Experimental Investigations on Repaired AISI 304 A by ...

Experimental Investigations on Repaired AISI 304 A

by Optimized Parameters of Various Welding

Techniques Using Nitinol Wire

A Thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

in

Mechanical Engineering

by

Kavita K. Kripalani

Enrollment No. 179999919024

under supervision of

Prof. (Dr.) Piyush S. Jain

GUJARAT TECHNOLOGICAL UNIVERSITY

AHMEDABAD

[February - 2022]

iii

© Kavita K. Kripalani

iv

DECLARATION

I declare that the thesis entitled Experimental Investigations on Repaired AISI

304 A by Optimized Parameters of Various Welding Techniques Using Nitinol

Wire submitted by me for the degree of Doctor of Philosophy is the record of

research work carried out by me during the period from December 2017 to

February 2022 under the supervision of Prof. (Dr.) Piyush S. Jain and this has not

formed the basis for the award of any degree, diploma, associateship, fellowship,

titles in this or any other University or other institution of higher learning. I further

declare that the material obtained from other sources has been duly acknowledged

in the thesis. I shall be solely responsible for any plagiarism or other irregularities,

if noticed in the thesis.

Signature of the Research Scholar: Date: 28/02/2022

Name of Research Scholar: Ms. Kavita K. Kripalani

Place: Ahmedabad

v

CERTIFICATE

I certify that the work incorporated in the thesis Experimental Investigations on

Repaired AISI 304 A by Optimized Parameters of Various Welding

Techniques Using Nitinol Wire submitted by Ku. Kavita K. Kripalani was carried

out by the candidate under my supervision/guidance. To the best of my knowledge:

(i) the candidate has not submitted the same research work to any other institution

for any degree/diploma, Associateship, Fellowship or other similar titles (ii) the

thesis submitted is a record of original research work done by the Research Scholar

during the period of study under my supervision, and (iii) the thesis represents

independent research work on the part of the Research Scholar.

Signature of Supervisor: Date: 28/02/2022

Name of Supervisor: Prof. (Dr.) Piyush S. Jain

Place: Bardoli, Dist-Surat

vi

Course-work Completion Certificate

This is to certify that Ms. Kavita K. Kripalani, Enrolment No. 179999919024 is a PhD scholar

enrolled for PhD program in the branch Mechanical Engineering of Gujarat Technological

University, Ahmedabad.

She has been exempted from the course-work (successfully completed during M.Phil

Course)

She has been exempted from Research Methodology Course only (successfully completed

during M.Phil Course)

She has successfully completed the PhD course work for the partial requirement for the

award of PhD Degree. His performance in the course work is as follows-

Grade Obtained in Research Methodology

(PH001)

Grade Obtained in Self Study Course

(Core Subject)

(PH002)

BB AB

Prof. (Dr.) Piyush S. Jain

PhD. Supervisor

vii

Originality Report Certificate

It is certified that PhD Thesis titled Experimental Investigations on Repaired AISI 304 A by

Optimized Parameters of Various Welding Techniques Using Nitinol Wire by Kavita K.

Kripalani has been examined by us. We undertake the following:

a. Thesis has significant new work / knowledge as compared already published or are under

consideration to be published elsewhere. No sentence, equation, diagram, table,

paragraph or section has been copied verbatim from previous work unless it is placed

under quotation marks and duly referenced.

b. The work presented is original and own work of the author (i.e. there is no plagiarism).

No ideas, processes, results or words of others have been presented as Author own work.

c. There is no fabrication of data or results which have been compiled / analysed.

d. There is no falsification by manipulating research materials, equipment or processes, or

changing or omitting data or results such that the research is not accurately represented in

the research record.

e. The thesis has been checked using URKUND (copy of originality report attached) and

found within limits as per GTU Plagiarism Policy and instructions issued from time to

time (i.e. permitted similarity index <10%).

Signature of the Research Scholar: Date: 28/02/2022

Name of Research Scholar: Kavita K. Kripalani

Place: Ahmedabad

Signature of Supervisor: Date: 28/02/2022


Place: Bardoli, Dist-Surat.

x

PhD THESIS Non-Exclusive License to

GUJARAT TECHNOLOGICAL UNIVERSITY

In consideration of being a PhD Research Scholar at GTU and in the interests of the

facilitation of research at GTU and elsewhere, I, Kavita K. Kripalani having Enrollment No.

179999919024 hereby grant a non-exclusive, royalty free and perpetual license to GTU on

the following terms:

a) GTU is permitted to archive, reproduce and distribute my thesis, in whole or in part,

and/or my abstract, in whole or in part (referred to collectively as the “Work”) anywhere

in the world, for non-commercial purposes, in all forms of media;

b) GTU is permitted to authorize, sub-lease, sub-contract or procure any of the acts

mentioned in paragraph (a);

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authority of their “Thesis Non-Exclusive License”;

d) The Universal Copyright Notice (©) shall appear on all copies made under the authority

of this license;

e) I undertake to submit my thesis, through my University, to any Library and Archives.

Any abstract submitted with the thesis will be considered to form part of the thesis.

f) I represent that my thesis is my original work, does not infringe any rights of others,

including privacy rights, and that I have the right to make the grant conferred by this non-

exclusive license.

xi

g) If third party copyrighted material was included in my thesis for which, under the terms

of the Copyright Act, written permission from the copyright owners is required, I have

obtained such permission from the copyright owners to do the acts mentioned in

paragraph (a) above for the full term of copyright protection.

h) I retain copyright ownership and moral rights in my thesis, and may deal with the

copyright in my thesis, in any way consistent with rights granted by me to my University

in this non-exclusive license.

i) I further promise to inform any person to whom I may hereafter assign or license my

copyright in my thesis of the rights granted by me to my University in this non-exclusive

license.

j) I am aware of and agree to accept the conditions and regulations of PhD including all

policy matters related to authorship and plagiarism.

Signature of the Research Scholar:

Name of Research Scholar: Kavita K. Kripalani

Date: 28/02/2022

Place: Ahmedabad

Signature of Supervisor:


Principal, S.N.Patel Institute of Technology & Research Centre,

Umrakh, Bardoli.

Date: 28/02/2022

Place: Bardoli, Dist-Surat

xii

Thesis Approval Form

The viva-voce of the PhD Thesis submitted by Kavita K. Kripalani (Enrollment No.

179999919024) entitled Experimental Investigations on Repaired AISI 304 A by

Optimized Parameters of Various Welding Techniques Using Nitinol Wire was

conducted on 28/02/2022, Monday at Gujarat Technological University.

The performance of the candidate was satisfactory. We recommend that he should be

awarded the PhD degree.

Any further modifications in research work recommended by the panel after 3 months

from the date of first viva-voce upon request of the Supervisor or request of

Independent Research Scholar after which viva-voce can be re-conducted by the same

panel again.

The performance of the candidate was unsatisfactory. We recommend that he should

not be awarded the PhD degree.

Dr. Piyush S. Jain

Principal, S.N.P.I.T & R.C,

Umrakh, Bardoli.

Name and signature of supervisor (1) (External Examiner-1)

Dr. Amitava De

(2) (External Examiner-2) (3) (External Examiner-3)

Dr. Kiran C. More Name and signature

(Briefly specify the modifications suggested by the panel)

(The panel must give justifications for rejecting the research work)

xiii

ABSTRACT

Experimental Investigations of various welding parameters of repaired AISI 304A using Design

of Experimentation for optimizing parameter subset of welding by shape memory alloy NiTinol

is done using prominent six joinery methods viz: Tungsten Inert Gas, Micro Plasma, Laser,

Friction Stir, Induction Brazing and Capacitor Discharge and its smart material effect is studied

along with determining repaired properties of Tensile Strength, hardness, pseudo elasticity.

NiTinol alloy in wire form is used for experimentation study. However, unlike other shapes of

NiTinol like powder, plates, tubes and other forms NiTinol in wire form is used for

experimentation as it is favorable for obtaining loading high plateau stress in joineries. The

experimental investigation has been made on optimized parameter study based on DOE and its

computational and simulation validation to find the most fitting range of parameters subset in

these welding processes for NiTinol Wire with and without curing process for most apt method

of Friction Stir welding. Comparative analysis graphically and analytically is made on repaired

part of AISI 304A plate of various joinery methods using Nitinol as filler material to assess the

most apt technique of the repaired strength, yield elongation, hardness and micro grain structure

properties, pool gravity, nugget zone contact study to determine micro grain and valence

structure of NiTinol properties impact on welded component. The study reveals that welding

Nitinol requires utmost calculative parameters control of amperage, voltage, pulse frequency,

pulse duty cycle, secondary current, feed distance, axial force, tilt angle of tool, lens source,

gravity pool of amalgamation, travel speed which plays prominent role varying from process in

determining characteristic weld strength for joint analysis. Optimized with design set up and

tooling, selected most appropriate mechanical joining technique for these welding methods after

comparing with other alternative techniques, which improved the process of repaired welding

through Nitinol and dissimilar metals which were further analyzed. The core weldability

difficulties associated with NiTi were strength reduction, formation of intermetallic compounds,

modification of phase transformation and transformation temperatures as well as changes in both

super elastic and shape memory effects. Welding Nitinol with AISI 304A was a challenge due to

formation of fragile intermetallic components which formed marked loss in tenacity in welded

joints during remelting stage due to solidification cracks associated with dendritic microstructure

of weld metal, along with this precipitation due to phase transformation in thermally affected

zone resulted in loss of mechanical resistance. Friction Stir Welding and Induction Brazing

depending upon its repaired component process and applicability were found more suitable

unlike all other four joinery methods. These two joinery methods parameters further validated by

xiv

computational and simulation to formulate optimum designs of these two processes for NiTinol

wire with 0.00278% bias error feasible in mechanized Friction Stir Welding with retained smart

material feature in welded plate due to formation of epitaxial layer of thin film of NiTinol in

transition at Heat affected zone. The NiTinol welded specimen after tests of surface analysis

determined that partial affected weld zone is 115 µm and heat affected zone of 31-47µin width,

unlike devoid of gravity pull in contact nugget area. Thus, research in welding and its effects on

the joint’s performance has been conducted with a detailed review of welding and joining

processes applied to NiTi, in similar and dissimilar combinations considering both fusion and

solid- state in Micro Plasma arc welding, Micro TIG/Pulsed Arc, Laser & Friction Stir Welding

Manual as well as Mechanized Friction Stir Welding, Induction brazing techniques. The joinery

experimentation done after studying the changes in nugget zone while welding as it depends on

phase diagram of Nitinol and its curing characteristic features. However, negative effects during

welding while using filler material of Nitinol was far extent reduced using post weld heat

treatment procedure in friction stir welding. This Ph.D. thesis will be useful for researchers and

industry domain personnel to cater with the issues and approaches to overcome the problems

faced to form intricate finish joinery by NiTi shape memory alloy on AISI 304A material. The

experimentation which is based on optimized parameter subset exhibiting an overview of

advanced welding development procedure of Friction Stir Welding joining technique will be

useful to understand the methodology so as to retain super alloy characteristic joinery with its

distinct feature.

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Acknowledgement

Embarking journey of persistent work on NiTinol material in my Ph.D. studies, I would

like to bow whole-heartedly and with devotion to Almighty God & Guru Nanak Saheb to

guide me throughout with his eternal grace and my parents Mohini Kripalani, and Kishin

Kripalani who have been the strongest pillar of my life. My work is dedicated to my family

Guru Sant Shree Swami Lilashah Maharaj ji [1880-1973] & Shree Santoshi Maa who has

always blessed me with inner strength of giving self-belief and solace. Without their

blessings, this could not have ever been possible.

I would like to sincerely express my sincere gratitude to my guide, Dr. Piyush. S. Jain,

Principal, Sitarambhai .Naranji Patel Institute of Technology & Research Centre, Umrakh.

His continuous momentum and immense contribution and motivation have made it

possible to complete this endeavor. He is very considerate, inspirational, generous and

straightforward Mentor.

Furthermore, my sincere gratitude goes to my DPC members Dr. Piyush Gohil , Associate

Professor, Faculty of Technology and Engineering Department, M.S University Baroda &

Dr. Vijay Chaudhary, Professor and Head Mechanical Engineering of C.S.Patel Institute of

Technology, Charusat University, Changa for showing me the appropriate path in this

research without their valuable guidance and in depth insights this could not be done with

such considerate.

I am sincerely thankful and obliged to GTU Vice Chancellor Hon. Prof. (Dr.) Navin Sheth

Sir & Respected Registrar Sir Dr. K. N. Kher of GTU.

Finally the last but not the least to everyone who have one or the other way helped in this

research work.

Sant Shree Swami Lilashah Maharaj Saheb.1880-1973

Kavita K. Kripalani

xvi

Table of Content

Abstract…………………………………………………………………………………..xiii

Acknowledgement……………………………………………………………...................xv

List of Figures……………………………………………………………………………xix

List of Tables…………………………………………………………………………..xxviii

List of Abbreviation.…………………………………………………………………….xxx

List of Symbols ................................................................................................................xxxi

List of Appendices……………………………………………………………………..xxxii

CHAPTER – 1 Introduction……………………………………………………...............1

1.1 General .............................................…………………………………………..1

1.2 Schematic Diagram of NiTinol Wire Welding...………………………………2

1.3 Comparative Analysis of Various Joinery Methods.……………......................2

1.4 Comparative Study of Conventional Methods using NiTinol Wire on

AISI 304 of Various Joinery Process..................................................................4

1.5 Overview of Thesis................……………………………………………..……6

CHAPTER – 2 Literature Review…………………………………………………..........9

2.1 State of Art Literature Review......………………………………..…………...9

2.2 Plasma Arc Welding by NiTinol Wire..……………………………..………..9

2.3 Tungsten Inert Gas Welding……………………..………………………….12

2.4 Friction Stir Welding...........………………………………………..……….17

2.5 Induction Brazing............................................................................................23

2.6 Laser Welding ................................................................................................28

2.7 Capacitor Discharge Welding ........................................................................37

2.8 Conclusion of the Literature Review .............................................................41

2.9 Objectives of the Research Work...................................................................42

xvii

2.10 Research Gap and Definition of the Problem...............................................45

2.11 Original Contribution by this Thesis..............................................................45

CHAPTER – 3 Design of Experimentation Techniques………………..…….…........46

3.1 Design of Experimentation......……………………………………..…….......46

3.2 Plasma Arc Welding...……………………………………………..................46

3.3 Tungsten Inert Gas Welding....…………….………………………….…..….49

3.4 Laser Welding .................................................................................................51

3.5 Friction Stir Welding.......................................................................................53

3.6 Capacitor Discharge Welding..........................................................................59


CHAPTER – 4 Experimental Investigations Performing Joinery by NiTinol

Wire on AISI 304 A Plate………………..…….…................................46

4.1 Plasma Arc Welding......……………………………………..……................63

4.2 Tungsten Inert Gas Welding............................................................................64

4.3 Laser Welding..................................................................................................66

4.4 Manual and Robotic Friction Stir Welding......................................................69

4.5 Mechanized Friction Stir Welding...................................................................72

4.6 Capacitor Discharge Welding .........................................................................76


CHAPTER – 5 Simulation Modelling & Analytical Optimization of Parameters....81

5.1 Simulation of Friction Stir and Induction Brazing Repaired Techniques

Based on Comparative Anlysis..……………………………..……................63

5.2 Mechanized Friction.........................................................................................85

5.3 Simulated Modelling of Induction Brazing Welding.......................................90

CHAPTER – 6 Comparative Analysis of Real-Time Parameters for Repaired

xviii

Specimen ................................................................................................95

6.1 Mechanized Friction Stir Welding………………………………..……........96

6.2 Induction Brazing ..........................................................................................102

CHAPTER – 7 Study of Design of Experiments, Simulation & Analytical Results

of Various Joineries and Their Discussions........................................107

7.1 Parameter Validation by Design of Experimentation using Poisson &

Johnson-Cook Model For The Test Run of Welding Later to be

Validated by Computational Method ……………………………..…….......107

7.2 Friction Stir Welding ......................................................................................108

7.3 Induction Brazing.............................................................................................115

7.4 Computational Validation of Optimized Parameters of Friction Stir

Welding and Induction Brazing.......................................................................121

7.5 Simulation Results of Joinery Process.............................................................127

7.6 Comparative Results of Friction Stir Welding and their Discussion...............134

CHAPTER – 8 Conclusion and Future Scope.................………………..…….…........138

8.1 Conclusion from Various Joinery Techniques…………………..……...........139

8.2 Main Concluding Points of Most Apt Joinery Friction Stir Welding...............140

8.3 Future Scope ....................................................................................................142

List of References .............................................................................................................143

List of Publications ..........................................................................................................154

Appendix – I .....................................................................................................................155

Appendix – II ...................................................................................................................159

xix

List of Figures

1. Figure 1.1 Reference CAD Model of Simulated Laser Welding by

Nitinol Wire.

