This dissertation examines the parametric optimization of friction stir welding (FSW) when joining dissimilar aluminum alloys. The document outlines the methodology, which includes: selecting critical welding parameters; designing experiments using a fractional factorial design of experiments approach in Minitab; conducting FSW experiments; analyzing tensile strength and hardness results; and developing mathematical models. Regression analysis identified tool tip plunge depth, shoulder diameter, tilt angle, and tool shape as significant parameters. Interactions between parameters also influenced weld strength. The study aims to optimize FSW of dissimilar aluminum alloys for applications like shipbuilding and aerospace.

1. Dissertation
On
“Parametric Optimization of Friction Stir Welding
while using Dissimilar Aluminium Alloys”
Presented By: Supervised By:
Rahul Singla Prof. (Dr.) Bikram Jit Singh
75117130
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

2. Contents
•Introduction
• Need of Present Study
• Literature Review
• Research Gap
• Problem Formulation
• Methodology Adopted
• Experimentation Findings
• Result Analysis and Validation
• Conclusion
• Scope for Future Study
• References
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

3. Introduction
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4. Welding:
Welding is a process by which two similar or dissimilar materials,
usually metals, are permanently joined together by coalescence,
which is induced by a combination of temperature, pressure and
metallurgical conditions. The particular combination of these
variables can range from high temperature with no pressure to high
pressure with no increase in temperature. Thus welding can be
accomplished under a wide variety of conditions and a number of
welding processes have been developed.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)
Welding Process
Fusion
Welding
Solid State
Welding

5. Friction Stir Welding (FSW):
FSW is a fairly recent technique that utilizes a non consumable
rotating welding tool to generate frictional heat and plastic
deformation at the welding location, affecting the formation of a
joint while the material is in the solid state
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6. FSW Process:
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7. Key Benefits of FSW:
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Metallurgical Benefits Environmental Benefits Energy Benefits
 Solid-Phase process
 Low distortion
 Good dimensional stability and
repeatedly
 No loss of alloying elements
 Excellent mechanical properties in
the joint area
 Fine recrystallized microstructure
 Absence of solidification cracking
 Replace multiple parts joined by
fasteners
 Weld all Aluminium alloys
 Dissimilar materials can be joined
 No Shielding gas required
 Minimal surface cleaning
required
 Eliminate grinding wastes
 Eliminate solvents required for
degreasing
 Consumable materials saving,
such as rugs, wire or any other
gases
 No harmful emissions
 Improved materials use
(e.g. joining different
thickness) allows
reduction in weight.
 Decreased fuel
consumption in
lightweight aircraft,
automotive and ship
application

8. FSW Applications:
•Aerospace Industry (wings, fuel tanks, scientific rockets, repair for
other welds etc.)
• Ship Building and Marine Industry (deck panels, helicopter
landing platforms, refrigeration plant, hulls,
superstructures, al extrusions etc.)
• Railway Industry(high speed trains, trams, goods wagon, containers etc)
• Land Transportation (truck bodies, wheel rims, fuel tankers etc.)
• Construction Industry (window frames, pipes, al reactors, air
conditioners etc.)
• Electrical Industry (bus bars, electric motor housings etc.)
• Other Industry Sectors (refrigeration panels, cooking equipments,
furniture etc.)
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9. FSW Equipment:
Tool Vertical Milling Machine
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10. FSW Equipment:
Fixture
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11. FSW Process Parameters:
• Tool Rotation Speed
• Feed Rate
• Tool Tip Shape
• Tool Tip Plunge Depth
• Tool Tilt Angle
• Shoulder Diameter
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12. Design of Experiments (DoE):
DoE is a series of test in which the researcher makes purposeful
changes to input variables of a system or process and the effect on
response variables are measured.
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13. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)
Traditional Method DoE
Hit & Trial Method. Designed/Planned Method.
OFAT
Multi Factors and their interaction
can be recorded to final affect on
response.
Statistically significant factors can’t be
found.
It can be found and hence it makes
optimization of process more
accurate.
Time consuming, Energy wastage,
complex computations.
Mote accurate and less time
consuming as well as complex.
Graphical implication of different factors
effecting response could not be
determined.
It can be done using DoE.

