Scholars Journal of Engineering and Technology (SJET) ISSN 2321-435X (Online)

Scholars Journal of Engineering and Technology (SJET) ISSN 2321-435X (Online)
Scholars Journal of Engineering and Technology (SJET)
Sch. J. Eng. Tech., 2016; 4(1):6-14
ISSN 2321-435X (Online)
ISSN 2347-9523 (Print)
©Scholars Academic and Scientific Publisher
(An International Publisher for Academic and Scientific Resources)
www.saspublisher.com
Original Research Article
Experimental Investigation of Friction Stir Welding of Aluminium Alloys Using
Response Surface Methodology
Shubham Patel1, Murali Krishna2
PG Student, Associate Professor, Mechanical Engineering Department, Gyan Ganga Institute of Technology and
Science, Jabalpur, Madhya Pradesh, India
1
2
*Corresponding author
Shubham Patel
Email:
Abstract: Friction stir welding (FSW) uses a non-consumable tool to produce frictional heat in the adjoining surfaces.
The welding parameters like rotational speed, welding speed, tool pin length, and tool shoulder diameter play a major
role in deciding the joint properties. In this work, an attempt has been made to analyse the effect of various tool profiles
have been used to fabricate joints by using constant thickness (3mm) work piece of aluminium alloy. The mechanical
properties of welded materials are measured in terms of tensile strength. With the help of vertical milling machine create
the specimen by friction stir welding (FSW). Now using universal testing machine on which tensile testing of the welded
specimen was carried out. After that by using design of experiment (DOE)concept. Experimentally were carried out to
predict tensile strength of the welded joint. After comparison of predicted and practical values of tensile strength
conclude that with increase in pin length tensile strength increase contently and tool geometry with a large shoulder
diameter together with high welding speed leads to decrease in welds speed leads to decrees’ in tensile strength of the
welds work pieces.
Keywords: aluminium alloy 6063-TS, friction stir welding, RSM.
INTRODUCTION
Friction stir welding (FSW), a solid-state
welding process has gained much popularity in research
areas as well as manufacturing industries since its
inception in 1991. For nearly two decades, FSW has
found its applications in aerospace and marine
industries as well as in high precision applications such
as micro welding. The basic physics behind a solid state
welding process is the joining of work pieces without
arriving at the melting point of the work pieces, thereby
requiring lower heat input for welding process. This is a
major advantage of FSW over conventional fusion
welding processes where high heat input is required to
melt the work material. The FSW makes it possible to
join lightweight materials like aluminium alloy,
magnesium alloy, etc. which are difficult to weld using
conventional welding processes. These advantages have
appreciably increased the usage of these materials in
structural applications. In addition, FSW also makes
possible to produce sound welds in 5000 and 7000
series aluminium alloys which cannot be welded by
conventional welding processes. In FSW, no sparks or
flames are produced. Therefore, safety and
environmental issues are not a major concern. FSW
process provides good quality and strong weld joints
with less number of equipment and eliminates the use
of filler metal. Due to these factors, FSW has been
successfully utilized in aerospace and ship building
industries. The need to understand and improve FSW
process continues to promulgate in many applications.
From much literature we select the metal
aluminium alloy 6063-TS which has good weld ability
for FSW aluminium plate of 3mm thickness were cut to
50mm*70mm rectangle for suitability for conventional
milling machine. Tool dimension and material play very
important role of FSW. The tool is made of mild steel.
From the literature we come to know that tool rpm,
welding speed, shoulder diameter and pin length play
very important role of the tool design so we taking 4
input parameters. After that with the conversional
milling machine we prepare the specimen with FSW
after that universal testing machine is used for tensile
strength. Total number of 30 experiment ware
performed experimentally including all the combination
of the four independent parameter experimental runs
generated through design expert stactical software with
response surface methodology after finding the 30
experiment we will compare the both values.