3

2. Figure 2.1 Plasma Arc welding Reference Image courtesy by

Unbox Factory, different types of welding

10

3. Figure 2.2 Microstructure content of NiTi welded cross section 13

4. Figure 2.3 Scanning electron Microscope images shows fracture

structure of welded AISI 304 by TIG Welding

14

5. Figure 2.4 Potential (mV vs SCE) and Current density 15

6. Figure 2.5 (a) Curves of base metal & Weld metal with diff % Ni

in Ar gas (b) Specimen welded bead using speed lower than 2

mm sec-1, results observed on face side, root side and welded

cross section respectively in a, b, c

16

7. Figure 2.6 Weld Geometry at various power output 16

8. Figure 2.7 Tensile strength, hardness, and impact toughness graph

of Martensite steel joinery

17

9. Figure 2.8 Friction stir welding: probability for various

mechanical properties

18

10. Figure 2.9 Total deformation and temperature profile and tensile

test graph of 4mm and 6mm

18

11. Figure 2.10 Longitudinal stress (a) FSW & (b) SSFSW 19

12. Figure 2.11 Temperature Maps (a) FSW & (b) SSFSW 20

13. Figure 2.12 Microstructure for grain interior and along grain

boundary (a) base Metal (b) H HAZ (c) TMAZ near HAZ and

(d) TMAZ near nugget zone with different parameter

20

14. Figure 2.13 Distance from weld cente 21

15. Figure 2.14 150 Tons Mechanized Linear Friction image courtesy

from website

21

16. Figure 2.15 (a) Welding with NiTi and SS weld (b) EDS

Composition

22

xx

17. Figure 2.16 Wt. and differences of different material 22

18. Figure 2.17 Binary Diagram of Ni and Ti 23

19. Figure 2.18 Quasi binary eutectic system 24

20. Figure 2.19 Time resolved brazing microstructure at 120 seconds 24

21. Figure 2.20 Temperature profile of Induction Brazing 25

22. Figure 2.21 NiTinol Wire heating image courtesy from website 26

23. Figure 2.22 NiTinol Wire heating’s susceptibility for MRI Scan 26

24. Figure 2.23 Stress-strain surface temperature for NiTi at various

temperature

27

25. Figure 2.24 Joint Design and Brazing of Cemented Carbide WC-

Co and Steel

28

26. Figure 2.25 Surface magnetic flux density at room temperature

image courtesy LANTHA TECH

29

27. Figure 2.26 Parameter for Magnetic flux by LANTHA TECH 30

28. Figure 2.27 Microstructure of NiTi-304 laser welded at HAZ and

FZ zone

30

29. Figure 2.28 Peak Strain 31

30. Figure 2.29 Bend Test K10 specimen (b) Bending K4 33

31. Figure 2.30 Multiple plateau of laser welded specimen 33

32. Figure 2.31 DCS scan of wires in different conditions 35

33. Figure 2.32 2D XRD frame gathered at 1D11 beamline of ESRF

from wires

35

34. Figure 2.33 Exploded diagram of NiTi/304SS pilot weld 36

35. Figure 2.34 (b) Pilot joint weld (c) Laser welded 36

36. Figure 2.35 Temperature profile at 36 J heat for 1.31ms welding

time

37

37. Figure 2.36 CD Weld deposited on Fe3Al 37

38. Figure 2.37 Tip length of 1.4 mm Capacitor discharge welding 38

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process used to join 6.35 mm Fe3Al solid cylinders with 100V

39. Figure 2.38 Characterization of capacitor discharge welding

process and simulation

39

40. Figure 2.39 Simulation results of temperature T distribution at

t=0.75ms

39

41. Figure 2.40 Electrical voltage of different contacts 40

42. Figure 2.41 Micro hardness test of welded NiTi and steel tube by

Micro Electron beam welding without filler material

40

43. Figure 2.42 Welding with NITinol wire 43

44. Figure 2.43 Flow chart of research work 44

45. Figure 2.44 Publications statistics in the world 44

46. Figure 3.1 Schematic Diagram of Plasma Arc Welding 47

47. Figure 3.2 Taguchi Analysis: Tensile Strength vs Ampere &

Voltage of PAW

48

48. Figure 3.3 Response Table for Signal to Noise ratio for PAW 48

49. Figure 3.4 Empirical Cumulative Distribution Function of

Ampere of PAW

49

50. Figure 3.5 Surface Plot of PAW 49

51. Figure 3.6 Schematic Diagram of Tungsten Inert Gas Welding 50

52. Figure 3.7 DOE of TIG 50

53. Figure 3.8 Surface Plot of TIG 51

54. Figure 3.9 Schematic diagram of Laser Welding by NiTinol Wire 52

55. Figure 3.10 CDF Empirical for Laser welding by NiTinol wire 52

56. Figure 3.11 Surface Plot of Laser Welding by NiTinol Wire 53

57. Figure 3.12 Schematic Diagram of Friction Stir Welding 53

58. Figure 3.13 DOE of FSW 54

59. Figure 3.14 Empirical CDF of FSW 54

60. Figure 3.15 Surface plot of RPM v/s Upset Force v/s Hot Rolled 55

xxii

61. Figure 3.16 Surface Plot of FSW 55

62. Figure 3.17 Upset time v/s Upset force 56

63. Figure 3.18 SN ratio v/s Ampere 56

64. Figure 3.19 Statistical analysis for models 57

65. Figure 3.20 Response table for standard deviations 57

66. Figure 3.21 Estimated model coefficients for means 57

67. Figure 3.22 Response table for means 58

68. Figure 3.23 Estimated model coefficient for standard deviations 58

69. Figure 3.24 Schematic Diagram of Capacitor Discharge Welding 59

70. Figure 3.25 Capacitor Discharge Welding DOE 60

71. Figure 3.26 Empirical CDF of CD Welding 60

72. Figure 3.27 Surface Plot of CDW 61

73. Figure 3.28 Induction Brazing 61

74. Figure 3.29 Empirical CDF of IB 62

75. Figure 3.30 Surface plot of temperature v/s frequency v/s power 62

76. Figure 4.1 Plasma arc welded 304 plates with NiTinol wire 64

77. Figure 4.2 Laboratory photograph 65

78. Figure 4.3 Computerized Compression Testing Machine 66

79. Figure 4.4 Lab experiment photograph 66

80. Figure 4.5 Laser welding machine 67

81. Figure 4.6 Laser welding machine setup 68

82. Figure 4.7 Laser welded specimen 68

83. Figure 4.8 NiTinol Wire 69

84. Figure 4.9 NiTinol wire welded 69

85. Figure 4.10 Schematic Diagram of Friction Stir Welding 70

xxiii

86. Figure 4.11 CAD Model of FSW using Grab CAD 70

87. Figure 4.12 Experimentation on Lathe Machine 71

88. Figure 4.13 FSW AISI 304 A with NiTinol Wire 71

89. Figure 4.14 Robotic/Mechanized Friction Stir Welded Specimen 72

90. Figure 4.15 CAD Model showing the path of the welding 72

91. Figure 4.16 Experimentation on AISI 304 plate with NiTinol

Wire

73

92. Figure 4.17 CAD Model 73

93. Figure 4.18 Simulation model of welded specimen 74

94. Figure 4.19 Grain Structure 74

95. Figure 4.20 Grain Structure 75

96. Figure 4.21 Simulation software for welding 76

97. Figure 4.22 Capacitor Discharge 76

98. Figure 4.23 NiTinol welded specimen with rivets 77

99. Figure 4.24 Induction Brazing Machine 78

100. Figure 4.25 Induction Brazing specimen 78

101. Figure 4.26 Micro grain structure of the welded specimen 79

102. Figure 5.1 Simulated Models of Friction Stir Welded plate by

NiTinol wire engulfed to Stud by Lathe Machine (a)

81


NiTinol wire engulfed to Stud by Lathe Machine (b)

82


NiTinol wire in four orientation axis to capture weld penetration

82


NiTinol wire shows nugget zone of specimen

83

106. Figure 5.5 Mesh analysis with brown spot with traces of NiTinol 83

107. Figure 5.6 Surface texture of repaired AISI 304 with NiTinol 84

xxiv

108. Figure 5.7 Matlab Simulation for stress analysis of welded joint

(a)

84

109. Figure 5.8 MATLAB Simulation for stress analysis of welded

joint (b)

85

110. Figure 5.9 Simulation of specimen welded by Mechanized

Friction Stir Welding (a)

85

111. Figure 5.10 Simulation by Mechanized Friction Stir Welding (b) 86

112. Figure 5.11 Simulation by Mechanized Friction Stir Welding (c) 86

113. Figure 5.12 Simulation by Mechanized Friction Stir Welding:

mesh analysis with orange line stress zone

87


NiTinol wire engulfed to Stud by Mechanized Machine (e): mesh

analysis with orange line stress zone

87

115. Figure 5.14 Mesh analysis & UV texture map of repaired AISI

304 with NiTinol by Mechanized FSW: red area shows stress

depicting weld flow at HAZ

88

116. Figure 5.15 Mesh analysis of weld flow & UV texture map of

repaired AISI 304A with NiTinol by Mechanized FSW

88

117. Figure 5.16 Surface texture at fusion zone with frictional

resistance

89


304 with NiTinol by Mechanized: dark layer shows

amalgamation

89

119. Figure 5.18 Mesh analysis of amalgamation zone 90

120. Figure 5.19 Mesh analysis of amalgamation zone & UV texture

map of repaired AISI 304 with NiTinol by Mechanized

90

121. Figure 5.20 Simulated Models of Induction Brazed Welded plate

by NiTinol wire: nugget area (square) portion shows uneven weld

flow

91

122. Figure 5.21 Simulated Models of Induction Brazed Weld: stress

concentration is more in starting and reduced as it advances

91

123. Figure 5.22 Simulated Models of Induction Brazed Weld: mess 92

xxv

analysis of stressed zone


304 with NiTinol by Induction Brazing: mess analysis of stressed

zone

92


304 with NiTinol by Induction Brazing: camera capture of

surface texture (a)

93


304 with NiTinol by Induction Brazing: camera capture of

surface texture (b)

93

127. Figure 6.1 Multiple regression for V1 summary report 98

128. Figure 6.2 Multiple regression effect report 99

129. Figure 6.3 Multiple regression for V1 model building report 100

130. Figure 6.4 Multiple regression for V1 Prediction and

Optimization report

100

131. Figure 6.5 Box plot of V1 by rpm, mm/s, diagnostic report 101

132. Figure 6.6 Box plot of V1 by rpm, mm/s, broken down report 101

133. Figure 6.7 Before/after Poisson capability Comparison for center

pt. v/s stdorder_1

102

134. Figure 6.8 Induction brazing by Nitinol wire 103

135. Figure 6.9 Screening design 104

136. Figure 6.10 Paired test for the mean of V0 and V1, summary

report

104

137. Figure 6.11 Paired test for the mean of V0 and V1, diagnostic

report

105

138. Figure 6.12 DOE of Real-time parameters welding by calculation

and camera captured the flow of weld (a)

106

139. Figure 6.13 DOE of Real-time parameters welding by calculation

and camera captured the flow of weld (b)