14. Response Variables in Study:
• Tensile Strength
• Hardness
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15. Need of Present Study
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16. Motivation of Study:
• Technology of Welding is growing.
• Application of Friction Stir Welding(FSW) as an advance
welding technology.
• Choice of dissimilar materials.
• Aluminium alloys offers wide range of capability and
applicability.
• Selection of Process Parameters (MFAT).
• DoE an important tool for designing the experiments.
• Use of Minitab software.
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17. Literature Review
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18. Description of FSW
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19. Selection of critical to process parameters (CPPs)
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20. Optimization of FSW
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21. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

22. Research Gap
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23. GAPS IN EXISTING RESEARCH WORK
(i) Most of the work has been conducted on similar alloys like
(AA 6061, AA 5083 and AA 2219). Not much work has been
done on dissimilar aluminum alloys.
(ii) No significant work has been done on AA 5086 which is
indeed very important alloy used in marine engineering and
aerospace applications like ship building, fabrication of
aircrafts.
(iii) The literature survey indicates that majority of the studies
have been conducted by taking into account one
parameter/factor at a time (say; tool rotation, tool profile,
tool shape, tilt angle etc.). Multi factors at a time have
rarely been taken into account. Moreover it is hard to find
papers defining impact of two or more factor-combinations
or interactions at a time.
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24. Contd…
(iv) Above literature search indicates that the technique of
Design of Experiments (DoE) has not been used in a
systematic way and the experiments have been
conducted by using hit & trial methods. Prioritization of
various CTP parameters is highly lacking.
(v) The literature surveyed also reveals that wherever DoE has
been used, very few had deduced mathematical modeling
of process parameters for future scope.
.
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25. Problem Formulation
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26. Keeping in view the background, literature review and
gaps thereon, this research work aims at:
• Selection and prioritization of various Critical Process
Parameters (CPPs).
• Identification of key characteristics (Desired Mechanical
properties).
• Mathematical Modeling (equation formulation for
various key characteristics).
• Optimization through DoE (by using Minitab 16 release
version).
• Scope of present work in future.
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27. Methodology Adopted
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Objectives
Selection of CCPs Parameters
Define the Range of CPPs
Designed the Experiments
Actual Experimentation
Selection of Response variable(s)

28. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)
Mechanical Testing
DoE Statics
Prioritization of CPPs
Optimization through Response
Optimizer
Result Analysis and Validation
Development of Mathematical
Model for different desired
characteristics
Conclusion and Scope for future
work