LITERATURE REVIEW
The friction stir welding makes it possible to
join light weight material like aluminium alloy,
magnesium alloy, etc. which are difficult to weld using
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Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
conventional welding process. These advantages have
appreciable increased the uses of these materials in
structural application and many researchers have been
to focus on FSW[1]. In this study, Al 1080 alloy
materials were welded using friction stir welding
process. The influence of stirrer design on the welding
process was investigated. For this purpose, five
different stirrers, one of them square cross-sectioned
and the rest were cylindrical with 0.85, 1.10, 1.40 and
2.1 mm screw pitched were used to carry out welding
process. Bonding could be affected with the square,
0.85 and 1.10 mm screw pitched stirrers. Microscopic
examination of the weld zone and the tension test
results showed that the best bonding was obtained with
0.85 mm screw pitched stirrer. In addition, temperature
distribution within the weld zone was also determined
[2]. Friction stir welding (FSW) is a new and promising
welding process that can produce low-cost and highquality joints of heat-treatable aluminum alloys because
it does not need consumable filler materials and can
eliminate some welding defects such as crack and
porosity. In order to demonstrate the friction stir
weldability of the 2017-T351 aluminum alloy and
determine optimum welding parameters, the relations
between welding parameters and tensile properties of
the joints have been studied in this paper. The
experimental results showed that the tensile properties
and fracture locations of the joints are significantly
affected by the welding process parameters. When the
optimum revolutionary pitch is 0.07 mm/rev
corresponding to the rotation speed of 1500 rpm and the
welding speed of 100 mm/min, the maximum ultimate
strength of the joints is equivalent to 82% that of the
base material. Though the voids-free joints are fractured
near or at the interface between the weld nugget and the
thermo-mechanically affected zone (TMAZ) on the
advancing side, the fracture occurs at the weld center
when the void defects exist in the joints[3]. The effect
of different shoulder geometries on the mechanical and
microstructural properties of a friction stir welded joints
have been studied in the present paper. The process was
used on 6082 T6 aluminium alloy in the thickness of
1.5 mm. The three studied tools differed from shoulders
with scroll and fillet, cavity and fillet, and only fillet.
The effect of the three shoulder geometries has been
analysed by visual inspection, macrograph, HV
microhardness, bending test and transverse and
longitudinal room temperature tensile test. The
investigation results showed that, for thin sheets, the
best joint has been welded by a shoulder with fillet and
cavity[4]. AA6061 aluminium alloy (Al-Mg-Si alloy)
has gathered wide acceptance in the fabrication of light
weight structures requiring a high strength-to-weight
ratio and good corrosion resistance. Compared to the
fusion welding processes that are routinely used for
joining structural aluminium alloys, the friction stir
welding (FSW) process is an emerging solid state
joining process in which the material that is being
welded does not melt and recast. This process uses a
non-consumable tool to generate frictional heat in the
abutting surfaces. The welding parameters such as tool
rotational speed, welding speed, axial force etc., and the
tool pin profile plays a major role in deciding the weld
quality. In this investigation an attempt has been made
to understand the effect of axial force and tool pin
profiles on FSP zone formation in AA6061 aluminium
alloy. Five different tool pin profiles (straight
cylindrical, tapered cylindrical, threaded cylindrical,
triangular and square) have been used to fabricate the
joints at three different axial force levels. The formation
of FSP zone has been analysed macroscopically.
Tensile properties of the joints have been evaluated and
correlated with the FSP zone formation. From this
investigation it is found that the square tool pin profile
produces mechanically sound and metallurgically defect
free welds compared to other tool pin profiles [5].