106

140. Figure 7.1 Chi-square test for Nitinol wire by Temperature 108

xxvi

141. Figure 7.2 Poisson process capability report for rpm 109

142. Figure 7.3 Johnson transformation for V0, rpm, mm/s 110

143. Figure 7.4 Before/after Poisson capability comparison for run

order vs 1, diagnostic report

110


order vs 1, summary report

111

145. Figure 7.6 Poisson capability analysis for f 111

146. Figure 7.7 Probability plot for rpm 112

147. Figure 7.8 Before/after Poisson capability comparison for centre

Pt v/s Std Order_1

112

148. Figure 7.9 Main effects plot for signal 113

149. Figure 7.10 Main effect plot for signal (b) 113

150. Figure 7.11 Contour plot of Power v/s Operating Current, Max.

Coating thickness

114

151. Figure 7.12 Surface plot of RPM v/s Upset force v/s Hot rolled % 114


order vs 1

115

153. Figure 7.14 Johnson transformation for power 116

154. Figure 7.15 Formation for current density in coil 116

155. Figure 7.16 Fit linear model for V3.1 117

156. Figure 7.17 Interaction plot for signals 117

157. Figure 7.18 Interaction plot for signals (b) 118

158. Figure 7.19 Contour plot of Std Order vs f, j 118

159. Figure 7.20 Surface plot of STd Order v/s f, j 119

160. Figure 7.21 Graphical Comparison of Six Welding Process based

on Joint Analysis

125

161. Figure 7.22 Simulation result 125

162. Figure 7.23 Simulation result (b) 127

xxvii

163. Figure 7.24 Simulation result (c) 127

164. Figure 7.25 Simulation results (d) 128

165. Figure 7.26 Surface plot 128

166. Figure 7.27 Surface plot (b) 129

167. Figure 7.28 Graphical analysis based on comparative analysis 130

168. Figure 7.29 Residual’s v/s fitted values and observation order 132

169. Figure 7.30 Multiple regression for current dens 132

170. Figure 7.31 Comparative analysis of all three methods for FSW &

IB for block 1 and block 2

133

171. Figure 7.32 NiTinol & AISI 304A Stress-Strain Curve for FSW 133

172. Figure 7.33 Comparative analysis of FSW Experimental,

Analytical & Simulation Data Parameter With bias error

136

173. Figure 7.34 Comparative analysis of Parameter subset 137

174. Figure 7.35 Comparative analysis of properties of optimum four

welding processes from six processes

137

xxviii

List of Tables

1. Table 2.1 Basic physical and mechanical properties of NiTinol

and 304 steel

13

2. Table 2.2 TIG Welding Parameters for Experimentation. 15

3. Table 2.3 Ultrafine grained microstructure 21

4. Table 2.4 Summary of Laser Operating Parameter 32

5. Table 3.1 Characteristic Properties of NiTinol and 304 steel 47

6. Table 4.1 Parameters for Plasma Welding 64

7. Table 4.2 Parameter set by DOE 65

8. Table 4.3 Parameter set based on DOE 67

9. Table 4.4 Laser Nd: Yag Welding Machine specifications 67

10. Table 4.5 Welding parameters 72

11. Table 4.6 Parameters set by machines 75

12. Table 4.7 Parameters for welding machine 77

13. Table 4.8 Parameters for Induction Brazing 79

14. Table 6.1 Coded Co-efficient 96

15. Table 6.2 Robotic Friction real-time parameters 97

16. Table 7.1 Basic Properties of AISI 304 A & NiTinol 108

17. Table 7.2 DOE Parameter comparison for FSW and IB 119

18. Table 7.3 Parameter Exponential by Poisson’s Method 120

19. Table 7.4 Induction Brazing DOE t value and p-value 121

20. Table 7.5 Mechanized & Manual Friction Stir Welding DOE t

value and p-value

121

21. Table 7.6 Analytical Comparative analysis of Experimental

Data Parameter

129

xxix

22. Table 7.7 Micro grain Structure of Joinery Method to determine

shape memory alloy features

129

23. Table 7.8 Comparative analysis of computational simulation

linear regression with experiment value of FSW

131

24. Table 7.9 Analytical Comparative analysis of Experimental

Data Parameter

134

25. Table 7.10 Friction Stir Computational Validation based on

Research Paper

135

xxx

LIST OF ABBRAVIATION

SR.NO. ABBREVIATIONS FULL FORM

1 FSW Friction Stir Welding

2 PAW Plasma Arc Welding

3 IB Induction Brazing

4 TIG Tungsten Inert Gas

5 CD Capacitor Discharge

6 Laser Welding Light amplification by stimulated emission of radiation

7 Af Austenite Finish Temperature.

8 NiTinol Nickel & Titanium alloy

9 AISI 304 A Austenitic chromium-nickel stainless steel

10 DOE Design of Experimentation

11 Ar gas Argon Gas

12 CDF Cumulative Distribution function

13 RPM Revolution per minute

14 SN Ratio Signal Noise Ratio

15 CAD Computer Aided Design

16 UV Texture Ultra Violet Texture

17 Al Aluminium

18 Mg Magnesium

19 Zn Zinc

20 Co Cobalt

21 EDS Energy dispersive X ray spectrometer

22 ASME American Society of Mechanical Engineers

23 Nd: YAG Neodymium-doped Yttrium Aluminium Garnet

24 MS Mild steel

25 PID Proportional Integral Device (three controller)

26 A Ampere

27 KN Kilo Newton

xxxi

LIST OF SYMBOLS

SR.NO. SYMBOL NAME

1 µ Micron

2 δ Delta

3 Π Pi

4 λ Lambda

5 σ Sigma

6 τ Tau

7 υ Upsilon

8 Ψ Psi

9 ξ Xi

xxxii

APPENDIX

APPENDIX-I: Lab Reports

APPENDIX-II: Calculations

INTRODUCTION

1

CHAPTER 1

INTRODUCTION

1.1 General

Emerging Trends in Subtractive Manufacturing joinery on repaired AISI 304A by

NiTinol wire is finding its prominence due to a greater amount of precision and

pseudo elasticity being one of the prominent factors. NiTinol constituents of an

equiatomic alloy of nickel and titanium. Nickel Titanium alloy is an expensive

material possesses unique functional characteristic features like shape memory, the

effect of pseudo elasticity, stiffness, dampness, corrosion-resistant biocompatibility

which make its conventional use in various joinery methods on the plate of AISI 304

A/L. Amongst the various shape memory alloys, NiTinol is the most commonly used

in medical, automotive sector-specific.

However, joining by Nitinol is difficult because of its high reactivity and ductility

with dissimilar material. This restricts its usage in the joinery domain and makes it

supplement. D u e t o its substantial distinct quality of shape memory and restoring large

strain of almost 8% by unloading and heating, if the proper methodology is used to

join with this unique material without detrimentally affecting its properties such as

curing and autoclave. The study of micro structural properties of NiTinol and

influencing factors on the transformation temperature of NiTinol, its uniqueness can be

revived thus the welding procedure making it useful as a filler material in joinery.

NiTinol is available in various shapes and grades in the forms of Tubes, Rods, Wires,

Powder form, but for welding usually, powder and wire form is preferable. However,

there are various methods by which NiTinol is made like Casting and Powder

Metallurgy. Near Net device with limitations like complexity in resulting parts and

controlling size and shape of porosity is preferred. However, additive manufacturing is

gaining substantial attention for manufacturing NiTinol as they overcome challenges

as these processes rely on CAD data. This method uses either powder bed-based

INTRODUCTION

2

technologies like Selective Laser Melting (SLM) or Laser Engineered Net Shaping

(LENS). The powder form of the method is suitable to make NiTinol in powder form

such as water atomization, gas atomization, hydriding, mechanical attrition. Welding

by Stainless steel is a widely used material in medical for implants and surgical

instruments, aeronautical domain to name specifically. Since it is expensive and it has

poor machinability, the increased demand for dissimilar welding of NiTinol

components to steel components leads to the intermetallic formation of titanium and

iron which causes cracks and thus making inferior joint strength due to its brittle phase.

However, sound welds without the presence of any crack can be produced by using

methods like curing, using super elastic Nitinol by providing good quality weld seams

with accuracy in arc/beam alignment, controlling the level of dilution in the weld

metal. The austenite stainless steel plate 304 L is initially electric arc melted, with

refinement to homogeneity and purity yields minimal voids with surface roughness

less than 7 micro inches.

1.2 Schematic Diagram of Nitinol Wire Welding

Figure 1.1 depicts the schematic representation of NiTinol wire welding and then

checking the joint strength by Camera Vision for one of the experimented joinery

technique so as to demonstrate that tool setup also plays an important role in joint

strength with NiTinol wire. The research study reveals that NiTi to NiTi similar

welding when done near Heat Affected Zone, hardness is minimum near the fusion

line as there is grain growth which substantially increases towards base metal, whereas

unlike to dissimilar metal of AISI 304, it shows the increased hardness value due to

its fine structure and microstructure homogeneity at weld zone.

1.3 Comparative analysis of Various Joinery Methods by NiTinol Wire and

Problem Definition

With various parameters of travel speed, feed, depth, sheet thickness, preheated,

Cured. In this section, the comparison of various methods is done after in-depth

research of literature study, from books, ASTM Journals, and available databases of

the web. The comparison is done in tabular and graphical mode for research done

and my work in this reference. The quality of weld varies depending on the size of

the Plate, heat input source so for experimentation the dimension of AISI 304 A plate

is kept to some extent the same.

INTRODUCTION

3

Figure 1.1 Reference CAD Model of Simulated Laser Welding by Nitinol Wire.

1.4 Comparative Study of Conventional m e t h o d & using NiTinol Wire on

AISI 304 of Various Joinery Process

Sr. No.

Method of

Welding

Conventional Method

Description (1-13)

Joinery Method on AISI 304 by NiTinol Wire

1. Plasma Arc

/Pulsed Arc

Welding

Method

Arc is formed between the

pointed tungsten electrode and

304 A Steel/work piece.

Three operating modes can be

produced by varying bore

diameters. and varying bore

The plasma arc is operated with

DC, with a dropped

characteristic power

source.

A pilot arc is formed between

welds, which results in electrical

interference.

The electrode comprises tungsten

having 2% thoria with plasma

nozzle is of copper, wherein its

tip diameter is made around 30-

60 degrees.

Modular Plasma/TIG

welding machine with

Comfort 2.0 P control.

Plasma and pulsed TIG

welding up to the kHz range

allow a high welding speed

with minimal heat input using

a constricted arc.

Plasma welding current

adjustable in 0.1 A

increments Pilot arc current

adjustable in 0.1 A increments

between 2–15 A. The pilot

arc current can be adjusted at

four operating points during

the welding process

(beforehand, during, and the

following welding, as well as

INTRODUCTION

4

during pauses in welding)

Non-latched/latched

operation Spot welding/tack

function (spot Arc/spot matic)

Spotmatic – reduce the time

required for tacking by up to

50% (TIG only)

Adjustable up-slope and

down- slope time

3.5 m mains supply lead with

16 A shock-proof plug.

It comprises high welding

speed with in-depth

penetration.

2. TIG Welding

Method

Zero contact process welding

utilizes an electric arc struck

between a tungsten electrode

and target component in an inert

atmosphere.

The filler material can be added

separately to the weld pool.

Closed-loop linear power

supplies apply for maintaining

precise arc generation.

Factors like duration of weld

and amplitude produce effective

changes in heating pattern and

control in the welding process.

Produces weld with a non-

consumable tungsten electrode.

It is operated with DC or AC,

with a constant current power

source.

Pure Tungsten with 1to 4 %

thoria with alternative additives

like lanthanum oxide and cerium

oxide are used to enhance its

performance.

In DC electrode is connected to

negative polarity and positive to

work piece.

Fusion-based processes with

reduced thermal affected

regions are provided.

For a total of 600 cycles, 4-8

% strain can be imposed

without rupture.

It is an inexpensive process

and is simple to operate in

the industrial environment.

Low heat input.

Good quality

joints.

INTRODUCTION

5

3. Laser Welding LASER welding uses a

concentrated beam of light on a

very small spot so the

underneath area absorbs light

and becomes energetic.

Solid-state Fiber and Gas Lasers

are mostly used as Lasers in

Laser Machine, which is supply,

by use of Optical fibers.

It is often used in combining

with arc welding forming

Hybrid Arc Welding using any

processes like MIG, TIG, or

SAW using deep penetration

Laser Welding, which can be

automated using CAD/CAM

setup.

No electrode is used and no tool

wear is formed with very

specific targeting getting very

high-quality weld.

This welding method does

not depend on the use of

melting wire, as the arc is

established within work

piece and non- consumable

electrode.

This welding results in steep

weld zones comparative to

arc welding resulting in

smaller welding spots with

in-depth penetration using

Nd-YAG laser unlike CO2

Laser as in the plasma

shielding effect is very much

less due to short wavelength.

The width of 200 µm, with

power, is raised from 0.6 to

0.9 KW, wherein thermal

stresses play a crucial role.

For Stainless Steel, the

extensive reaction takes

place on the steel plate side

resulting in poor strength and

ductility because of

transversal cracks.

Energy input is maximum.

The penetration of the weld

is in-depth.

4. Friction Stir

Welding

The process of friction stir

welding applies a non-

consumable tool with frictional

force by rotating tool in chuck

and mandrel respectively and

plunged into the interface and

frictional heat resulting in

material to heat and soften,

wherein the rotating tool

mechanically mixes the softened

material resulting in solid-solid

bond.

With the increase in spindle

speed, weld time increases due

to burning off the length.

Heat Treated and cold rolled

Ni- rich Nitinol material is

deformed by detaining with

reduced latent heat and

broadening temperature at

which transformation takes

place with Af temperature in

the range of -5ºC to +5 º C

Soft Force, Friction force &

Upset force plays prominent

parameters governing the

strength of the weld.

With the increase in spindle

speed more refined grain

structure with increased

hardness and tensile strength

INTRODUCTION

6

in welded structure.

5. Induction

Brazing

Usually, the specification of the

machine is of ranges from

handheld heating to the

Induction Machine ranging in

the power of generally from 300

KW- 30 KW.

Its applicability is found in

optical cable manufacturing

company repair due to enhanced

productivity and efficiency in

the manufacturing process.

Specification used:

Power:160KW

Frequency:18-

25KHZ

Current:230A

Voltage:3-phase

380V- 50/60HZ

The joinery is done in

presence of an argon

atmosphere for 20-

60 seconds. Exhibits good

wetting within AISI plate

and NiTinol wire used as

filler material after treated by

curing for the 20s, which

creates homogeneous

bonding region.

Tensile strength up to 250

MPa was achieved.

6. Capacitor

Discharge

Welding

CDW allows welding small

diameter studs on the base

plate, which utilizes short

welding time. The weld cycle

time varies from 0.01 seconds to

1 second.

It possesses the distinct

advantage of minimal heat

buildup with minimal distortion.

It utilizes a capacitor storage

system producing electrical

discharge using the Contact and

Gap technique.

Stud with projection or ignition

tip is used, wherein ignition tip

is considered more precise.

Welding Range: -2-10

mm Stud length range:31

mm Hand Tool length-

201 mm Cable length-3

meters Hand Tool

Length-1.9 Kg. Power

Supply 120 V

Charge range 80 VDC to

200 VDC. With the increase

in pressure, weld heat is

reduced and weld strength is

increased. Tensile Strength

up to 524.55 N/mm2 is

obtained. Preheating, thicker

material, increasing stud area

are major factors affecting

weld strength by NiTinol

Wire.

1.5 Overview of Thesis

The work is bifurcated into eight chapters to present the outcome and overview of the

research work.

INTRODUCTION

7

Chapter 2 describes the literature survey for all joinery methods using NiTinol wire

with different similar as well as dissimilar materials assessing the parameters

involved and determining repaired strength, microstructure change of NiTinol. A

literature survey assesses all available potential joinery methods for NiTinol wire. The

research gap is identified and the problem is also defined. Research objectives are

also identified, and the research work which would contribute to the present original

work is discussed.

Chapter 3 details the design of the experimentation technique implied for finding the

optimum parameters to check before performing butt weld on AISI 304 plate by using

NiTinol. F iller material used by six selected joinery methods viz: Plasma Arc, TIG,

Laser, Friction Stir, Induction Brazing & Capacitor Discharge Welding for NiTinol

wire discussed. The graphical analysis of various parameters like temperature, rpm,

tool tilt angle, etc. have been judged by Poisson Johnson- Cook Model & Surface

plotting to choose the most susceptible parameter range for each selected joinery

method.

Chapter 4 presents the assessment of selected parameters of six technologies and

methodology adopted for curing NiTinol wire for retaining pseudo elastic and shape

memory characteristic feature by studying grain structure and EDS.

Chapter 5 details simulation modeling of optimum two methods amongst the six

selected joinery methods: Friction Stir Welding and Induction brazing which give

optimum results amongst other joinery methods. This chapter incorporates the

modeling done by MATLAB, Simulated Annealing software & Blender software of

joined specimens at different parameters range. The characteristics features of Friction

Stir Welding and Induction brazing of the selected process are analyzed by the

algorithm. The simulation results of Friction Stir Welding and Induction Brazing at

different optimum parameters are discussed. The feasibility and effectiveness of

various parameters of these joinery methods are verified by simulation results.

Chapter 6 presents the real-time parameters for comparison of repaired specimen . The

tensile strength, hardness, pseudo elasticity properties concerning speed, feed, depth,

current density range curves of CDF demonstrated of optimum two joinery methods

on the module output are analyzed. In addition, the comparisons of these mentioned

welding parameters are analyzed.

INTRODUCTION

8

Chapter 7 deals with experimentation results presented after verification by

numerical assessment for FSW & Induction Brazing joinery methods by 2nd

Polynomial algorithm at various modes of parameter testing with comparative results

of DOE, Simulation & analytical finding the bias error so, as to arrive with suitable

range for selected joinery.

Chapter 8 finally depicts the summary with concluding remarks and the future scope

of this research work.

LITERATURE REVIEW

9

CHAPTER 2

LITERATURE REVIEW

2.1 State of the art Literature Review

This chapter describes the research work done on various methods of joinery using NiTinol

wire on AISI 304 plate along with the analysis of its dependences on various parameters

for tensile strength and hardness for repaired base material. This chapter comprises review

of literature survey of six welding methods namely Plasma Arc, Tungsten Inert Gas

Welding, Laser, Friction Stir, Induction Brazing and Capacitor Discharge welding which

are bifurcated in six joinery techniques respectively. The literature review is done by first

presenting the principle of these six joining techniques along with the difficulties faced

while joining by NiTinol wire and their applicability in the sectors like medical,

manufacturing industry, aviation and many more. Optimization of parameters by Taguchi

method for Additive Manufacturing and subtractive manufacturing using NiTinol Wire

were studied which explores that quality of weld repair depends primarily on the type of

NiTinol shape in the form of rods, tubes, wire or powder. The base material, speed, feed,

type of welding is also studied. Finally, at the end of this chapter, the research gap is

identified and objectives of the present work have been stated.