29. Tool Speed (rpm) Feed (mm/min)
Tip Plunge Depth
(mm)
Shoulder Diameter
(mm)
Tilt Angle
(Degrees) Tool Shape
Low Level 3080 20 4.5 16 1 Square
High Level 4600 30 5.5 20 2 Trapezodial
Factors with Levels
Factorial Design of Experiments (1/2 Fraction)
(for Optimization of Friction Stir Welding of non-similar Al-Alloys)
Experimental Findings
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30. Tool Speed (rpm) Feed (mm/min)
Tip Plunge Depth
(mm)
Shoulder Diameter
(mm)
Tilt Angle
(Degrees)
Tool Shape
(Physical Shape)
Tensile Strength
(KN/mm²) Hardness (HVN)
1 4600 20 4.5 20 1 Trapezodial 0.079 79.53
2 4600 30 4.5 16 1 Trapezodial 0.065 67.97
3 4600 20 4.5 16 1 Square 0.103 70.80
4 3080 20 4.5 20 2 Trapezodial 0.099 68.17
5 3080 30 5.5 16 1 Trapezodial 0.094 76.03
6 3080 30 4.5 16 2 Trapezodial 0.109 59.97
7 4600 20 4.5 20 2 Square 0.152 62.97
8 3080 30 5.5 20 2 Trapezodial 0.025 69.80
9 4600 20 5.5 20 1 Square 0.118 71.80
10 3080 30 4.5 20 1 Trapezodial 0.106 65.40
11 3080 20 4.5 16 1 Trapezodial 0.100 57.10
12 3080 20 4.5 20 1 Square 0.133 70.47
13 3080 30 4.5 20 2 Square 0.085 63.90
14 4600 30 5.5 20 1 Trapezodial 0.080 78.70
15 3080 20 4.5 16 2 Square 0.121 67.47
16 3080 30 4.5 16 1 Square 0.074 76.83
17 3080 20 5.5 16 1 Square 0.075 78.63
18 4600 30 4.5 16 2 Square 0.123 52.90
19 4600 30 5.5 20 2 Square 0.113 58.13
20 4600 30 4.5 20 1 Square 0.157 56.30
21 3080 20 5.5 20 1 Trapezodial 0.184 56.20
22 3080 30 5.5 20 1 Square 0.168 75.27
23 3080 20 5.5 16 2 Trapezodial 0.042 77.30
24 3080 20 5.5 20 2 Square 0.046 66.33
25 4600 30 5.5 16 1 Square 0.038 60.30
26 4600 20 5.5 16 1 Trapezodial 0.087 63.13
27 3080 30 5.5 16 2 Square 0.072 80.37
28 4600 20 4.5 16 2 Trapezodial 0.113 73.40
29 4600 30 4.5 20 2 Trapezodial 0.063 74.90
30 4600 20 5.5 16 2 Square 0.092 52.27
31 4600 30 5.5 16 2 Trapezodial 0.088 69.53
32 4600 20 5.5 20 2 Trapezodial 0.072 62.13
Designed Experimental Runs with Responses
ResponsesIndependent Process Parameters
Runs
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31. Data Testing w.r.t. Tensile Strength
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32. Source DF Adj SS Adj MS F-Value P-Value
Model 17 0.038138 0.002243 6.90 .000
Linear 5 0.009185 0.001837 5.65 .005
Tool Speed 1 0.000003 0.000003 0.01 .923
Tip Plunge Depth 1 0.002592 0.002592 7.97 .014
Shoulder Diameter 1 0.002521 0.002521 7.75 .015
Tilt Angle 1 0.001891 0.001891 5.81 .030
Tool Shape 1 0.002178 0.002178 6.70 .021
2-Way Interactions 8 0.021731 0.002716 8.35 .000
Tool Speed*Tip Plunge Depth 1 0.000066 0.000066 0.20 .659
Tool Speed*Shoulder Diameter 1 0.000036 0.000036 0.11 .744
Tool Speed*Tilt Angle 1 0.005618 0.005618 17.27 .001
Tool Speed*Tool Shape 1 0.001711 0.001711 5.26 .038
Tip Plunge Depth*Tilt Angle 1 0.003655 0.003655 11.24 .005
Tip Plunge Depth*Tool Shape 1 0.000840 0.000840 2.58 .130
Shoulder Diameter*Tilt Angle 1 0.007626 0.007626 23.45 .000
Shoulder Diameter*Tool Shape 1 0.002178 0.002178 6.70 .021
3-Way Interactions 4 0.007222 0.001806 5.55 .007
Tool Speed*Tip Plunge Depth*Tilt Angle 1 0.003445 0.003445 10.59 .006
Tool Speed*Tip Plunge Depth*Tool Shape 1 0.001225 0.001225 3.77 .073
Tool Speed*Shoulder Diameter*Tilt Angle 1 0.001012 0.001012 3.11 .099
Tool Speed*Shoulder Diameter*Tool Shape 1 0.001540 0.001540 4.74 .047
Error 14 0.004553 0.000325
Total 31 0.042691
Factorial Regression: Tensile Strength Versus FSW Parameters
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33. Regression Equation in Un-coded Units
Tensile Strength (KN/mm²) = 2.837 - 0.000525 Tool Speed
- 0.382 Tip Plunge Depth - 0.0587 Shoulder Diameter
- 1.902 Tilt Angle + 0.049 Tool Shape
+ 0.000078 Tool Speed*Tip Plunge Depth
+ 0.000010 Tool Speed*Shoulder Diameter
+ 0.000371 Tool Speed*Tilt Angle
- 0.000009 Tool Speed*Tool Shape
+ 0.2524 Tip Plunge Depth*Tilt Angle
- 0.0523 Tip Plunge Depth*Tool Shape
+ 0.0439 Shoulder Diameter*Tilt Angle
+ 0.01340 Shoulder Diameter*Tool Shape
- 0.000055 Tool Speed*Tip Plunge Depth*Tilt Angle
+ 0.000016 Tool Speed*Tip Plunge Depth*Tool Shape
- 0.000007 Tool Speed*Shoulder Diameter*Tilt Angle
- 0.000005 Tool Speed*Shoulder Diameter*Tool Shape
To make the above equation more simple…..
We can even ignore the non-significant factors and their
respective interactions.
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34. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

35. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

36. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

37. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

38. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

39. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

40. Tool Speed 3840
Tip Plunge Depth 5
Tool Shape Square
Hold Values
Shoulder Diameter
TiltAngle
2019181716
2.0
1.8
1.6
1.4
1.2
1.0
>
–
–
–
–
–
–
< 0.08
0.08 0.09
0.09 0.10
0.10 0.11
0.11 0.12
0.12 0.13
0.13 0.14
0.14
(KN/mm²)
Strength
Tensile
Contour Plot of Tensile Strength vs Tilt Angle, Shoulder Diameter
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41. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

42. Analysis w.r.t. Second Response
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43. Data Testing w.r.t. Hardness
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44. Factorial Regression: Hardness Versus FSW Parameters
Source DF Adj SS Adj MS P-Value
Model 22 2022.96 91.953 .001
Linear 6 220.08 36.680 .029
Tool Speed 1 92.75 92.752 .010
Feed 1 2.31 2.311 .623
Tip Plunge Depth 1 24.22 24.221 .134
Shoulder Diameter 1 0.50 0.500 .818
Tilt Angle 1 63.06 63.056 .026
Tool Shape 1 37.24 37.238 .071
2-Way Interactions 11 1392.21 126.564 .000
Tool Speed*Feed 1 58.32 58.320 .031
Tool Speed*Tip Plunge Depth 1 168.36 168.361 .002
Tool Speed*Shoulder Diameter 1 163.44 163.443 .002
Tool Speed*Tilt Angle 1 49.20 49.203 .043
Tool Speed*Tool Shape 1 553.78 553.779 .000
Feed*Tip Plunge Depth 1 162.36 162.360 .002
Feed*Tilt Angle 1 2.93 2.928 .581
Feed*Tool Shape 1 55.34 55.335 .034
Tip Plunge Depth*Shoulder Diameter 1 36.98 36.980 .072
Tip Plunge Depth*Tilt Angle 1 0.38 0.378 .841
Tilt Angle*Tool Shape 1 141.12 141.120 .003
3-Way Interactions 5 410.67 82.135 .002
Tool Speed*Feed*Tip Plunge Depth 1 31.68 31.681 .092
Tool Speed*Feed*Tilt Angle 1 124.19 124.189 .005
Tool Speed*Feed*Tool Shape 1 60.94 60.941 .028
Tool Speed*Tip Plunge Depth*Shoulder Diameter 1 145.35 145.351 .003
Tool Speed*Tip Plunge Depth*Tilt Angle 1 48.51 48.511 .045
Error 9 80.22 8.914
Total 31 2103.18
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45. Regression Equation in Un-coded Units
Hardness (HVN) = -1200 + 0.3327 Tool Speed + 0.81 Feed + 302.5 Tip Plunge Depth
+ 53.4 Shoulder Diameter + 10.0 Tilt Angle + 14.6 Tool Shape
- 0.00142 Tool Speed*Feed - 0.0793 Tool Speed*Tip Plunge Depth
- 0.01253 Tool Speed*Shoulder Diameter
- 0.0032 Tool Speed*Tilt Angle - 0.00361 Tool Speed*Tool Shape
- 1.11 Feed*Tip Plunge Depth + 4.10 Feed*Tilt Angle
- 1.132 Feed*Tool Shape
- 11.84 Tip Plunge Depth*Shoulder Diameter
- 24.4 Tip Plunge Depth*Tilt Angle
- 4.20 Tilt Angle*Tool Shape
+ 0.000524 Tool Speed*Feed*Tip Plunge Depth
- 0.001037 Tool Speed*Feed*Tilt Angle
+ 0.000363 Tool Speed*Feed*Tool Shape
+ 0.002804 Tool Speed*Tip Plunge Depth*Shoulder Diameter
+ 0.00648 Tool Speed*Tip Plunge Depth*Tilt Angle
To make the above equation more simple…..
We can even ignore the non-significant factors and their
respective interactions.
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46. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

47. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

48. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

49. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

50. Tip Plunge Depth 5
Shoulder Diameter 18
Tilt Angle 1.5
Tool Shape Square
Hold Values
Tool Speed
Feed
46004400420040003800360034003200
30
28
26
24
22
20
>
–
–
–
< 60
60 64
64 68
68 72
72
(HVN)
Hardness
Contour Plot of Hardness (HVN) vs Feed, Tool Speed
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51. Feed 25
Shoulder Diameter 18
Tilt Angle 1.5
Tool Shape Square
Hold Values
Tool Speed
TipPlungeDepth
46004400420040003800360034003200
5.50
5.25
5.00
4.75
4.50
>
–
–
–
–
–
–
< 60.0
60.0 62.5
62.5 65.0
65.0 67.5
67.5 70.0
70.0 72.5
72.5 75.0
75.0
(HVN)
Hardness
Contour Plot of Hardness (HVN) vs Tip Plunge Depth, Tool Speed
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52. Tool Speed 3840
Shoulder Diameter 18
Tilt Angle 1.5
Tool Shape Square
Hold Values
Feed
TipPlungeDepth
302826242220
5.50
5.25
5.00
4.75
4.50
>
–
–
–
–
–
< 63
63 64
64 65
65 66
66 67
67 68
68
(HVN)
Hardness
Contour Plot of Hardness (HVN) vs Tip Plunge Depth, Feed
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53. Feed 25
Tip Plunge Depth 5
Tilt Angle 1.5
Tool Shape Square
Hold Values
Tool Speed
ShoulderDiameter
46004400420040003800360034003200
20
19
18
17
16
>
–
–
–
–
–
< 60.0
60.0 62.5
62.5 65.0
65.0 67.5
67.5 70.0
70.0 72.5
72.5
(HVN)
Hardness
Contour Plot of Hardness (HVN) vs Shoulder Diameter, Tool Speed
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54. Tool Speed 3840
Feed 25
Tilt Angle 1.5
Tool Shape Square
Hold Values
Tip Plunge Depth
ShoulderDiameter
5.505.255.004.754.50
20
19
18
17
16
>
–
–
–
< 65
65 66
66 67
67 68
68
(HVN)
Hardness
Contour Plot of Hardness (HVN) vs Shoulder Diameter, Tip Plunge Depth
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55. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

56. Multi Response Optimization: Hardness (HVN), Tensile Strength (KN/mm²)
Parameters
Response Goal Lower Target Upper Weight Importance
Hardness (HVN) Range 52.270 80.370 1 1
Tensile Strength (KN/mm²) Maximum 0.025 0.184 1 1
Solution
Tensile
Tip Hardness Strength
Tool Plunge Shoulder Tilt (HVN) (KN/mm²)
Solution Speed Feed Depth Diameter Angle Tool Shape Fit Fit
1 3080 30 5.5 19.9993 2 Square 76.3381 0.164552
Composite
Solution Desirability
1 0.867036
Multiple Response Prediction
Variable Setting
Tool Speed 3080
Feed 30
Tip Plunge Depth 5.5
Shoulder Diameter 19.9993
Tilt Angle 2
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57. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

