0.0143 4.05 4.73
D Af 2 0.1969 0.0985 27.95 32.68
E Error 9 0.0317 0.0035 5.28
Total 17 0.6024 0.0354 100
2.7  GRA Method
The GRA method is a prominent technique employed 
to optimize the process parameters of the FSW 
process, such as micro-hardness, and tensile and 
impact strength. The GRC and GRG values are 
derived from Eqs. (11) and (12) for all experiments. 
The weights for the outcome responses are assigned 
equally (i.e., 1) and GRG values are presented in 
Table 6. The highest GRG value is selected as optimal 
parameter solution. Hence, the table suggest that the 
7
th
 experimental run (0.8465) holds the first rank and is 
termed as the optimal solution for better performance. 
The experimental combinations 2
nd 
(0.8461) and 
10
th
 (0.8226) have the next best optimal parameter 
combination using the GRA method. Therefore, the 
suitable and optimal parameter combination found 
to be that 15 % B
4
C, 1200 rpm rotational speed,  
9 mm/min welding speed and 9 KN axial force using 
GRA. 
2.8  ANOVA for GRG 
The results obtained from the GRG for the various 
parameter combinations are analysed mathematically 
using ANOVA, which is presented in Table 7. The 
GRA approach is used to optimize the obtained results 
for different CMC materials. According to this, the 
percentage of reinforcements in work materials affects 
the welding performances significantly at about 37.85 
%. The axial force of welding tool creates impact on 
the welding performance around 33.22 %, which is 
the next significant factor in the FSW process. 
Table 6.  GRG ranking
Experiment 
No.
GRC
GRG Rank 
Hardness
Tensile 
strength 
Impact 
toughness
1 0.6022 0.8890 0.8333 0.7748 4
2 0.6292 1.0000 0.9091 0.8461 2
3 0.5000 0.8778 0.7692 0.7157 7
4 0.7943 0.6711 0.6250 0.6968 10
5 0.7134 0.6645 0.6452 0.6743 13
6 0.7467 0.7070 0.6061 0.6866 11
7 1.0000 0.8729 0.6667 0.8465 1
8 0.6087 0.5309 0.6452 0.5949 17
9 0.6627 0.5000 0.6897 0.6175 15
10 0.5989 0.8689 1.0000 0.8226 3
11 0.6222 0.8257 0.7143 0.7207 6
12 0.5333 0.8011 0.8696 0.7347 5
13 0.7467 0.6929 0.6667 0.7021 9
14 0.6667 0.6509 0.5556 0.6244 14
15 0.7368 0.8015 0.6061 0.7148 8
16 0.9256 0.5610 0.5556 0.6807 12
17 0.6437 0.5506 0.6061 0.6001 16
18 0.7179 0.5092 0.5000 0.5757 18
Table 7.  ANOVA table for GRG
Sym-
bol
Machining 
parameter
df SS MS F
% 
contribution
A Ce 2 0.0438 0.0219 0.00825191 37.85
B Vm 2 0.0246 0.0123 68.1870725 21.30
C Cd 2 0.0072 0.0036 19.9226318 6.22
D Te 2 0.0384 0.0192 106.335841 33.22
E Error 9 0.0016 0.0002 1.41
 Total 17 0.1157 0.0068 100
3  CONCLUSIONS
This paper attempted to express the advantages and 
performance study of FSW process with copper 
composite material in reinforcement addition. Three 
CMC materials are prepared using pure copper 
(Cu) as the matrix; tungsten (W) and boron carbide 
(B
4
C) particles are reinforcements for various 
concentrations. The multi-objective decision-making 
methods, such as TOPSIS and GRA methods are 
used to find the optimal parameter combination, 
and experiments are planned according to the L 18 
orthogonal array (OA), using the most influential 
parameters, such as the percentage of boron carbide 

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)9-10, 388-400
399 Mechanical and Microstructural Properties of B4C/W Reinforced Copper Matrix Composite Using a Friction Stir-Welding Process
reinforcements, tool rotational speed, welding speed, 
and axial force. 
• Based on the optimization results, 15 % of B
4
C, 
900 rpm rotational speed, 15 mm/min welding 
speed and 6 kN axial forces produces the better 
mechanical strength on the welding using both 
TOPSIS and GRA techniques. 
• The microstructure of welding reveals that 
consistency of welding joint on all sides of the 
parent metal is found to be better in 15 % B
4
C 
reinforced CMC materials than other reinforced 
work materials, and lesser regularity found in 5 % 
B
4
C reinforced CMC material.
• 80 % CMC and 85 % CMC reinforced copper 
work metal produces 68 % and 10 % higher 
impact toughness respectively than that using of 
welding on 90%CMC work metal. 
• Based on the ANOV A table of TOPSIS, composite 
work materials, the percentage of reinforcements 
with copper material contributes more impact 
on welding characteristics of around 43.89 %. 
Subsequently, the next significant factor is axial 
force, which produces a 32.68 % contribution on 
the FSW process.
• Therefore, the mechanical strength of welding 
with FSW process increases with an increase of 
the percentage of reinforcement in the copper 
composite material. Also, these types of materials 
could be used for the applications for which high 
mechanical strength is required.
• Furthermore, experiments with hybrid composite 
with pure copper can be conducted, and assistance 
with FSW process such as heat energy can be 
experimentally tested with the FSW process to 
enhance the welding quality. 
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