AA2219 aluminium alloy has gathered wide acceptance
in the fabrication of light weight structures requiring a
high strength to weight ratio. Compared to the fusion
welding processes that are routinely used for joining
structural aluminium alloys, friction stir welding (FSW)
process is an emerging solid state joining process in
which the material that is being welded does not melt
and recast. This process uses a non-consumable tool to
generate frictional heat in the abutting surfaces. The
welding parameters and tool pin profile play major roles
in deciding the weld quality. In this investigation, an
attempt has been made to understand the effect of
welding speed and tool pin profile on FSP zone
formation in AA2219 aluminium alloy. Five different
tool pin profiles (straight cylindrical, tapered
cylindrical, threaded cylindrical, triangular and square)
have been used to fabricate the joints at three different
welding speeds. The formation of FSP zone has been
analysed macroscopically. Tensile properties of the
joints have been evaluated and correlated with the FSP
zone formation. From this investigation it is found that
the square pin profiled tool produces mechanically
sound and metallurgically defect free welds compared
to other tool pin profiles[6]. In this study, the different
heat-treated-state 2024 Al-alloys were friction stir
welded. The tensile properties of the joints have a
tendency to increase with the precipitation hardening of
the base material. The peak tensile properties have been
obtained in the T6 (100 _C – 10 h) joint. It is observed
that the weld zone is strengthened by the friction stir
welding process for the 2024-O joint. The fracture
regions are detected near the nugget for W joint, the
interface between the nugget and the thermo
mechanically affected zone for T4 and T6 joints and
base material for O joint[7]. Friction stir welding
(FSW) is a novel solid state welding process for joining
metallic alloys and has emerged as an alternative
technology used in high strength alloys that are difficult
to join with conventional techniques. The applications
of FSW process are found in several industries such as
aerospace, rail, automotive and marine industries for
joining aluminium, magnesium and copper alloys. The
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Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
FSW process parameters such as rotational speed,
welding speed, axial force and attack angle play vital
roles in the analysis of weld quality. The aim of this
research study is to investigate the effects of different
welding speeds and tool pin profiles on the weld quality
of AA6082-O aluminium. This material has gathered
wide acceptance in the fabrication of lightweight
structures requiring a high strength-to-weight ratio. Triflutes and taper screw thread pin are used as tool pin
profiles in this research. The appearance of the weld is
well and no obvious defect is found using these tools.
Consequently, the obtained results explain the variation
of stress as a function of strain and the effect of
different welding speed and pin profiles on yield
strength ultimate tensile strength and elongation. The
friction stir welded plates of AA6082-O by using the
taper screw thread pin profile reaches the ultimate
tensile strength of 92.30% of the base metal ultimate
strength and % elongation of 27.58% [8]. The aircraft
aluminium alloys generally present low weld ability by
traditional fusion welding process. The development of
the friction stir welding has provided an alternative
improved way of satisfactorily producing aluminium
joints, in a faster and reliable manner. In this present
work, the influence of process and tool parameters on
tensile strength properties of AA7075-T6 joints
produced by friction stir welding was analysed. Square
butt joints were fabricated by varying process
parameters and tool parameters. Strength properties of
the joints were evaluated and correlated with the
microstructure, microhardness of weld nugget. From
this investigation it is found that the joint fabricated at a
tool rotational speed of 1400 rpm, welding speed of 60
mm/min, axial force of 8 kN, using the tool with 15 mm
shoulder diameter, 5 mm pin diameter, 45 HRc tool
hardness yielded higher strength properties compared to
other joints [9]. Currently friction stir welding tools are
designed by trial and error. Here we propose and test a
criterion for the design of a tool shoulder diameter
based on the principle of maximum utilization of
supplied torque for traction. The optimum tool shoulder
diameter computed from this principle using a
numerical heat transfer and material flow model
resulted in best weld metal strength in independent tests
and peak temperatures that are well within the
commonly encountered range [10]. Friction stir welded
joints of Al–Zn–Mg aluminium alloy AA7039 were
given five different post weld heat treatments in order
to investigate their effect on microstructure and
mechanical properties. In general, all the applied post
weld heat treatments increased the size of an aluminum
grains in all zones of friction stir weld joints. Abnormal
grain growth was observed in entire zone modified by
friction stir welding in case of solution treated joints
with and without artificial aging. The naturally aged
joints offered the highest mechanical properties while
solution treated joints offered lowest mechanical
properties of the joints. Naturally aged joints yielded
highest tensile strength (94.9%) and elongation
(174.2%) efficiencies while artificially aged joints
yielded highest yield strength efficiency (96.7%).