58. Result Validation
TS (OS) H (OS) TS (GS) H (GS)
0.165 73.98 0.103 70.8
0.175 74.55 0.099 68.17
0.152 71.54 0.094 76.03
0.131 59.89 0.109 59.97
0.168 73.98 0.152 62.97
0.141 67.98 0.025 69.8
0.169 74.51 0.1 57.1
0.171 75.45 0.133 70.47
0.157 70.01 0.085 63.9
0.167 75.54 0.08 78.7
0.11 83.25 0.121 67.47
0.152 74.21 0.074 76.83
0.166 76.56 0.063 74.9
0.164 77.25 0.092 52.27
0.161 69.25 0.088 69.53
Optimized Setting (OS) General Settings (GS)
(OS) Optimized Settings of FSW Parameters - as suggested by Minitab Software
(GS) General Settings of Parameters - as normally taken during existing FSW Practice
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59. Two-Sample T-Test: TS (OS), TS (GS)
Two-sample T for TS OS) vs TS GS)
N Mean StDev SE Mean
TS (OS) 15 0.1566 0.0175 0.0045
TS (GS) 15 0.0945 0.0298 0.0077
Difference = μ (TS (OS)) - μ (TS (GS))
Estimate for difference: 0.06207
95% CI for difference: (0.04357, 0.08056)
T-Test of difference = 0 (vs ≠): T-Value =
6.96
P-Value = 0.000 DF = 22
Result Validation of Tensile Strength

60. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

61. Two-Sample T-Test : H (OS), H (GS)
Two-sample T for H (OS) vs H (GS)
N Mean StDev SE Mean
H (OS) 15 73.20 5.20 1.3
H (GS) 15 67.93 7.55 1.9
Difference = μ (H (OS)) - μ (H (GS))
Estimate for difference: 5.27
95% CI for difference: (0.39, 10.15)
T-Test of difference = 0 (vs ≠): T-Value = 2.23
P-Value = 0.036 DF = 24
Result Validation of Hardness

62. Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

63. Results Achieved
Since Calculated error is less than 10%,
Hence simultaneous optimization of
dual-responses for FSW
(of non-similar Al alloys)
is practically validated.
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64. Conclusions
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Mechanical
Properties
Concluding
Observations
Desired Characteristics
Tensile Strength Hardness
Most influencing Impact Factor/
Interaction Type
Two Way Interaction Two Way Interaction
Most considerable Impact
Factor/Interaction
Shoulder Diameter with
Tilt Angle
Tool Speed with Tool
Shape
Prioritization of CPPs done Yes (Refer Slide 35) Ye s (Refer Slide 47)
Mathematical Modeling Yes (Refer Slide 33) Yes (Refer Slide 45)
Software Optimized Values 0.165 KN/mm² 76.3 HVN
Actually Achieved Values (After
Validation)
0.156 KN/mm² 73.19 HVN

65. The research study revealed the following salient outcomes:
• The selected process parameters like tip plunge depth, shoulder
diameter, tool shape, tilt angle, tool speed and feed have
considerable effect on the mechanical properties of the welded
specimen as they results obtained have shown great variations in
values.
• As an independent factor, tool tip plunge depth and tool speed
has been most significant process parameters effecting the
strength and hardness of the weld respectively. With increase in tip
plunge depth and tool speed, the respective tensile strength as
well as hardness declines.
• Two way interaction(s) has emerged to have substantial impact
on tensile strength and hardness of the weld. The impact is even
more than independent and other interaction(s) of process
parameters. It hence justifies the concern of taking into account
multi factors and their interactions approach during the study.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

66. Scope for Future
• Considering impact of certain more CPPs like axial force,
tool geometries and profiles.
• Undertaking more ranges of different process
parameters.
• DoE, a recommended tool for future work to be carried
out.
• Making use of vertical milling machine may be
beneficial to explore further benefits of FSW.
• Research regarding microstructure properties and
TMAZ can be carried out for FSW of dissimilar Al. alloys.
• Weld strength of T joints, lap joints can also be
explored.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