2.2 Plasma Arc Welding by NiTinol Wire

Plasma arc welding is a liquid state process of metal joining using Plasma as ionized gas.

Arc is formed between the plate and constricted nozzle using NiTinol wire as filler

material. Temperature maintained is around 2000°C. The basic drawback of welded

specimen by this method is formation of toxicological effects. The study of corrosion

behavior of Nitinol in the repaired base material after weld is of critical importance because

of the known toxicological effects of nickel manufactured commonly from casting, powder

metallurgy with vast challenges in heat treatment during joineries [1]. The effect of the

Mechano-chemical treatment on structural properties of the matrix and surface layer of the

LITERATURE REVIEW

10

drawn TiNi-based alloy wire optimized by Taguchi method DOE analysis is studied to

understand the phenomena of toxicological. However, the research over additive

manufacturing and subtractive manufacturing by NiTinol wire explores that quality of

weld repair depends primarily on type of NiTinol shape whether it is in the form of rods,

tubes, wire or powder form along with base material, speed, feed, type of welding which

are also important. The crux of research gap of reviewed literature survey and the objective

of current work states the methodologies to curb it. For this process, a range of samples

were prepared using different drawing and etching procedures to remove these toxicological

defects. From the results, it was obtained that the fabricated samples showed a composite

structure comprising the complex matrix and textured oxycarbonitride spitted surface

layer. The suggested method of surface treatment increased the surface roughness for the

enhanced bio-performance and better in-vivo integration additive manufacturing is

considered as prominent method due to relatively low expense [2]. Plasma gas from

constricted beam as shown in figure 2.1 was adopted for performing straight shape setting

on commercially available austenitic Nitinol thin wires, at different power levels, which

was moved along the wire length for inducing the functional performances.

Figure 2.1 Plasma Arc welding Reference Image courtesy by Unbox Factory, different

types of welding

Calorimetric, pseudo-elastic and microstructural features of the plasma-annealed wires

were studied through differential scanning calorimetry which revealed tensile testing and

LITERATURE REVIEW

11

high-energy X-ray diffraction. Challenge faced in joining by this technique is

amalgamation in HAZ zone and transition temperature of Austenite to Martensitic phase of

NiTinol is high, therefore it is difficult for spatter free joinery. It can be stated that the

plasma technology can induce SE Itn thin Nitinol wires: the wire performance can be

modulated as in function of the laser power and improved functional properties are

obtained. However, half bead welding method is more favorable in nuclear reactors

pressure repair [3] with the purpose of catheter improvement made by NiTi super elastic

wire which purportedly used in lieu of standardized 304 wires. This process of PAW has

limitation in process characteristic that at minimal heat input results into negative change

of NiTi leading to degrading usability hence NiTi+304 AISI heterogeneous welds find its

limitation. However, for PAW, the properties of welding feature can be enhanced by using

different types of material similar to dissimilar combination, product designing and

welding technique [4] fatigue behavior of additively manufactured (AM) NiTi (i.e. Nitinol)

specimens and compared results to the wrought material. Automized PAW specimen can

be further enhanced by finishing using additive manufacturing technique wherein

components are fabricated using a sliced CAD model based on the desired geometry. NiTi

rods can also be used apart from NiTinol wire for PAW which is fabricated using Laser

Engineered Net Shaping (LENS) and Direct Laser Deposition (DLD) AM technique. Due to

the high plateau stress of the as-fabricated NiTi, all the PAW specimens are heat- treated to

reduce their plateau stress, close to the one for the wrought material. Two different heat

treatment processes, resulting in different stress plateaus, are employed t o b e able to compare

the results in stress- and strain-based fatigue analysis.

Strain controlled constant amplitude pulsating fatigue experiments were conducted on

heat- treated AM NiTi specimens at room temperature (~24°C) to investigate their cyclic

deformation and fatigue behavior. SEM revealed the presence of microstructural defects

such as voids, resulting from entrapped gas or lack of fusion and serving as crack initiation

sites, to be the main reason for the shorter fatigue lives of PAW NiTi specimens.

However, the maximum stress level found to be the most influential factor in the fatigue

behavior of super elastic NiTi. The stability of NiTinol primarily relies on TiO2 layer [5].

Also, as in laser welding process, microstructure and anti wear property of laser cladding

Ni– Co duplex coating on copper examined by Yivong Wang et al. [6].

Ni–Co duplex coatings were cladded onto Cu to improve the anti-wear properties of Cu

products. Prior to laser cladding, n-Al2O3/Ni layers were introducing as interlayers

between laser cladding coatings and Cu substrates to improve the laser absorptivity of

LITERATURE REVIEW

12

these substrates and ensure defect-free laser cladding coatings. The structure and

morphology of the coatings of PAW were characterizing by scanning electron microscopy

and optical microscopy, and the phases of the coatings were analyzed by X-ray diffraction.

Their hardness was measured using a micro hardness tester. Experimental results showed

that defect-free composite coatings were obtain and that the coatings were metallurgically

bonded to the substrates. The surface of the Ni–Co duplex coatings comprised a Co-based

solid solution, Cr7C3, (Fe,Ni)23C6, and other strengthening phases.

The micro hardness and wear resistance of the duplex coatings were significantly improved

compared with the Cu substrates. The average micro hardness of the cladded coatings was

845.6 HV, which was approximately 8.2 times greater than that of the Cu substrates (102.6

HV). The volume loss of the Cu substrates was approximately 7.5 times greater than that

of the Ni–Co duplex coatings after 60 min of sliding wear testing. The high hardness of

and lack of defects in Ni–Co duplex coatings reduced the plastic deformation and adhesive

wear of the Cu substrates, resulting in improved wear properties. [6]

2.3 Tungsten Inert Gas Welding

Basic principle of Tungsten Inert Gas welding is of producing high intensity generated arc

which induces increased energy thus joining plate with NiTinol wire. During this process

with the solid-liquid amalgamation layer, arc generation to joinery remains permeable with

temperature induced gaseous impurities during the process. Thus, forming the increased air

compression in heat affected zone leading to sieved forming area. However, the reacting

gases have an impact on conductive & convective heat transfer process. The specific

reaction area is occupied by apportion of liquid, which is then, shifted from reaction zone

to surface joined zone, which if not properly done forms crevices, while repairing the

cracks. Hence, to avoid the matrix and grain structure of NiTinol to devoid refined shell

structure formulation which is formed by amorphous ox carbonitrides in form of bi

substrate as the welded specimen has elasticity and biocompatibility, thus makes Nitinol

alloy susceptible usage for medical [7].

For this process of joinery, NiTinol wire with curing is a challenge for forming straight

shape and regaining super elastic feature after joinery which can be done in annealing heat-

treating furnace to some extent and obtained with good tensile strength. NiTinol wire when

used in joining can give optimized functional characteristic feature comparable to other

conventional processes bend wire with recovery of almost 96.3% [8]. Basic physical

properties of NiTinol & 304 steel used in medical are as shown in Table 2.1 [8].

LITERATURE REVIEW

13

Table 2.1 Basic physical and mechanical properties of NiTinol and 304 steel [8]

NiTi 304

Density [g/cm3] 6,5 8

Fusion Temperature [ºC] 1240-1310 1450

Thermal Conductivity[W/mºC] 18 16

Thermal Expansion Ratio [10-6ºC] 11 17,5

Heat Capacity [J/gºC] 0,32 0,5

Ultimate Tensile strength [MPa] 754-960 500

Young Modulus [GPa] 40(M),75(A) 193

It is found by researchers that filler material forms brittle phase in nugget zone while using

TIG method for repairing of steel with the NiTinol as filler material. The matrix phase is

an amalgamation of Ti, Ni and Fe content, wherein in eutectic spectrum are Ni rich content

and the spectrum 3 comprises Ti carbonitrides. The weldability can be improved by

product designs, welding procedures [9]. The shape memory characteristic features at

heating, wherein elasticity varies from almost 4 to 6%. Stress level plays an important role

in fatigue behavior [10]. Figure 2.2 shows that when analysis of microstructure of NiTi

welded specimen is done, it reveals that welded joint micro hardness was higher in TIG

compared to plasma arc welding and dependent on filler material unlike laser welding.

NiTi welded joints had 11% strain in LBW unlike PAW of 8% [11].

Figure 2.2 Microstructure content of NiTi welded cross section [12]

LITERATURE REVIEW

14

It was detected that unlike dissimilar-similar material welding showed more strength in

parameter of Vickers Hardness test ranging from 900 HV and its microstructure as shown

in figure 2.2 [12]. When Tungsten Inert Gas welding was done on AISI 304 with similar

and dissimilar material using NiTinol Wire, SEM reveals fracture zone as shown in figure

2.3. The major setback in making dissimilar joints is due to difference in thermophysical

properties as well its constituents chemically forming intermetallic phase precipitation,

which can be enhanced using suitable joinery method, curing process, addition of alloys or

forming Interlayer as shown in figure 2.3 [17].

Figure 2.3 Scanning electron Microscope images shows fracture structure of welded

AISI 304 by TIG Welding. [17]

It is found that because of hindering stresses, recovered strains and solid-state operation

provides more strength and joints when assessed by X-ray spectroscopy. EDS analysis

shows that composition of Ni is 67% and Ti 33% [14]. When in experimentation, pure

argon as shielding gas and ampere of 75A was set with variation in speed from 2 to 3.5

mm sec-1

forming complete weld bead. When speed increases with lower heat input, the

width decreases and penetration increases. This is resulting into reduction of delta ferrite

LITERATURE REVIEW

15

fraction in austenite structure, thereby increasing pitting corrosion potential. When

nitrogen content increased the weld reduced delta ferrite in an austenite matrix, which

enhanced corrosion resistance shifting pitting to noble direction. It also thereby imparted

optimum microstructure and making weld resistant from solidification cracking as

mentioned in following parameters and figure revealing the results for AISI 304 as stated in

Table 2.2 [15].

Table 2.2 TIG Welding Parameters for Experimentation. [15]

Welding parameter

Welding Current/A 75

Welding Voltage/V 12±1

Welding Speed/ (mm·s−1) 2,3,3.5

Arc Length/mm 1.6

Nozzle Size 8

Tungsten electrode diameter (EWTh2)/mm 2.4

Flow rate of shielding gas on the face side using pure argon and argon mixed with

nitrogen/(min-1

) 101

Flow rate of backing gas on the root side using pure argon/(min-1

) 91

The important parameters in TIG welding are voltage, current and speed. Amongst these,

speed plays pivotal role for determining tensile strength. It is found that penetration depth

increases with increase in current, which is linear, wherein for voltage it is vice versa and

penetration decreases with increase in speed. Weld bead formation for parameter

comparison is shown in figure 2.5 [16]. It is found that while welding AISI 304, the

properties of austenite stainless steel are governed by delta ferrite phase. Heat treatment

processes like preheating and annealing were negatively correlated stating that from delta

ferrite to sigma phase takes place at high temperature, otherwise tensile strength, hardness

and corrosion current density exhibit a positive correlation as shown in figure 2.4 and 2.5.

Figure 2.4 Potential (mV vs SCE) and Current density [20]

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Figure 2.5 (a) Curves of base metal & Weld metal with diff % Ni in Ar gas. (b) Specimen

welded bead using speed lower than 2 mm sec-1

, results observed on face side, root side and

welded cross section respectively in a, b, c [20]

The weld geometry at various power output is shown in figure 2.6.

Figure 2.6 Weld Geometry at various power output [21]

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2.4 Friction Stir Welding

In this welding process, either through lathe machine or VMC machine, one tool made of

steel or Al or Cu is rotated in chuck and other in mandrel, and the steel plate is placed in

between these two tools. Because of frictional heat, generated joinery takes place wherein

with NiTinol wire is engulfed in between these two tools. It is of importance as a solid-

state welding process. Controlling various parameters of rotational speed of tool and

transverse speed, tool angle tilt along with axial load plays crucial role in quality and

tensile strength of weld. The study was done to find relation between varying transverse

speed and the tool profile. It is found in study that from 575-900 rpm and traverse speed of

3.16 mm/min - 8.16 mm/min forms good joinery. When the rotational speed is increased

mechanical properties decreases for AA6061-T6 aluminium [18] as shown in figure 2.7,

2.8 and 2.9.

Figure 2.7 Tensile strength, hardness, and impact toughness graph of Martensite steel

joinery [23]

The presence of residual stress and distortion cannot be devoid as in Friction stir welding

process due to non-uniformity of changes in temperature. The research carried out in the

study reveals that when stationary shoulder friction stirs (SSFSW) of 6005A- T6 Al is done

at 200mm/min to 600mm/min using thermos-mechanical model, it showed that compared

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to conventional FSW SSFSW possessed good joinery with mechanical characteristic

features.

Figure 2.8 Friction stir welding: probability for various mechanical properties[22]

Figure 2.9 Total deformation and temperature profile and tensile test graph of 4mm and

6mm [23]

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Stationary shoulder was used to produce minimal residual stress and distortion, while

joinery of 6005A-T6 alloys with comparative analysis for conventional type of FSW and

SSFS welded, which showed that a bowl like shape contracted in size with increasing

welding speed during conventional weld.

In addition, it is deduced that in case of SSFSW, it is increased slowly while heating and

reduced rapidly during cooling, when added stationary shoulder it decreased peak

temperature during welding. The stress induced in welding zone increases with increase in

speed in case of SSFSW, which is deliberately lower than 50% compared to conventional

FSW. The welded plate had an apparent saddle type of shape and its geometry changed

with increase in welding speed, which was reduced by adding shoulder [19] as shown in

figure 2.10 and 2.11.

Figure 2.10 Longitudinal stress (a) FSW & (b) SSFSW [24]

Emphasis is therefore focused on the pattern of experimentation which are responsible to

form welds and microstructural refinement, as this also has its effects which varies with

parameters and technology diffusion leading to better understanding of microstructure and

and its characteristic features relationship. Parameters of tool geometry, joint design,

process modelling, metal flow were studied [19].

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Figure 2.11 Temperature Maps (a) FSW & (b) SSFSW

It is found that amongst these, tool geometry plays vital role. Cylindrical threaded pin,

concave shoulders and tri-fluted pins are widely used. In addition, other parameters like

tool rotation rate, traverse speed, tool tilt angle and target depth are equally important to be

studied.

For joinery of butt or lap, flow is crucial, and it is very less researched which is understood

as situ extrusion method with stirring taking place at surface layer. For Al temperature rise

of 400-500 degree centigrade is crucial for fine recrystallized grains of 0.1-18 µm texture,

forming specifically three zones nugget region, thermomechanical and heat affected

region. It is found that almost 80% of yield stress to base Al metal is achieved with good

ductility feature. As melting point is high, it depends heavily on parameters for strength of

joint such as steel, which requires thorough understanding of matrix structure [20]. Figure

2.12 shows microstructure of grain interior along grain boundary and figure 2.13 shows

distance from weld center. Table 2.3 shows micro grain structure.