Further, post weld heat treatment also affected fracture
location and mode of fracture [11]. Friction stir linear
welding (FSLW) uses a non consumable tool to
generate frictional heat in the abutting surfaces. The
welding parameters such as rotational speed, welding
speed, axial force, tool tilt angle, etc., and tool pin
profiles play a major role in deciding the joint
properties. In this paper, an attempt has been made to
study the effect of four different tool pin profiles on
mechanical properties of AA 6061 aluminum alloy.
Four different profiles have been used to fabricate the
butt joints by keeping constant process parameters of
tool rotational speed 1200RPM, welding speed
14mm/min and an axial force 7kN. Different heat
treatment methods like annealing, normalizing and
quenching have been applied on the joints and
evaluation of the mechanical properties like tensile
strength, percentage of elongation, hardness and
microstructure in the friction stirring formation zone are
evaluated. From this investigation, it is found that the
hexagonal tool profile produces good tensile strength,
percent of elongation in annealing and hardness in
quenching process[12]. The joining of dissimilar
AA2024 and AA6061 aluminium plates of 5mm
thickness was carried out by friction stir welding (FSW)
technique. Optimum process parameters were obtained
for joints using statistical approach. Five different tool
designs have been employed to analyse the influence of
rotation speed and traverse speed over the
microstructural and tensile properties. In FSW
technique, the process of welding of the base material,
well below its melting temperature, has opened up new
trends in producing efficient dissimilar joints. Effect of
welding speed on microstructures, hardness distribution
and tensile properties of the welded joints were
investigated. By varying the process parameters, defect
free and high efficiency welded joints were produced.
The ratio between tool shoulder diameter and pin
diameter is the most dominant factor. From micro
structural analysis it is evident that the material placed
on the advancing side dominates the nugget region. The
hardness in the HAZ of 6061 was found to be
minimum, where the welded joints failed during the
tensile studies [13]. Friction stir welding (FSW) uses a
non consumable tool to produce frictional heat in the
adjoining surfaces. Then welding parameters like
rotational speed, welding speed, tool pin length, and
tool shoulder diameter play a major role in deciding the
joint properties. In this work, an attempt has been made
to analyze the effect of various tool profiles on
mechanical properties of aluminum alloy. Various tool
profiles have been used to fabricate joints by using
constant thickness (3mm) work piece of aluminum
alloy. The mechanical properties of welded materials
are measured in-terms of tensile strength and Brinell
hardness number (BHN). By using Design of
Experiment (DOE) concept, experiments were carried
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Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
out to predict tensile strength and BHN of the welded
joint. In this work, heat generated during the process is
utilized to improve the quality of welded joint by using
backing plate (low thermal conductivity or insulating
material) between workpiece and fixture. By varying
the welding parameters, effect on joining efficiency in
terms of gap between two mating surfaces on the back
side of the welded plate has been analyzed. From this
investigation, it has been found that tool profile
(shoulder dia. 18 mm, pin length 2.8 mm) produces
good tensile strength.
From the literature review, the following areas
are identified in which future work is needed to be
carried out. Limited study has been done in the pin
length variation with shoulder diameter variation of tool
for same thickness of work piece in FSW. Various tools
have been used for the process parameters but use of
different tool length. Limited study has been done to
relate pin length variation with indentation quality.
Component
Wt.%
Al
Max.
97.5
Cr
Max.
0.1
METHODOLOGY
On the basis of literature review, still there is a
need to strengthen friction stir welding for light weight
and low melting temperature materials. Implementation
of such a strengthened friction stir welding requires
proper instrumentation to analyse the welded specimen.
To increase the strength of the friction stir welding, it is
important to control parameters used during the friction
stir welding process. The motive of this work is to
achieve high quality strength of the welded joint by
controlling the parameters when welding is taking
place. There for eat tempt has been made to improve the
strength of the welded specimen by applying statistical
analysis
Materials
Aluminum alloy 6063-T6, which has good
weldability for FSW, was used. Aluminum plate of
3mm thickness was cut to 50mmx70mm rectangle
whose chemical composition is listed inTable1.