67. References
Research Publications:
[1] Aval, H. Jamshidi, Serajzadeh, S. and Kokabi, A.H. (2011),
“Evolution of microstructures and mechanical properties in similar
and dissimilar friction stir welding of AA5086 and AA6061”, Elsevier,
Material Science and Engineering A528, pp. 8071-8083.
[2] Aval, H. Jamshidi, Serajzadeh, S. and Kokabi, A.H. (2011),
“Theoretical and experimental investigation into friction stir welding
of AA5086”, Springer International Journal Advance Manufacturing
Technology, pp. 52: 531-544.
[3] Aval, H. Jamshidi, Serajzadeh, S. and Kokabi, A.H. and Loureiro, A.
(2011), “Effect of tool geometry or mechanical and microstructural
behaviours in dissimilar friction stir welding of AA5086-AA6061”,
Institute of Materials, Minerals and Mining, Science and Technology
of Welding and Joining, Vol. 16, No. 7, pp. 597-604.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

68. [4] Arbegast, W.J. (2006), “Friction stir welding after a decade of
development”, Welding Journal, NFS center for friction stir processing,
South Dekota School of Mines and Technology, pp. 28-35.
[5] Bakshi, Yash, Singh, Bikram Jit, Singh, Sahib Sartaj and Singla, Rahul
(2012), “Performance optimization of backup power system though Six
Sigma: a case study”, International Journal of Applied Engineering
Research, ISSN: 0973-4562, Vol. 7, No. 11, pp. 1631-1635.
[6] Banwasi, N. (2005), “Mechanical testing and evaluation of high-speed
and low-speed friction stir welds”, Master’s Thesis, Wichita State
University.
[7] Cavaliere, P., Campanile G. and Panella F. (2006), “Mechanical and
microstructural behavior of aluminum alloy sheets joined by friction stir
welding”, International Journal of Machine Tools and Manufacture, vol. 46,
pp. 588-594.
[8] Cavaliere, P., Campanile G. and Panella F. (2006), “ Effect of welding
parameters on mechanical and microstructural properties of AA6056 joints
produced by friction stir welding”, Journal of Materials Processing
Technology, vol. 180, pp. 263-270.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

69. [9] Chen Thai Ping and Lin Wei-Bang (2008), “A study on dissimilar
friction stir welding process parameters in aluminum alloys and low
carbon steel”, International Conference on Smart manufacturing
Application.
[10] Elangovan, K. and Balasubramanian, V. (2008), “Influences of
tool pin profile and tool shoulder diameter on the formation of
friction stir processing zone in AA6061 aluminum alloy”, Elsevier,
Materials and Design 29(2008), pp. 362-373.
[11] Fujjii, H., Lui, L., Maeda, M. and Nogi, V. (2006), “Effect of tool
shape on mechanical properties and microstructure of friction stir
welded aluminum alloys”, Elsevier Materials Science and Engineering
A419, pp. 25-31.
[12] Giloni, A., Seshadri, S. and Simonoft, J.S. (2006), “Robust
analysis of variance: process design and quality improvement”,
International Journal Productivity and Quality Management, Vol. 1,
pp. 306-319.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

70. [13] Joshi, V., Balasubramaniam, K. and Prakash, R.V. (2011),
“Optimization of friction stir welding parameters for AA5083 by
radiography and ultrasonic technique”, IEEE – International Ultrasonic
Symposium Proceedings, 978-1-4577-1252-4/11, pp. 1920-1923.
[14] Lakshminarayanan, A.K. and Balasubramanian, V. (2008),
“Comparision of RSM with ANN in predicating tensile strength of
friction stir welded AA7039 aluminium alloy joints”, Elsevier Tean S.
Non ferrous metal SoC. China 19(2009), pp. 9-18.
[15] Mehra, S., Dhanda, P., Khanna, R., Goyat, N.S. and Verma, S.
(2012), “ Effect of tool on tensile strength in single and double sided
friction stir welding”, International Journal of Scientific and Engineering
Research, vol. 3, issue 11, ISSN 2229-5518.
[16] Muruganandam, D., Sreenivasan, K.S., Kumar R.S., Das, S. and Rao
V.S. (2011), “Study of process parameters in friction stir welding of
dissimilar aluminum alloys”, Proceedings of the 2011 International
Conference on Industrial Engineering & Operations Management, pp.
22-24.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