Figure 2.12 Microstructure for grain interior and along grain boundary (a) base Metal

(b) H HAZ (c) TMAZ near HAZ and (d) TMAZ near nugget zone with different

parameters [20]

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Figure 2.13 Distance from weld center [20]

Table 2.3 Ultrafine grained microstructure [20]

Material Plate

Thickness Tool

Geometry Cooling

Rotation rate

Traverse speed Grain

2024Al-T4 6.5 Threade,

cylindrical Ni 650 60 0.5-0.8

1050Al 5.0

Conical pin

without

thread N/A 155 N/A 0.5

075Al 7 N/R dry ice 2.0 120 0.1

Cast Al-Zn-

Mg-Sc 6.7 Threaded

cylindrical N/A 25.4 N/A 0.68

The advance mechanized machine for friction stir welding is shown in figure 2.14.

Figure 2.14 150 Tons Mechanized Linear Friction image courtesy from website

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The NiTi and Stainless-steel joint with its EDS composition is shown in figure 2.15.

Weight and differences of different materials is also shown in figure 2.16.

Figure 2.15 (a) Welding with NiTi and SS weld (b) EDS Composition [21]

For optimum results for Material Removal Rate and less tool wear rate for any welding

process peak current, tool rotation are prominent factors amongst other factors like pulse

on time and depth of weld penetration [22]. The binary diagram of Ni and Ti is very

important to understand to adjust parameters as shown in figure 2.17 [23].

Figure 2.16 Wt. and differences of different material [21]

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Figure 2.17 Binary Diagram of Ni and Ti [28]

Thus, as per researchers study it is stated that FSW of NiTinol plate is feasible, either with

controlling parameters, studying binary process for understanding grain structure, and

using polycrystalline cubic boron nitride or tungsten-rhenium tool in mandrel/chuck when

lathe is used. The results are verified by numerous methods like differential scanning

calorimetry understanding austenite and martensite transformation temperature etc. The

study also confirms that with grain content variation in friction-processed zone, the

strength is increased with Ar transformation temperature unlike base metal. However,

NiTinol can be hot rolled for FSW up to 76% at 850 ºC devoid of any cracks which gives

its prominence in NiTinol welding to dissimilar material used particularly in medical

applications [24].

2.5 Induction Brazing

Induction brazing the shape memory alloy is done by heating eddy current and its analysis of

temperature field is done by plotting mechanical model in large deformation with a T-

Model in thin shells using change in coordinates. This study reveals that shape change is

done without the need of doing re meshing process as one of the functions of temperature,

which is further validated by model. Corrosion resistant brazed joint is obtained without

use of fluxes [25]. Pure Niobium metal while researched in induction brazing works as a

depressant for NiTi, which forms a basis for robust brazing due to eutectic nature of NiTi-

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Nb equilibrium. The joinery possesses excellent strength apart from transforming

characteristic, which can be achieved in low-cost batch process topology enhanced from

conventional wrought type of precursors understanding transition range of quasi binary

eutectic system [26]. It is found that for welding by Induction brazing, different materials

and joint thickness play prominent role in brazed joints [27]. NiTi wire temperature in

induction heating process is eluded to influence transient time so as to reach target

temperature of 55 ºC which overshoots [28-30.] The unusual behavior is due to martensitic

conversion as shown in figure 2.18 and 2.19 depict transition range of quasi binary eutectic

system [31].

Figure 2.18 Quasi binary eutectic system [31]

Figure 2.19 Time resolved brazing microstructure at 120 seconds [31]

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Two crystal structures are formed on cooling comprising R phase and martensite [32] and

because of this unique shape elasticity using Induction brazing find its applicability in

couplings, antennas, sensors. As shown in figure 2.20 [33], NiTinol Wire or tubes or plates

to be Induction brazed is of major factor for strength as one of the major concerns is of

crystallographic texture which determines mechanical properties after joinery for

temperature -100 °C to 200 °C [34].

Figure 2.20 Temperature profile of Induction Brazing [33]

Nitinol brazed specimen resist outside force having resistive force radially [35]. While

doing Induction brazing of thin-walled pipes made of AISI 304 steel using Cu-Ni as solder,

the analysis done by simulation model for electromagnetic and temperature field determined

that current density and temperature plays important factor and was verified by experimental

temperature measurement using pipe induction heating. COC condition in martensite is due

to lattice deformation producing distorted lines in martensite region with its applicability in

antennas [36-37]. Experimentation of Induction brazing joinery for material

Ni57Zr20Ti17A15Sn1 an amorphous filler metal for 304 SS brazing was done within

seconds in presence of Argon gas due to susceptibility of mixing with air and when their

joinery strength was investigated. The joints which were braced for 5s to 10s showed good

strength, also overheating due to skin effect can be overcome by holding for 10s. 5s brazed

weld exhibited Ni rich content which showed smaller content of homogenization of joint

region also shear strength of 235 MPa was obtained when it was welded for 10s [37]. The

design of joinery exhibits its strength based upon the plate thickness, weld arrangement,

weld geometry and its restraint which affects weldability. The filler material used for

cemented brazing is Zn, Ag, Cu based. Ni when combines with Co in complete

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solidification stage with tungsten carbide, wherein increased amount of Co3W3C forms ɳ

phase as shown in figure 2.21 to 2.23 [38].

Figure 2.21 NiTinol Wire heating image courtesy from website

Figure 2.22 NiTinol Wire heating’s susceptibility for MRI Scan [38]

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Figure 2.23 Stress-strain surface temperature for NiTi at various temperature [38]

The Ag –Cu-Ni pseudo alloy in air exhibited good properties of wettability & strength with

contact angle of less than 10º, wherein Ag based alloy is used for dissimilar joinery,

increasing the temperature or variation in joinery time showed that amount of Ag material

as filler was used less during welding process. It is studied that preferably a solder

comprising material with low melting point is preferable. The brazing temperature varying

from 600 ºC to over 1050 ºC was found apt and dependent on brazing parameters. The

advantages and applicability are enormous. The techniques like torch brazing, furnace

brazing, induction brazing have their characteristic determination. As such when slow and

even heating and cooling and big sized structure are to be joined it is preferred. Smaller

equipment’s can be repaired by torch brazing and when mass production is required

Induction brazing is preferred which is clean, easy and fast method of brazing. For

dissimilar joinery, tungsten-based alloy is suitable but when it is used, the defects of cracks

are observed due to formation of coalescence of small voids are formed in grain structure.

With increase in % of Ni60% Ti40% the activation energy and strain energy variation takes

place. Due to 60% Ni workability of joinery stress varies when the temperature drops

below 850 ºC in vacuum furnace. Microstructure constituent of dynamic recrystallization

takes when strain range which is important where flat geometry is preferred compared to

curved geometry [39]. Figure 2.24 shows the joint design and brazing of cemented carbide.

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Figure 2.24 Joint Design and Brazing of Cemented Carbide WC-Co and Steel [43]

The microstructure and mechanical properties as studied and states that when Cu, CuSi3,

CuNi10 through arc-braze TC4 to 304 L, the analysis shows that there is change in valence

structure and existing state of Ti and Fe atoms are transferred from high content to low

when changed from Cu to CuSi3 due to Gibbs free energy. It was also analyzed that Ti-Ni

intermetallic with less hardness is created using CuZn37 wire. The study also reveals that

all cracks propagation with different wires is from bottom of seam with layer of thickness

10-20 µm formed on NiTinol surface [40]. The time for solder temperature kept 12s

ranging temperature of 1115 °C to 1125 °C for B- Cu97Ni(B) [41]. The brazed seam of Ni

rich at 5s and Fe rich for 10s brazing exhibited homogenization [42].

2.6 Laser Welding

For Laser Welding, the parameters to be considered are scan speed and laser power which

plays crucial role for strength of welded bead on plate by NiTinol sheets. The strength of

the joint is determined by geometry of bead, microstructure constituent, and change in

micro hardness with the amount of oxidation with variation in proportion of Ti/Ni ratio

after welding. The study of corrosion behavior studied after welding reveals that dimension

wise geometry observed decrease as scan speed of laser was increased, wherein at upper

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part of joinery showed the same aspects change with decrease in power. The proportional

properties of micro hardness content slowly became more with scan speed with dual failure

and single for parent metal, which showed that corrosion property of welded sample was

far more superior to actual metal plate. The research reveals that post weld heat treatment

when observed for study, weldability by laser welding with cemented carbides with Invar

increased as martensite was formed infusion zone with WC grain ≈ 30 µm [42]. The study

revealed that while laser welding of Ti6Al4 butt joint of 2 mm thickness the specific heat

input plays vital role. With increased speed, HAZ and FZ formed conic bead shape. Using

proper shielding gas with proper amount of devices usage in this method can be an apt

procedure. The specific heat variation was done with change in welding speed with Laser

power, Vickers Test determined strength as no filler wire, and shaped grooves were used

during this welding procedure. For involving Ti to reach at high temperature to study

thermal process temperature variation by specific heat was done as shown in figure 2.25 to

2.26 [43] with increase in % of Ni60% Ti40% the activation energy and strain energy

variation takes place.

Figure 2.25 Surface magnetic flux density at room temperature image courtesy

LANTHA TECH

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Figure 2.26 Parameter for Magnetic flux by LANTHA TECH

Due to 60% Ni workability of joinery stress varies when the temperature drops below

950ºC.Microstrure constituent of dynamic recrystallization takes when strain ranges from

0.2 to 1.0 as shown in figure 2.27 and 2.28 [44].

Figure 2.27 Microstructure of NiTi-304 laser welded at HAZ and FZ zone [44]

It was also analyzed that Ti-Ni intermetallic with less hardness is created using CuNi10

wire decreasing from 769 Hv and max tensile strength increases from 186.4 to 319.4 MPa.

The study also reveals that all cracks propagation with different wires is from bottom of

seamin TC4 due to high Schmidt factor which is almost more than 200 m/s which was

measured by high-speed camera 200000 fps [45]. This paper researched determining these

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two features, which were assessed by Transmission electron microscopy for microstructure

content determination whereas for corrosion 0.9% NaCl and Hank’s solution was

employed. It was studied that base metal showed single austenite (B2) phase exhibiting

highest corrosion resistance. Whereas, base metal showed a single austenite matrix with

the phase constitute with the precipitation of R-phase, hence reduced the corrosion

potential, which resulted in weakest zone [45].

Figure 2.28 Peak Strain [44]

Zhi Zeng Mao Yang Jao Pedro Oliveira, Di Song, Bi Peng researched that mechanical,

physical along with distinct phase change characteristics of base material of equivalent base

and other specimen with dissimilar material laser welded which reached 88.4% and 67.5%

of the wire BM ductility. Microhardness value slowly increases from center to base region

[46]. The research reveals that post weld heat treatment when observed for study, the

corrosion resistant increased at 200 ºC with tensile strength up to ~ 1.8 times.

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However, at 400 ºC the properties depreciated forming precipitates of intermetallic of

Fe2Ti, Cr2Ti, FeNi, Ni3Ti, which deduced that proper control of PWHT temperature is a

requisite for good strength of joinery of NiTi-304 AISI [47]. When heat treated Ti- 6Al-4V

with 1-2 mm thickness weld strength was assessed laser welded by Nd:YAG by

determining welding speed as prominent factor of surface morphology and shape, defects,

strength of joinery. The amalgamation zone comprised of higher joint strength with

reduced ductility due to micro pores an Al2O presence [48]. Laser welding is found to be

most apt method and find its prominence in medical sector for NiTinol, However, limited

knowledge prevails as to how laser-welding parameter determines microstructure

properties and corrosion resistance as shown in Table 2.4 [48-49].

Table 2.4 Summary of Laser Operating Parameter [48]

Processing

Parameter CO2 Laser

Nd: YAG (cw)

laser

Nd:YAG (pw)

laser

Laser 2200 2000 315

Average Peak --- --- 3000

Pulse frequency ---- ---- 70

Pulse duration --- --- 1.5

Travel 1.75 2.5 38×10-3

Focal point -0.4 -0.4 -0.8

Focal spot 0.30 0.48 0.05

Heat 75.4 48.0 497.4

Shielding Gas Argon Argon Argon

This paper researched these two features, which were assessed by transmission electron

microscopy for microstructure content determination whereas for corrosion 0.9% NaCl and

Hank’s solution was employed [50]. It was found in study that joint breaking force exertion

was 77.2% and 71.4%. The residual plastic strain variation of dissimilar material was of

study at different temperature during cycling test helping for design of multi- functional

monolithic structure [51]. The NiTinol pseudo elasticity content makes it a preferable

material in auto sector, aero sector, though challenges are associated with its joinery as

process parameters plays vital role in strength of laser-welded joinery. Schloßmaker et al.

investigated Ni rich and Ti rich NiTinol welding procedure, whereas Tussi et al. studied

the functional properties of welding. Cyclic loading increases after welding procedure as

shown in figure 2.29 and 2.30 [52].

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Figure 2.29 Bend Test K10 specimen (b) Bending K40 [52]

Figure 2.30 Multiple plateau of laser welded specimen [52]

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Falvo et al. stated that large strain application of Ti needs to be avoided; commercially

SE508 Ni strip of 0.37 mm thickness was used for laser welding. The test indicated that at

room temperature the base metal is predominantly austenite, therefore pseudo elasticity

behavior is exhibited. The researcher’s study revealed that fracture surface analysis was

made by varying welding parameters to analyze the weld strength, pseudoelastic and cyclic

loading of joinery. Peak power and pulse frequency played prominent role in determining

tensile strength and ductility of micro laser welded material. As shown in figure multiple

plateaus existed due to SIM transformation during welding deformation. Welded specimen

showed higher permanent residual strain with large efficiency during starting of 5 cycles

and then latter base metal showed the presence of ductile dimpled surface, while welded

specimen both brittle at low peak power and ductility at high peak power [53]. The shape

setting procedure of NiTinol Wire was carried out by Laser beam at various intensities. It

was researched that single-track type of beam induces pseudo elasticity property, which

was studied by calorimeter, mechanical & microstructural properties. Laser in power range

of 37-45% were used for this study. With extension in unloading plateaus, over 6% strain,

mechanical hysteresis of almost 42.5% was reduced. With high energy, XRD while power

rate increased the mechanical crystallographic leading to defectively reduced and increased

strain property. NiTi to NiTi laser welding shows 75% of tensile strength unlike pure

NiTinol wire tensile strength. However, for welding NiTinol to steel no interlayer was used

during the process. For dissimilar joints, provided strong bonding strength in fusion and

HAZ compared to higher plateaus stress level, as shown in figure 2.31 and 2.32 [54].

Properties of nickel-titanium exhibits 75% of ultimate tensile strength when joined NiTi to

NiTi for joining with steel, no interlayer was required. NiTi to thin NiTi wire also shows

the good strength. [55]. Butt joint two NiTinol sheets when laser welded with thickness of

1mm using ytterbium: yttrium aluminum garnet-Yb: YAG, the studies of phase

transformation temperature, UTS, hardness revealed that nominal difference existed in the

assessed properties in between water quenched and normalized one. It was deduced that

water quenched laser welded specimen had better characteristics than latter one. Laser

hybrid welding utilizes laser and arc welding producing gap bridging qualities [56] as

shown in figure 2.33, 2.34 and 2.35 [57]. While laser welding NiTi and 304 SS, to reduce

the content of alloying of Ti and Fe were suppressed by Ni rich filler metal. Pulse energy

did not form more penetration of weld. The maximum penetration of zone obtained was 483

µm and 13.1 µm.