Table 1: chemical composition
Cu
Fe
Mg
Mn
Max.
Max.
0.45Max.
0.1
0.35
0.9
0.1
Experimental setup
Experimental setup was established using a
conventional vertical milling machine Figure 1. No
extra setup is required for friction stirwelding except
tool and fixture, so as to place piece in proper position
during welding.
The specimen is fixed in the machine between
the grips and machine the displacement between its
cross heads on which the specimen is fixed. The
objective of tensile testing was to determine the tensile
yield strength and percentage of yield elongation of
friction stir welds of aluminium alloys.
Ti
Max.
0.1
Zn
Max.
0.1
Design of Experiment
Response surface methodology is concerned
with a set of statistical and mathematical techniques that
are useful for designing, developing, improving and
optimizing the process under study. RSM has widely
been used in the field of industry and chemical
engineering to study the yield or output of a system as it
varies in response to the changing levels of one or more
applied factors [2]. The main emphasis was on the use
of designs of experiments and regression analysis to
investigate a particular response produced by a given
set of input variables over a specified region of interest;
to explore the level of input variables that give a
specified response and to model the information in
adequate functional form, so that the shape of response
surfaces at its optimum point is identified. The role of
RSM is to work as a set of techniques that consists of
the following steps:
i.
ii.
iii.
Fig.1: Experimental Setup
Si
0.2-0.6
Determination of a sequence of experiments
that provide adequate and reliable values of the
response variables under study.
Finding the relationship between response and
a suitable independent factor (variables).
Locating optimum response of the process by
changing the levels of the input variables ξ_,
ξ_ ……. ξ_ that can be viewed as design
variables.
Factors are the processing conditions or input
variables whose values (or levels) can be controlled for
performing the experiments e.g. diameter, bend and
9
Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
speed etc. The word level means the value of input
variables or factors examined in the experiment.
can generate various classes of RSM designs and, in
some cases, can also offer several varieties of each
class. However, the central composite design is the
most popular of all the RSM
Experiments, which are particularly designed
to explore response surfaces, are called response surface
designs. They are particularly used to predict the model.
The form and order of approximating polynomial
depends on the postulated model. Usually first and
second order models are used.
A design which consists of two levels factorial
or fractional factorial is chosen so as to allow the
estimation of all first order and two factor interaction
terms augmented with further points which allow pure
quadratic effects to be estimated is called central
composite design (CCD). Three types of central
composite design (CCD), depending on the location of
star points are:
1. Central Composite Circumscribed (CCC)
Design
2. Central Composite Inscribed (CCI) Design
3. Central Composite Face (CCF) Centred
Design
There are many different second order design
e.g. Central composite cuboidal design, central
composite orthogonal design, central composite
rotatable design, central composite minimum variance
design, central composite mini-max loss3 design and
Box-Behukent design.
The suitability of the second order model is
based upon the following:
i.
It is a flexible model which can be used to
generate the curvilinear response surface and
to draw contour plots. The estimation of
parameters is simple which is obtained through
ordinary least squares method.
ii.
The second model is very useful in solving real
response surface problems.
iii.
In the case of missing observations, it is used
to measure the losses in central composite
designs.
In this thesis, a face centred design is used
because it requires only three levels of the factor sand in
practice; it is frequently difficult to change factor level.
However, a Face centred central composite design is
not rotatable. CCF designs provide relatively high
quality predictions over the entire design space and do
not require using points outside the original Factor
range [2].
The choice of the distance of axial points (ζ)
from the centre of the design is important to make a
central composite design (CCD) rotatable. The value of
ζ for rotatability of the design scheme is estimated as ζ
= (2)f*1/4But in (CCF) face centred ζ =1. The number of
experiments is estimated as
N = 2 f + 2 *f + nc
Where,
N=number of the experiment
f= number of the factor
nc= number of centre point
The
statistical
experimental
designs
extensively used in optimization of experiments are
referred as "response surface designs." In addition to the
trials at extreme level settings of the variables, response
surface designs also contain trials in which one or more
variables is/are set at the midpoint of the study range.