71. [17] Palanivel, R. and Mathews, P.K. (2012), “Mechanical and
microstructural behavior of friction stir welded dissimilar aluminum
alloy”, IEEE- International Conference on Advances in Engineering
Science and Management, ISBN 978-81-909042-2-3.
[18] Saini, P., Tayal, S.P., Kumar, A. and Kaushik, V. (2013),
“Experimental study of hardness by friction stir welding of 6061-T6
aluminum pieces”, International Journal of Current Engineering and
Technology, vol 3, no. 3, pp. 792-794.
[19] Schmidt, H. N., Dickerson, T.L. and Hottel, J.H. (2006),
“Material flow in butt friction stir welds”, Acta Materialia, vol. 54, pp.
1199-1209.
[20] Shukla, Ratnesh K. and Shah, Pravin K. (2010), “Comparative
study of friction stir welding and tungsten inert gas welding
process”, Indian Journal of Science and Technology, Vol. 3, ISSN:
0974-6846, pp. 667-671.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

72. [21] Singh, A., Sandhu, M. P., Singh, G. and Girdhar, K. B. (2013),
“Effect of rotational speed on tensile strength & micro hardness of
friction stir welded AL2014 and AL5083- aluminium alloy”,
International Journal of Advance Research In Science and
Engineering, IJARSE, vol. no.2, issue no.9.
[22] Singh, Bikram Jit and Khanduja, Dinesh (2011), “Introduce
quality processes through DoE: a case study in die cashing foundry”,
International Journal Productivity and Quality Management, Vol. 8,
No. 4, pp. 373-397.
[23] Singh, Lakshman et.al (2013), “An evaluation of TIG Welding
parametric influence on tensile strength of 5083 aluminium alloy”,
International Journal of Mechanical, Industrial Science and
Engineering, Vol. 7, No. 11, pp. 1278-1281.
[24] Singh, G., Singh, K. and Singh, J. (2011), “Effect of axial force
on mechanical and metallurgical properties of friction stir welded
AA6082 joints”, Journal of Advanced Materials Research, vol. 383-
390, pp. 3356-3360.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

73. [25] Sivashanmugam, M., Ravikumar, S., Kumar, T., Seshagiri R.V. and
Muruganandam, D. (2010), “A review on friction stir welding for
aluminum alloys”, IEEE, 978-1-4244-9082-0/10, pp. 216-221.
[26] Suri, Atul, Prashant, R.S.S. and Raj, K. Hans (2013), “Comparative
study of friction stir welding and tungsten inert gas welding of pure
aluminium”, IEEE, 978-1-4673-6150, pp. 929-935.
[27] Vohra, Gaurav, Singh, Palwinder and Sodhi, Harsimran Singh
(2013), “Analysis and optimization of Boring Process Parameters by
using Taguchi Method”, International Journal of Science and
Communication Engineering, ISSN 2319-7080, pp. 232-237.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)

74. Books:
[28] Degarmo, E.Paul, Blackm, J.T. and Kosher, Ronald A. (2005),
“Material and Process in Manufacturing Prentice Hall of India (P)
Ltd.”, 8th Edition, pp. 965.
[29] Garg, S.K. (2009), “Workshop Technology (Manufacturing
Processes)”, University Science Process, 3rd Edition, pp 77-84.
[30] Gupta, S.P. (2007), “Statistical Methods”, Sultan Chand and
Sons, 35th Revised Edition, pp. 881-951.
[31] Mishra, Rajiv S. and Mahoney, Murlay W. (2007), “Friction
Stir Welding and Processing”, ASM International, No. 05112G.
Department of Mechanical Engineering, Maharishi Markandeshwar University, Sadopur (Ambala)