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Figure 2.31 DCS scan of wires in different conditions [54]

Figure 2.32 2D XRD frame gathered at 1D11 beamline of ESRF from wires [54]

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Figure 2.33 Exploded diagram of NiTi/304SS pilot weld [57]

Figure 2.34 (b) Pilot joint weld (c) Laser welded [57]

After these results, thin walled NiTi and 304 Steel tubes with same parameters & then its

properties of joinery were assessed by optical microscopy, composition analysis, which

revealed that penetration in case of thin specimen average extension zone increased and was

7.90 µm. Hardness mapping test showed that outside weld joinery the distinct properties of

shape memory remained unaffected. EDS test showed that increased hardness due to

formation of Ni rich content within partial amalgamated zone. Mechanical strength test

showed that 457 MPa was obtained. A multi pass process was obtained for full penetration

in between tubes of 1.65 mm. Thick- walled specimen exhibited 346 MPa, which was less

than thin walled due to voids in thick walled. Fracture analysis test revealed that in both

thin and thick walled, which could have been prevented by cleaning and other curing

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measures. The strength of thick walled caused plastic deformation to detwin NiTi thin

walled and thick-walled showed cleavage fracture [58].

2.7 Capacitor Discharge Welding

For Capacitor Discharge welding amongst various variables, non-uniform flux density

amongst prominent as shown in figure 2.35, 2.36 and 2.37 [58][59].

Figure 2.35 Temperature profile at 36 J heat for 1.31ms welding time [58]

Figure 2.36 CD Weld deposited on Fe3Al [58]

The research by R.D Wilson, J.R. Woodyard S.R, and J.H Devletian studied for

characteristic features of joinery by capacitor discharge welding with the depth of

penetration in full depth, while plasma jet from cathode ejects melted metal from cathode to

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anode during arcing time which led to cooling of anode. Metal spatter did not caused

extrusion but from expulsion during capacitor discharge welding time. With unequal

heating and cooling ratio in anode and cathode due to unequal heating time due to plasma

jet defining as one-dimensional process [63].

Figure 2.37 Tip length of 1.4 mm Capacitor discharge welding process used to join 6.35

mm Fe3Al solid cylinders with 100 V [58]

As suggested by F.Palano, F.W Panella, V Dattoma, the capacitor discharge welding uses

high–intensity current pulses, discharged by large capacitors. Multipoint contact

characteristic features minimize stress concentration effect at weld toe, which formed thin

weld beads with excellent material continuity [59]. As studied by Johannes Koal, Martin

Baumgarten, Stefan Heilmann, Jorg Zschetzsche and UWE Fussel have studied about

capacitor discharge welding with high current pulses in short welding times. Experimental

process investigated were restricted for the limited zones in the confined area due to

covered contact zone with short processing time with finite element for suitable time with

usage of multiphysics numerical model in APDL with ring projection for joining. Materials

En-AW-6082 used for ring projection and EN-AW-5083 used for sheet metal. The model

design was investigated for thermal-electric for measured voltage. The discontinuous

geometry using simulated time up to 0.57 ms to 1.67 ms. indirect coupling allowed the

dynamic calculation of contact resistance with model to complexity with large

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deformation, short current rise times with high temperature gradient with contact setting at

room temperature along with rezoning was assessed which overcome convergence issues as

shown in figure 2.38, 2.39 and 2.40 [60].

Figure 2.38 Characterization of capacitor discharge welding process and simulation [60]

Figure 2.39 Simulation results of temperature T distribution at t=0.75ms [60]

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Figure 2.40 Electrical voltage of different contacts [60]

As per researcher J. P Oliveira, R.M.Miranda, F.M.Braz Fernandes, NiTi is widely used in

industrial application, but have limited applicability in welding and joining during intricate

production process, as strength reduction, change in phase, with control behavior in shape

and super elasticity behavior [61]. With changing in peak current parameter there is change

in wire material diffusion rate increases as shown in figure 2.41 [63][64].

Figure 2.41 Micro hardness test of welded NiTi and steel tube by Micro Electron beam

welding without filler material [63]

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WEDM is thermal process [65] in which drilling forces can exceed above 5000 N due to

viscosity and pseudo elasticity content of NiTinol [66]. In EDM cracks subsequently start

at vertical portion when using NiTinol [67]. MRR depends upon melting temperature and

alloy composition [68-69]. WEDM and EDM find applicability by using hybrid process by

using NiTinol [70-71]. The stability of NiTinol alloy is primarily dependent on TiO2 layer

existing on surface layer can be propagated by self-synthesis temperature which can be

heat treated due to high plateau stress using additive manufacturing process as NiTinol

possess biocompatibility feature with thermo mechanical affected zone TMAZ [72-77].

Heat treatment at 950 °C -1 h is optimized for bimetallic additively manufactured structure,

hinderance is nondestructive testing of parts [78-79-80].

2.8 Conclusion of the literature review

• The research paper published so far present study of NiTinol wire welding on

different similar as well as dissimilar material.

• The various joinery methods have different parameters implications while joinery

with NiTinol.

• Dissimilar material strength is less as compared to similar material welding or

welding with Ni or Ti content or as filler material.

• Joinery with Nitinol is not simple as other material. It is expensive except few

domains like Medical, Aero, Auto sectors. It finds limited applicability but repaired

or joinery is very accurate similar to new part if it is done with optimized controlled

parameters. Temperature, feed, power, voltage, tool tilt angle, axial load, shielding

with gas and filler material should be specific. However, apart from this as while

welding there is change in crystal structure so change in pseudo elasticity content

of NiTinol and to retain its mechanical properties of Nitinol after welding, it

requires utmost specific process of curing which varies with process to process of

joinery.

• Curing of Nitinol methods are heat treatment, acetone bath, vacuum autoclave

which is implied based upon joinery methods.

• However, no research is available, which focuses on optimizing welding

parameters of welding of NiTinol wire on AISI 304 butt joint using NiTinol as

filler material by assessing its repaired strength using DOE method with Taguchi of

all specified six joinery methods and then applying the Poisson method of Johnson

Cook Model, simulated annealing i. e using combination of analytical & simulation

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study for assessing parameters and then studying its grain crystallography of

welded joint.

• The Welding by NiTinol is difficult process as well joinery strength is not optimum

if during welding conditions like curing, parameters regulation is not carried out.

• The researchers reveal that in major cases of joinery by selected technology it

failed at the boundary between the joint region during tensile testing and the major

cause was due to strain and damage localization due to change in valence structure

while NiTinol shifts from austenite to martensite to retain pseudo elasticity content

which promoted by brittle intermetallic phase transformation.

• The joinery method on NiTinol wires with a smaller diameter did not formed

improved performance. During these processes arc source, power, offset plays

determining role in strength. Different joinery methods have different subset of

parameters with pros and cons so its comparative analysis to be made judiciously.

• As per study, NiTinol wires or surface to be joined needs to be modified into

various depths ranging nanometers to micrometers with coating thickness, which if

it is built from naïve oxides showed cracks with lower strain. Also biologically, it

showed that composition varied with surface oxide hydration degrees, its

conductivities, surface texture and catalytic action.

2.9 Objectives of the Research Work

1. To perform experiment using NiTinol wire welding of AISI 304A with selected

technologies: Laser Beam welding, Plasma Arc welding, Tungsten Inert gas

welding, Capacitor Discharge Welding, Induction Brazing & Friction Stir Welding

and to overcome the challenges faced by variation in parameters and set up,

intermetallic phase study and curing NiTinol wire.

2. To develop platform wherein the most suitable method with optimum parameters of

joinery of NiTinol with AISI 304 butt welding based upon grain structure and study

of austenite to martensite characteristic wherein its strength and pseudo elastic

content retained.

3. To develop a custom input format for validation experimentally as well as by

simulation to carry out joinery process to elaborate factors like overheating, skin

effect, bonding time and phases of transition temperature of smart material in HAZ.

4. To utilize inputs from Design of Experiment, Simulated Annealing and Poisson

Johnson Cook graphical analysis to carry out joinery analysis. The parameter subset

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formulated can overcome the challenges faced through these joinery techniques

specifically of wetting between the base material and NiTinol as cured and uncured

filler material, overheating, metallurgical interaction between liquidous NiTinol

and AISI 304 A base plate.

Figure: 2.42 describes graphically the statistics of experiments conducted by researchers of

six joinery techniques studied here by using NiTinol wire to understand the concept

viability of joinery process.

Figure 2.42 Welding with NITinol wire

Figure 2.43 describes the flow and methodology implied for this research. Figure 2.44

describes publication statistics of various joinery methods in the world to find the

applicability of joinery method by NiTinol Wire.

LITERATURE REVIEW

44

Figure 2.43 Flow chart of research work

Figure 2.44 Publications statistics in the world

LITERATURE REVIEW

45

2.10 Research Gap and Definition of the Problem

From the above mentioned literature review and study of various joinery methods using

NiTinol wire with AISI 304 /Ti-Al2O4 plate, following said problems and gap have been

identified.

The study reveals NiTinol wire welding with similar or dissimilar material with AISI

304A, but detailed analysis is not done as to why this range of parameters has been

selected. The difficulties faced in this type of joinery and expense incurred is not technique

to material specific.

As explained diagrammatically, more than 100 research papers reveal different conditions

and parameters range and their study of strength, hardness testing, amongst papers the

focus is made on heat control, pulse range, feed depth, etc.

These parameters vary from processes of joinery to NiTinol material shape, like wire,

tubes or sheet with similar to dissimilar materials to select optimum parameter, but from

DOE to select optimum for making comparative analysis keeping factors similar is not

done specifically yet.

When parameters are kept same but processes vary so the strength and pseudoelastic range

vary. NiTinol is very difficult material to weld with dissimilar material without carrying

out curing procedure.

Challenges in joinery in researched techniques does not elaborate how parameters affect

for wetting between the base material and Nitinol as filler material.

2.11 Original Contribution by this Thesis

The contribution of this research will help the researchers and welding personnel to

explore the possibilities of repair work with NiTinol material. Still its current applicability

is limited for repair work of fine intricacy in aero-foil blades, medical applications,

actuators because of expenses and other complexities associated while joining NiTinol

with dissimilar materials. It has to be cured and carried out heat treatment process before

welding process in optimum parameters settings. The study explored unattended facets to

overcome the challenges faced in joining by smart material and the parameter and

experimental set up to understand phase transition for retaining smart material feature,

mechanical properties enhancement and preserving light joint weight feature.

DESIGN OF EXPERIMENTATION TECHNIQUES

46

CHAPTER 3

DESIGN OF EXPERIMENTATION

TECHNIQUES

3.1 Design of Experimentation of selected joinery methods for parameter setting for

experimental analysis implied for finding the optimum parameters of Six Selected

Technologies Joinery by NiTinol Wire on AISI 304 plate without curing NiTinol

wire.

For all selected six joinery methods, the dimensions of 304A AISI plate and NiTinol wire

of 0.08 mm without curing and acetone bath cured NiTinol wire were the same for

comparative analysis amongst all joinery techniques. The research parameters were

analyzed by Design of Experimentation by Taguchi, surface plotting, Empirical CDF,

Pareto with parameter validation to formulate parameter subset for Experimentation of six

joineries with NiTinol Wire on AISI 304A base plate considering wetting, phase transition,

holding time ,bonding phase and intermetallics. Parameters of all six joinery methods were

assessed and then experimentation of each joinery conducted. Further the strength was

measured by lab test and simulation with optimization of two optimum results.

3.2 Plasma Arc Welding

Before carrying out the design of experiment for setting parameters for conducting

experimentation of joinery by NiTinol wire on butt welding by 304 AISI, by six Joinery

methods viz: Plasma Arc Welding, Tungsten Inert Gas Welding, Laser Welding, Friction

Stir Welding, Induction Brazing, Capacitor Discharge Welding, characteristic properties of

NiTinol wire & AISI 304A plate was determined based on available data as shown in

Table 3.1. The schematic experimental set up is shown in figure 3.1. The parameters

validated for experimentation are shown in figure 3.2 to 3.5 respectively based on DOE.

Figure 3.2 of Taguchi analysis of Tensile strength with reference to parameter ampere and

voltage analyzed along with signal noise ratio which states that with increase in ampere

and voltage above 42 amp and 23 V, the strength can be optimum which is further done by

signal noise ratio, as shown in figure 3.2 and 3.4. Figure 3.5 of Surface plot shows that 513

N/mm2 tensile strength is obtained at ampere from 42amp and 23 Voltage.


47

Table 3.1 Characteristic Properties of NiTinol and 304 steel

Properties 304 AISI NiTi

Density[g/cm3] 8 6,5

Fusion Temperatureº C 1450 1240-1310

Thermal Conductivity[W/mº C] 16 18

Heat Capacity [J/gº C] 0,5 0,32

Thermal Expansion Ratio[10-6/º C] 17,5 11

Ultimate Tensile strength[MPa] 500 754-960

Young Modulus[G Pa] 193 40(M),75(A)

Figure 3.1 Schematic Diagram of Plasma Arc Welding


48

Figure 3.2 Taguchi Analysis: Tensile Strength vs Ampere & Voltage of PAW

Figure 3.3 Response Table for Signal to Noise ratio for PAW


49

Figure 3.4 Empirical Cumulative Distribution Function of Ampere of PAW

Figure 3.5 Surface Plot of PAW


Tungsten with 2.322 % thorium in electrode with 2.75 diameter nozzle was used with the


50

angle of 45º with 1.5 mm near the 304A steel plate and NiTinol wire. The process was done

without any coating, so the results were poor. Experimental set up is shown in figure 3.6

with parameter validation for this joinery by DOE as shown in figure 3.7 and 3.8 with

respect to surface plot and mean comparison.

Figure 3.6 Schematic Diagram of Tungsten Inert Gas Welding

Figure 3.7 DOE of TIG


51

This shows that 230 N/mm2 Tensile strength is obtained at power of 42 and operating

current of 48 which is further validated by surface plot as shown in figure 3.8 showing 13

seconds favorable time for heating parameter with optimum 1.95 current density and 25°C

favorable. However, experimentation parameters were further assessed based on machine

specifications.

Figure 3.8 Surface Plot of TIG

3.4 Laser Welding

As per DOE, the parameter set and experimental set up shown in figure 3.9 to 3.11 for

Laser Welding is obtained by validating parameters by surface plotting by cumulative

distribution function CDF based on statistical reached data probabilistic occurrence of

likelihood of parameter range by DOE done. Thus using short pulse rang of YG: Argon.

CDF is plotted for parameters ampere and voltage along with surface plot with respect to

travel speed to determine tensile and bending strength comparison. Figure 3.9 shows

schematic set up for laser welding with CDF Empirical showing in figure 3.10 with 64 A

with 90 V and as shown in figure 3.11 of surface plot shows favorable tensile strength

achieved will be 310 N/mm2.


52

Figure 3.9 Schematic diagram of Laser Welding by NiTinol Wire

Figure 3.10 CDF Empirical for Laser welding by NiTinol wire


53

Figure 3.11 Surface Plot of Laser Welding by NiTinol Wire


The schematic diagram of FSW on manual lathe machine is shown in figure 3.12.

Figure 3.12 Schematic Diagram of Friction Stir Welding

The parameter subset was set by DOE as shown in figure 3.13 to 3.23. Taguchi analysis for

parameters of rpm is done which plays prominent factor in this welding. Surface Plot,

ANOVA, CDF and signal to noise ratio analysis done by MINITAB. Friction Stir welding


54

method decides parameter subset for factors of utilizing frictional force with exertion of

axial force up to 1 KN [84], the p values which is statistically later optimized as per

parameters subset. As shown in figure 3.13, 1200 rpm and upset forged force of 2 KN

validated by Empirical CDF as shown in figure 3.14 and 3.15, 3.16 of surface plot.