Thus, these designs provide information on direct
effects, on pair wise interaction effects and on
curvilinear variable effects. Response surface
methodology, an approach to product and process
optimization, derives its name from the extensively
used optimization experiment designs. Most of the
practitioners of RSM now obtain their experimental
designs and analyse the data using statistical software
running on a personal computer. Many of this software
Input Parameter
Shoulder dia. ( mm)
Pin length ( mm)
Tool RPM
Welding speed (mm/min)
Level of Independent variables
Response Surface Methodology (RSM)
Response surface methodology has been used
to develop the regression model. Regression models
have been developed using 30 experimental runs as per
desired central composite rotatable experimental design
In the experiment where f=4, nc=6 . The
number of experiments in a CCD matrix corresponding
to three process variables is calculated as 2 4 + (2 * 4) +
6 = 30.
Table 2
Level
-1
20
2.8
1600
100
0
18
1.9
1200
80
1
16
1
800
60
shown in Table 2. In central composite face centred
design, the response of the system and the input
parameters are taken to have the following
relationships:
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Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
𝐾
𝑌 = 𝛽0 +
𝐾
𝛽𝑖𝑖 𝑋𝑖 2 +
𝛽𝑖 𝑋𝑖 +
𝑖=1
𝛽𝑖𝑗 𝑋𝑖𝑋𝑗 … … … …
𝑖=1
𝑖<𝑗
Above equation expanded to:
Y=β0+β1X1+β2X2+β3X3+β4X4+β5 X12+ β6X13+β7X14+β8X23+β9X24+β10X34+β11X1
2+ β12 X22+ β13 X32 + β14 X42 ………………….…….Eq. (1)
Where:
β0= constant X1 = Shoulder dia.
β1, β2, β3,β4 = linear coefficients X2 = Pin length
β11, β12, β13, β14= quadratic coefficients X3 = Tool RPM
β5, β6, β7, β8, β9, β10= cross product coefficients X4= Welding speed
Regression equation has been developed using equation 1 to predict the response.
1. Regression equation for tensile strength:
Ts=(-275.458) + (14.657*S) + (77.622*P) + (0.079*T) + (2.976*F) - (0.748*S*P) +
(0.003*S*T) - (0.0218*S*F) -(0.007*P*T) - (0.098*P*F) + (0.002*T*F) - (0.303*S2)(6.437*P2)-(0.003*T2)-(0.016*F2) ………………..…Eq.
(2)
Table 2 shows the predicted response using
regression Eq. (2) from the Response surface
methodology (RSM) designing a set of experiments
which are analysed to identify the optimal conditions,
the factors that influence the results, selecting the
number of experiments to be performed under
controlled conditions. Develop the regression model.
Regression models have been developed using 30
experimental runs as per desired central composite
rotatable experimental design.
predicted values.
Table
shows the
A total number of 30 experiments were
performed to include all combinations of the four
independent parameters (table1). Table shows list of
experimental runs generated through Design expert
statistical software. These are the friction stir welding
conditions in sequence for friction welding.
Table 3
Experiment no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Shoulder dia.
Input parameter
Pin length
Tool RPM
Welding speed
20
16
20
18
18
18
20
16
20
16
18
16
18
16
16
18
18
16
18
20
18
20
20
20
18
18
18
16
16
20
2.8
1
1
1.9
1.9
1.9
2.8
2.8
2.8
2.8
1.9
2.8
1.9
1
1
1
1.9
1
2.8
1.9
1.9
1
2.8
1
1.9
1.9
1.9
1.9
2.8
1
60
60
60
80
80
80
100
100
60
100
80
60
60
60
100
80
80
100
80
80
100
60
100
100
80
80
80
80
60
100
800
1600
1600
1200
1200
1200
1600
1600
1600
800
1600
1600
1200
800
800
1200
1200
1600
1200
1200
1200
800
800
800
800
1200
1200
1200
800
1600
Predicted
values of
specimen
139.87
92.229
100.992
135.007
135.007
137.7
139.3
139.442
137.371
134.514
132.975
134.761
128.5
84.606
88.467
108.795
135.007
104.236
144.008
135.77
130.005
92.63
133.653
93.759
126.34
135.007
136.007
128.932
137.999
110.267
Experimental
values
of
specimen
138.6
90.5
100.6
136.4
132.8
136.8
128
141.4
139.4
135.2
132.1
136.8
129.11
86.2
88.5
112.7
136.6
105.8
145.8
135
129.3
91.7
136.43
91
125.9
136
136.4
128.5
137.8
110.5
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Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
After performing experiments tensile strength
is measured with the help of universal testing machine
(UTM). With the help of response surface
methodology, results relating input parameters and
output are shown graphically. Design expert statistical
software is used which defines input factors (such as
shoulder diameter, pin length, tool RPM and welding
speed)with their values and tensile strength as a
response. Results have been plotted as shown in graph 1
to 4.
Effect of pin length on tensile strength is
shown in graph 2, where tensile strength is continually
increasing with increasing pin length due to more
penetration of pin in the work pieces and produces more
frictional heat throughout the thickness of work piece
and plasticizes the material.
a certain level then decreases due to more heat
generation, which causes grains to become coarse.
Effect of tool RPM on the tensile strength is
shown in graph 3 where tensile strength increases up to
Comparison of experimental and model value
for various responses- now after got all the practical and
experimental values we will compared the all values
and plot the curves.
In graph1, Effect of shoulder diameter on
tensile strength is shown where tensile strength
increases with increase in shoulder diameter up to
18mm due to large surface area but in case of 20mm
shoulder diameter more heat generation results in
coarse structure hence, tensile strength decreases.
Effect of welding speed on tensile strength is
shown in graph.4, where tensile strength is lower at
initial level due to more heat generation which results in
coarse grain structure and at high welding speed lower
frictional heat is generated resulting in poor plastic flow
and defect generation.
Experimental and theoretical values of tensile
strength with variation in welding speed. (Graph 5)
12
Shubham Patel et al., Sch. J. Eng. Tech., January 2016; 4(1):6-14
Experimental and theoretical values of tensile
strength with variation in pin length. (Graph 6)
Experimental and theoretical values of tensile
strength with variation in tool RPM. (graph7)
Experimental and theoretical values of tensile
strength with variation in shoulder Diameter.(graph8)
were used to develop the regression modal. The
experimentally determined tensile strength values were
compared with values predicted by the regression
model and the model is proved to be capable of
predicting tensile strength within the acceptable margin
of error. The following conclusions have been made
out.
1. Regression analysis has been successfully used
to develop the relation between input
parameters and tensile strength.
2. The dominant factor affecting tensile strength
is pin length (mm) with increase in pin length
tensile strength increases constantly.
3. A tool geometry with a large shoulder diameter
together with a high welding speed leads to
decrease in tensile strength of the welded work
pieces.
RESULTS AND DISCUSSION
The error rate of this model is calculated.
Maximum error in case of tensile strength has been
reported at medium level for shoulder diameter,
welding speed and tool RPM and at lower level for pin
length. The calculated value of error is 0.26% for the
tensile strength. The error is within 5% which is
acceptable for regression model.
CONCLUSION
Tensile strength response is investigated by
varying input parameters such as shoulder diameter
(mm), length of pin (mm), tool speed (RPM) welding
speed (mm/min) which affect the performance of
friction stir welding under normal running condition.
Experiments were conducted according to Central
Composite Face Cantered Design with various
combinations of parameters, so as to determine the
combination which produces sound weld quality in
friction stir welding. Regression model was developed
to predict the tensile strength. The experimental values
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