Figure 3.13 DOE of FSW

Figure 3.14 Empirical CDF of FSW


55

Figure 3.15 Surface plot of RPM v/s Upset Force v/s Hot Rolled

Figure 3.16 Surface Plot of FSW


56

Figure 3.17 Upset time v/s Upset force

Figure 3.18 SN ratio v/s Ampere


57

Figure 3.19 Statistical analysis for models

Figure 3.20 Response table for standard deviations

Figure 3.21 Estimated model coefficients for means


58

Figure 3.22 Response table for means

Figure 3.23 Estimated model coefficient for standard deviations

The parameters are further validated by ANOVA analysis 3.17 for upset times and upset

force. As shown in figure 3.18 S/N ratio validates S value of 0.4058 for ampere parameter

as shown in figure 3.19 which is further validated in 3.19 and 3.20 to 3.23 in statistical


59

analysis further at 66 ampere.

Estimated model for Coefficient for standard deviation forms parameter modulation of

ampere, voltage based on response table for means which is validated by ANOVA and

signal noise ratio, which is used in the experimentation as discussed in next chapter.


The schematic diagram of this welding is shown in figure 3.24 wherein NiTinol wire

engulfed in stud as used [85].

Figure 3.24 Schematic Diagram of Capacitor Discharge Welding

CDF is generated with respect to specimen tested in % and Taguchi analysis is done for

parameters of temperature frequency and power. The strength of weld usually in CD

depends upon proximity of stud to weld zone [86] as it is a fusion welding process, usually,

silicon- controlled rectifier finds its usage. It finds therefore applicability in automotive

sector. As shown in figure 3.25, Taguchi analysis of tensile strength with respect to power,

frequency and temperature validated along with Empirical CDF and surface plotting which

is shown in figure 3.26 and 3.27.


60

Figure 3.25 Capacitor Discharge Welding DOE

Figure 3.26 Empirical CDF of CD Welding.


61

Figure 3.27 Surface Plot of CDW


As strength to weight properties Ti in NiTinol plays positive in repaired welded

corrosion resistant [87]. Figure 3.28 shows the schematic of Induction Brazing wherein

Induction Coil is used to heat & melt NiTinol Wire.

Figure 3.28 Induction Brazing


62

Empirical CDF in figure 3.29 shows temperature and frequency with current density

parameter analysis. Surface plot of temperature parameter shown in figure 3.30 depicts

the UTS of 222 N/mm2.

Figure 3.29 Empirical CDF of IB

Figure 3.30 Surface plot of temperature v/s frequency v/s power

EXPERIMENTAL INVESTIGATIONS

63

CHAPTER 4


PERFORMING J O I N E R Y BY NiTinol WIRE ON

AISI 304A PLATE

DOE results set parameter ranges for ampere, voltage, frequency, pulse duty cycle, current

density, axial load, tilt angle, power varying in selected six joinery methods were

performed for butt welding 304 AISI plate using NiTinol wire without curing. Lab tests

reports and optical microscopy analyzed the following results for crystal grain structure

change of NiTinol from austenite to Martensite.

The comparative results of the tensile strength, bend test and hardness test were then

determined to select two optimum processes favorable for carrying out welding by uncured

NiTinol wire. Friction Stir Welding –Manual & Robotics and Induction Brazing were

selected technologies, which were later analyzed with simulated annealing and algorithm

analytical to find controlled optimized parameters to find bias percentage error check of

these processes to validate the same.

4.1 Plasma Arc Welding

AISI 304 Plate with dimension 100 W × 1T × 250 was butt welded by Nitinol wire with

diameter 0.96 as filler material which was kept same while welding with all selected six

technologies with parameters variations. Nitinol wire was used for welding. The Table 4.1

shows the parameters set while performing plasma arc welding on AISI 304 by NiTinol

wire. The welding parameters were based on DOE and analysis based on a lab report

which is given in Table 4.1. Experimentation performed as shown in figure 4.1 using the

validated parameter subset. Experiment comprised of using concise high velocity plasma

of 0.5 Lpm in presence of shielding gas with non-consumable electrode with butt welding

base plate using NiTinol cured in acetone bath for 15 s. In between two bases AISI 304A

NiTinol wire diffused forming amalgamation in nugget area with phase transition from

austenite to martensite.


64

Table 4.1 Parameters for Plasma Welding

Description Parameter

Plasma Gas 0.5 LpM

Shielding Gas 8 LpM

Ampere 40

Volt 22

Pulse frequency 3.5

Secondary Current 50% of main current (27.5)

Pulse Duty Cycle 50%

Travel Speed 140 mm/min

Figure 4.1 Plasma arc welded 304 plates with NiTinol wire


The optimum parameter is based on breaking load and standard deviation over 960 MPa

[88-89]. The TIG welding was carried out on AISI 304 A plate with NiTinol wire using

TIG torch & NiTinol wire from the fixture in spool form as shown in figure 4.2, while butt


65

welding AISI 304 plate which is based on the parameters set by DOE as shown in the

Table 4.2

Figure 4.2 Laboratory photograph

Table 4.2 Parameter set by DOE


Argon Gas 0.8 LpM

Shielding Gas 12 LpM

Temperature 24º C

Current Density 1.95

Ampere 55 Ampere

Voltage 9 V to 10 V

Pulse frequency 3.5

Secondary Current 50% of main current(27.5 amp)

Pulse Duty Cycle 50%

Travel Speed. 140 mm/min.

The test report which is performed on computerized testing machine as shown in figure

4.3, reveals that tensile strength does not meet with ASME standards.


66

Figure 4.3 Computerized Compression Testing Machine

4.3 Laser Welding

Interlayer formation during welding plays prominent role including refinement of grain

size [90-91]. Taguchi analysis with L9 series used using parameter variations in samples

[92-93]. Laser welding as shown in the figure 4.4 was performed with Nd: Yag with the

following machine specification as shown in Table 4.3 and 4.4.

Figure 4.4 Lab experiment photograph


67

Table 4.3 Parameter set based on DOE

Table 4.4 Laser Nd: Yag Welding Machine specifications.

Material AISI 304 & NiTinol wire

Automatic Grade Automatic

Output Current 100-200 A

Frequency 50 - 60 Hz

Voltage 380 - 440 V

Weld Thickness 0.5 - 3 mm

Laser Power 500-3000 W

Laser Wavelength 1064 NM

The Laser welding as shown in figure 4.5 and 4.6 depicts the experimentation done by

Laser welding on AISI 304 A plate with NiTinol Wire using short range of LASER pulse.

Figure 4.5 Laser welding machine


68

Figure 4.6 Laser welding machine setup

The parameter subset is obtained by DOE method, butt welded specimen of AISI 304 A

with NiTinol showed poor strength unlike to NiTinol-to-Nitinol wire joinery by LASER

method with specimen shown in figure 4.7 to 4.9. Figure 4.9 is NiTinol wire to NiTinol

wire welded showing unlike dissimilar material, the strength and retained smart material

feature in base plate is superior.

Figure 4.7 Laser welded specimen


69

Figure 4.8 NiTinol Wire

Figure 4.9 NiTinol wire welded

The welding report revealed cracks formulation in AISI 304 plate and NiTinol wire, but

while joining NiTinol wire to NiTinol wire, the strength was as per confirmation and

minute welding as possible [94].

4.4 Manual and Robotic Friction Stir Welding

Schematic diagram in figure 4.10, 4.11 and 4.12 show the parameters application for

manual FSW with experimental set up forming plastic and thermal strains along welded

zone using parameters subset by design of Experimentation [95,97,98]. An automated lathe

machine was used for experimentation where a steel plate 304 A parallel was vertically

butt welded with the frictional force generated by MS and AL stud mounted on chuck and


70

mandrel respectively. The parameters for this process are given in the Table 4.5. The setup

involved engulfing NiTinol wire in an MS stud of diameter 0.96 mm.

Figure 4.10 Schematic Diagram

Figure 4.11 CAD Model of FSW using Grab CAD


71

Figure 4.12 Experimentation on Lathe Machine

The chuck was rotated whereas mandrel was kept stationary while creating axial pressure

of 2.1 tons with tool tilt of 3° over stationary plate mounted on the fixture as shown in

figure 4.12. This resulting increases in temperature upto 1200 rpm which started with 900

rpm. After 1200 rpm crack was observed resulting in the red-hot zone. A reverse braking

process was used for creating good quality weld. During the process, steel fixtures were

used to clamp the AISI 304 plate and the back plate was used for bottom support. Welded

specimen as shown in figure 4.13 using parameter subset shown in Table 4.5.

Figure 4.13 FSW AISI 304 A with NiTinol Wire


72

Table 4.5 Welding parameters


Steel Plate & Nitinol Wire Diameter 100 W × 1T × 250× 0.96

Axial load & Welding Temperature 2.5 KN,345º C

Tool rotational Speed 1200 rpm

Tool Tilt angle 3º

Upset force, Friction force 2.1 ton,1 ton

Welding Speed 115 mm/sec

4.5 Mechanized Friction Stir Welding

Comparison of geometry [98] plays vital role to understand bead geometry of specimen

welded by FSW. Specimen shows it is spatter free [99]. Figure 4.14 shows the weld joint

done by mechanized friction stir welding. Figure 4.15 shows the CAD model of path of the

welding.

Figure 4.14 Robotic/Mechanized Friction Stir Welded Specimen

Figure 4.15 CAD Model showing the path of the welding


73

Figure 4.16 shows experimentation on AISI 304 plate with NiTinol wire using robotic

welding.

Figure 4.16 Experimentation on AISI 304 plate with NiTinol Wire

The Robotic Friction Stir Welding was performed on AISI 304 plate with Nitinol wire.

Based on CAD modelling as shown in figure 4.17 to 4.19 were controlled.

Figure 4.17 CAD Model


74

Figure 4.18 Simulation model of welded specimen

Figure 4.19 Grain Structure

However other specifications were set by machine as shown in Table 4.6. Welded

specimen as shown in figure 4.14 was spatter free & lab tested showed traces of retained

smart material characteristic feature as shown in figure 4.20. Unlike automated lathe

machine in robotic friction stir welding skin effect in red hot zone was less with less

intermetallic and wettability and light weight of joinery was made.


75

Figure 4.20 Grain Structure

Table 4.6 Parameters set by machines


Force Control (Down Force)N 3000

Path Deviation Compensation(Derivative Term) 0

Rotational Tool Speed 1200 rpm

Welding Speed (mm/sec) 10

Welding Temperature 300º C

Path Deviation Compensation Robot Deflection model

The grain structure showed the fine weld with pseudoelastic property retained while

transforming from austenite to martensite [100]. Non Welding parameter apart from

temperature control and PID Control using the proper set parameter of down force,

welding speed, rotational tool speed, temperature plays a pivotal role in strength. However,

the force of the tool decreases when height i.e Z Position and it goes downhill with decrease

the height which is always opposite of welding direction increasing Fx.


76


The stud engulfed with NiTinol wire was used to rivet at steel plate by Capacitor discharge

gun of the solenoid, based on following parameters as shown in figure 4.21 and 4.22.

Narrow rupture and discontinuous strips [101] were observed and the specimen was

cracked at corners of riveting, so was not suitable for the test based on parameter subset as

shown in Table 4.7 and figure 4.23 welded specimen.

Figure 4.21 Simulation software for welding

Figure 4.22 Capacitor Discharge


77

Figure 4.23 NiTinol welded specimen with rivets

Table 4.7 Parameters for welding machine


Weld Cycle time 0.02 seconds

Weld Technique Contact & Gap

Stud Design Ignition Tip

Upsetting force 20 KN

Peak Current 62 A

Discharge Time of rivet 15ms


Induction brazing method was selected for performing the experimental process of welding

NiTinol wire with AISI 304 as the throughput time is more due to fast heating cycle time

and is controllable. Along with this, the main reason was only narrowly defined areas are

heated unlike leaving other adjacent areas so parameters check is more favorable [102].

The experimental setup assembly of the AISI 304 plate was made on mandrel as shown in

figure 4.24 with heated NiTinol Wire on fixture was induction brazed as shown specimen

in figure 4.25 with grain structure as shown in figure 4.26 shows Af transition of austenite


78

to martensite is granular and as per the parameters shown in the Table 4.8, specimen is of

good tensile strength but smart material feature is not retained during transition as in

Friction stir welding.

Figure 4.24 Induction Brazing Machine

Figure 4.25 Induction Brazing specimen


79

Figure 4.26 Micro grain structure of the welded specimen

Table 4.8 Parameters for Induction Brazing


Temperature of assembly 470 ºC

Capacitor -2 0.9µ F

Power 4.5 KW

Brazing Coil 40 ºC

Time 7 Sec

Mandrel size 330 mm

Parameter variations and methodologies used for joining is presented for Friction stir

welding. This method produced welded specimen with traces of smart material, whereas

remaining joinery methods could not produce desired results. Parameter RPM variation of

movement is done by moving chuck clockwise and counterclockwise. The favorable

results were obtained at clockwise direction upto 1200 rpm. Also, traverse line was

changed along the line of joint and off the line of joint. It was found that along the line of

joint the frictional heat was substantial generated for spatter free joining. The


80

methodology of joining was changed by frictional force keeping mandrel Al tool stationary

and by Robotic Friction with continuous heat generation by pedant, favorable result were

obtained by Robotic Friction process, which is further assessed and validated in next

chapters.

SIMULATION MODELLING & ANALYTICAL OPTIMIZATION OF PARAMETERS

81

CHAPTER 5

SIMULATION MODELLING & ANALYTICAL

OPTIMIZATION OF PARAMETERS

5.1 Simulation of Friction Stir and Induction Brazing Repaired Techniques Based on

Comparative Analysis

The Simulation of the Model of friction stir welding with UV was done to find optimized

parameters & weld joint analysis. Due to the frictional force of steel studs engulfed with

NiTinol wire when the analysis was done on blender software. It was found that the

external portion of the welded specimen showed more transition in the NiTinol phase as

compared to the joint portion due to transition and valance dislocation of material phase

change in the nugget zone. The lower portion welded frictional force created a stir which

showed higher displacement of stress and lower affinity of tensile strength for joining

withheld with pseudo elastic content. The mesh analysis and UV map as shown in the

figure 5.1 to 5.5 accessed AISI 304 with NiTinol repaired material through the generated

output of the texture generated coordinate node which was used to map a texture onto a

specimen.

Figure 5.1 Simulated Models of Friction Stir Welded plate by NiTinol wire engulfed to

Stud by Lathe Machine (a)


82

Figure 5.1 describes the simulation of mesh analysis with red region showing stress area of

friction stir welded specimen and which is further shown in figure 5.2 of welded specimen

with light blue describes the weld flow with red region of stress concentration in heat

affected zone. It is depicting the red zone shows a high value of repaired strength and with

a low value shown in blue whereas the geometry with the range of repair is shown in green

color.


Stud by Lathe Machine (b)

Figure 5.3 Simulated Models of Friction Stir Welded plate by NiTinol wire in four

orientation axis to capture weld penetration


83

The angle and axis displayed with minimum and maximum range helps while doing job

repair by Robotic friction welding using distance range for determining the thickness of

welded geometry intersection width to avoid any welded distortion [103]. However, mesh

analysis results applicability had limitations as the results displayed based on Deform

Modifiers for high poly-meshes with low performance.

Figure 5.4 Simulated Models of Friction Stir Welded plate by NiTinol wire shows nugget

zone of specimen

Figure 5.5 Mesh analysis with brown spot with traces of NiTinol


84

Figure 5.6 Surface texture of repaired AISI 304 with NiTinol

The fatigue resistance of repaired AISI 304 with NiTinol wire was analyzed in MATLAB-

19 for singular stress field zone. It was found in the joint area of the plate, and stud, which

calculated across three axes as shown in the figure 5.7 and 5.8. It shows that maximum 200

MPa stress with dislocation of 150 mm at 1.25 mm distance after weld penetration was

observed. Showing best stress at 0.491302 and mean 664119 for less geometric

discontinuities at the region of interface between plate and NiTinol engulfed stud.

Figure 5.7 Matlab Simulation for stress analysis of welded joint (a)


85

Figure 5.8 MATLAB Simulation for stress analysis of welded joint (b)

5.2 Mechanized Friction

As shown in figure from 5.9 to 5.19, specimen welded by mechanized friction stir welding

through Blender software produces mesh analysis and UV surface texture of welded zone

highlights HAZ which shows that austenite to martensite phase transformation shows the

traces of smart material NiTinol by stress application technique.

Figure 5.9 Simulation of specimen welded by Mechanized Friction Stir Welding (a)


86

Figure 5.10 Simulation by Mechanized Friction Stir Welding (b)

Figure 5.11 Simulation by Mechanized Friction Stir Welding (c)

However, treatment of specimen is done by curing and skin effect recovering along with

controlling overheating by holding time of 15 s to retain partial loss during welding by

mechanized friction stir welding. The UV term in blender means dimensional process of

which was later mapped in 3D model as this process made easier seam joints at edges with

diffuse and albedo map which gave optimal quality results. The simulation modelling


87

shows that gradient of temperature in horizontal and vertical axis shows that traces of

martensite is there with grain growth of 2 µm which shows traces of smart material feature

in base plate after weld at 1200 rpm with 3° tool tilt with tool material of 45NiCrMo16

with numerical designation 1.2767. The coefficient of friction was calculatedly done to

control the frictional heat range.

Figure 5.12 Simulation by Mechanized Friction Stir Welding: mesh analysis with orange

line stress zone


Stud by Mechanized Machine (e): mesh analysis with orange line stress zone


88

Figure 5.14 Mesh analysis & UV texture map of repaired AISI 304 with NiTinol by

Mechanized FSW: red area shows stress depicting weld flow at HAZ

Figure 5.15 Mesh analysis of weld flow & UV texture map of repaired AISI 304A with

NiTinol by Mechanized FSW


89

Figure 5.16 Surface texture at fusion zone with frictional resistance


Mechanized: dark layer shows amalgamation


90

Figure 5.18 Mesh analysis of amalgamation zone

Figure 5.19 Mesh analysis of amalgamation zone & UV texture map of repaired AISI 304

with NiTinol by Mechanized

5.3 Simulated Modelling of Induction Brazing Welding

As shown in figure 5.20 to 5.25, UV mapping & Mesh analysis is done in Blender


91

Software to analyze joint mesh for thermo mechanical analysis. The analysis showed

reduced distortion and stress but smart material feature was not retained after weld unlike

friction stir welding in Induction Brazing.

Figure 5.20 Simulated Models of Induction Brazed Welded plate by NiTinol wire: nugget

area (square) portion shows uneven weld flow

Figure 5.21 Simulated Models of Induction Brazed Weld: stress concentration is more in

starting and reduced as it advances


92

Figure 5.22 Simulated Models of Induction Brazed Weld: mess analysis of stressed zone


Induction Brazing: mess analysis of stressed zone


93


Induction Brazing: camera capture of surface texture (a)


Induction Brazing: camera capture of surface texture (b)

The simulation analysis of various specimen of FSW and IB made it to finalize the

parameters suitable to produce results, which were further optimized computationally after

DOE. The results showed that specimen of Induction Brazing has good hardness due to


94

retained martensite but smart material features were not found, however Friction Stir

welded specimen showed good hardness as well specimen was light weight with traces of

smart material, hence based on UV texture reports, simulation mesh analysis friction stir

welded specimen were found of desired results which are further validated computationally

to find appropriate parameter module.

COMPARATIVE ANALYSIS OF REAL-TIME PARAMETERS

95

CHAPTER 6

COMPARATIVE ANALYSIS OF REAL-TIME

PARAMETERS FOR REPAIRED SPECIMEN

The real time computational model is developed to obtain desired accurate friction stir

welding with retained smart material feature. The real time optimization by Kalman filter

of Poisson method and then by Johnson Cook Model by Taguchi Method is derived to

obtain basic characteristic feature of NiTinol wire in Friction welding parameter after

comparative analysis with simulation of Induction Brazing narrows down to Friction Stir

welding Parameter optimization. This process by MATLAB and computational algorithm

helped in fine tuning the parameters. Statistical technique is used to refine the results for

Tensile strength, hardness, pseudo elasticity properties of Nitinol Wire when friction stir

welded with AISI 304 A plate controlling parameters of speed, feed, depth, current

density range, tilt angle axial force as shown in curves of Cumulative Distribution Function

demonstrated of optimum joinery method: Robotic Friction Stir Welding & Manual

Friction stir welded on the module output are analyzed. In addition, the comparisons of

these mentioned welding parameters are analyzed. In Friction Stir Welding, real-time

parameters are developed to attend desirable weld strength by NiTinol Wire. Difficulty in

modelling was overcome by optimized parameters run by Design Test Modulation by

Taguchi by DOE Method. Kalman Filter Algorithm by Poisson Method was optimized for

the position of NiTinol Wire welding and velocity of the tool, using the equation and

measurement model. The predicted model compared with experimental results, which

accurately predicted the bead geometry [104-117].


96

6.1 Mechanized Friction Stir Welding

Real Time Parameters of DOE after tuning is shown in Table 6.1 and 6.2 with coded

coefficient. As shown in Table 6.1 for coded coefficient, VO tool angle, V1 tool velocity

V2 rpm of tool and V3 thickness of base plate, this table analysis is used to define size and

direction of relationship. Amongst all parameters to understand the proportion VIF

(variance inflation factor) for VF>5, the parameters are highly correlated and p < α value

judges it is going towards null hypothesis. Hence from the given table all the stated

parameters are correlated with specific response optimization.

Table 6.1 Coded Co-efficient

Term Effect Coef SE Coef T-Value P-Value VIF

Constant 7.958 0.723 11.00 0.058

v0-Tool angle 4.632 2.316 0.789 2.94 0.209 16.08

v1-Tool

Velocity 3.601 1.800 0.387 4.65 0.135 3.88

rpm 0.149 0.075 0.311 0.24 0.851 2.51

mm/s -1.416 -0.708 0.982 -0.72 0.603 11.07

mm -0.500 -0.250 0.433 -0.58 0.667 4.85

v0*v1 -0.149 -0.075 0.444 -0.17 0.894 5.10

v0*rpm -0.601 -0.300 0.354 -0.85 0.552 3.24

v0*mm/s 2.62 1.31 1.17 1.12 0.464 19.96

v0*mm 0.500 0.250 0.433 0.58 0.667 4.85

v1*rpm -1.750 -0.875 0.331 -2.65 0.230 2.83

v1*mm -1.000 -0.500 0.354 -1.41 0.392 2.31


97

Table 6.2 Robotic Friction real-time parameters

Model Summary

S R-sq R-sq(adj) R-sq(pred)

0.707107 99.73% 96.70% *

Analysis of Variance

Source DF Adj SS Adj MS F-Value P-Value

Model 11 181.500 16.5000 33.00 0.135

Linear 5 59.873 11.9746 23.95 0.154

v0 1 4.313 4.3125 8.63 0.209

v1 1 10.800 10.8000 21.60 0.135

rpm 1 0.029 0.0286 0.06 0.851

mm/s 1 0.260 0.2595 0.52 0.603

mm 1 0.167 0.1667 0.33 0.667

2-Way Interactions 6 9.452 1.5754 3.15 0.406

v0*v1 1 0.014 0.0141 0.03 0.894

v0*rpm 1 0.360 0.3605 0.72 0.552

v0*mm/s 1 0.626 0.6255 1.25 0.464

v0*mm 1 0.167 0.1667 0.33 0.667

v1*rpm 1 3.500 3.5000 7.00 0.230

v1*mm 1 1.000 1.0000 2.00 0.392

Error 1 0.500 0.5000

Total 12 182.000

Regression Equation in Uncoded Units

Run Order = -126.8 + 4.40 v0 + 47.2 v1 + 0.0747 rpm - 0.120 mm/s + 8.0 mm - 0.60 v0*v1 - 0.00401 v0*rpm + 0.0433 v0*mm/s + 1.00 v0*mm - 0.02333 v1*rpm - 4.00 v1*mm

Fits and Diagnostics for Unusual Observations

Obs RunOrder Fit Resid Std Resid

3 3.000 3.000 0.000 * X

4 4.000 4.000 0.000 * X

5 5.000 5.000 0.000 * X

6 6.000 6.000 0.000 * X

7 7.000 7.000 -0.000 * X

8 8.000 8.000 0.000 * X

9 9.000 9.000 0.000 * X

10 10.000 10.000 -0.000 * X

11 11.000 11.000 0.000 * X

12 12.000 12.000 0.000 * X

13 13.000 13.000 -0.000 * X

X Unusual X

Alias Structure

Factor Name

A v0

B v1

C rpm

D mm/s

E mm

Aliases

I - 0.60 BD + 0.05 CD + CE + 0.15 DE - 0.60 ABC - ABE + 0.55 ACD + 0.40 ACE + 0.75 ADE + 0.05 BCD + 0.25 BDE - 0.20 CDE + 0.35 ABCD + 0.25 ABDE + 0.10 ACDE - 0.70 BCDE - 0.20 ABCDE

A + 0.15 BD + 0.55 CD + 0.15 DE - 0.60 ABC - 0.75 ABD + ABE + 0.05 ACD - 0.60 ACE - 0.75 ADE

+ 0.80 BCD + 0.80 CDE - 0.40 ABCD - 0.40 ACDE + 0.55 BCDE + 0.05 ABCDE

B + 0.60 BD - 0.05 CD - 0.15 DE + 0.60 ABC + ABE + 0.45 ACD - 0.40 ACE + 0.25 ADE - 0.05 BCD

+ BCE - 0.25 BDE + 0.20 CDE + 0.65 ABCD + 0.75 ABDE - 0.10 ACDE + 0.70 BCDE + 0.20 ABCDE

C + 0.15 BD + 0.55 CD + 0.15 DE - 0.60 ABC + 0.25 ABD + 0.05 ACD - 0.60 ACE + 0.25 ADE

- 0.20 BCD + BCE - 0.20 CDE - 0.40 ABCD - 0.40 ACDE + 0.55 BCDE + 0.05 ABCDE

D + 0.60 BD + 0.20 CD + 0.60 DE + 1.60 ABC - 0.80 ACD + 1.60 ACE + 0.20 BCD + BDE + 0.20 CDE

+ 0.40 ABCD + 0.40 ACDE + 0.20 BCDE - 0.80 ABCDE

E + 0.25 CD + 0.75 DE - ABE - 0.25 ACD + ACE - 0.25 ADE + 0.25 BCD - BCE + 0.25 BDE - 0.25 ABCD - 0.75 ABDE + 0.50 ACDE - 0.50 BCDE


98

AB - 0.15 BD + 0.45 CD + 0.85 DE + 0.60 ABC + 0.75 ABD - ABE - 0.05 ACD + 1.60 ACE + 0.75 ADE + 0.20 BCD + BDE - 0.80 CDE + 0.40 ABCD + ABCE + 0.40 ACDE - 0.55 BCDE - 0.05 ABCDE

AC + 0.40 BD + 0.05 CD + 0.40 DE - 0.60 ABC + 0.55 ACD - 0.60 ACE + 0.05 BCD + 0.05 CDE - 0.65 ABCD + ABCE - 0.65 ACDE + 0.05 BCDE + 0.55 ABCDE

AD - 0.40 BD - 0.80 CD - 0.40 DE + 1.60 ABC + ABD + 0.20 ACD + 1.60 ACE + ADE - 0.80 BCD - 0.80 CDE + 1.40 ABCD + ABDE + 1.40 ACDE - 0.80 BCDE + 0.20 ABCDE

AE - 0.25 CD - DE + ABE + 0.25 ACD - ACE - 0.25 BCD - BDE + 0.75 CDE + 0.25 ABCD - ABCE + 0.25 ACDE + 0.75 BCDE + 0.25 ABCDE

BC + 0.25 BD + CE + 0.25 DE - ABC - 0.25 ABD - ACE - 0.25 ADE + 0.75 BCD + 0.75

CDE - 0.75 ABCD - 0.75 ACDE

BE - CE - 0.75 DE + ABE - ACE - 0.75 ADE - 0.25 BDE + 0.25 CDE - 0.25 ABDE + 0.25

ACDE + 0.75 BCDE + 0.75 ABCDE

As shown in figure 6.1 for multiple regression for parameter V1, judging p value parameter

optimization is done. Table 6.2 gives the summary of parameters optimized by

Mechanized/Robotic Friction Stir Welding, with following operatives: Run Order = -126.8

+ 4.40 v0 + 47.2 v1 + 0.0747 rpm - 0.120 mm/s + 8.0 mm - 0.60 v0*v1 - 0.00401 v0*rpm

+ 0.0433 v0*mm/s + 1.00 v0*mm - 0.02333 v1*rpm - 4.00 v1*mm which is further

validated. Figure 6.2 with Multiple Regression report dependence of V1 and V3. As shown

in figure 6.3 further Parameters V1 are fine-tuned checking for normality and residual

output .Further as shown in figure 6.4 shows optimization parameters report, all parameters

V0,V1,V2,V3 are optimized.

Figure 6.1 Multiple regression for V1 summary report


99

Figure 6.2 Multiple regression effect report


100

Figure 6.3 Multiple regression for V1 model building report

Figure 6.4 Multiple regression for V1 Prediction and Optimization report

As shown in figure 6.5 Box plot of V1 tool velocity as per previous table as VIF was

moderately correlated is further analyzed at tool rpm correlation to state that range of

experiment performed is from 900rpm to 1200 rpm, experimentally it was proved that after

1200 rpm, strength reduced and due to high frictional force tool was tilted.


101

Figure 6.5 Box plot of V1 by rpm, mm/s, diagnostic report

Further, it is validated by Box plot as shown in figure 6.6 which is DOE and analytically

validated by Poisson 2 way Exponential method.

Figure 6.6 Box plot of V1 by rpm, mm/s, broken down report


102

Figure 6.7 Before/after Poisson capability Comparison for center pt. v/s stdorder_1

As shown from figure 6.1 to 6.7 by Poisson method of tool tilt shoulder, rpm of tool in

chuck parameter before and after is tuned to obtain more refined results with diagnostic

and multiple Regression report to find fine-tuned parameter subset for friction stir welding

with better % of retained super alloy feature .Also as apart from smart material as hardness

and stress factor in Induction Brazed weld was of good quality, its process parameters are

also made for real time parameter testing by double exponential method.


The real-time parameters were optimized by the Double Exponential Method using the

formula & DOE optimized [118-120].

Where, µ is the location parameter and β is the scale parameter, µ=0 and β=1 are used for

this double exponential method calculation based on optimized parameters by DOE,

graphically its validation by an actual and smoothed factor of α and Y level trend is shown

in the figure 6.8.


103

Figure 6.8 Induction brazing by Nitinol wire

As discussed in equations (5) and (6) the location of solder tip as location factor and its

temperature in nugget zone is analysed. However by DOE as shown in figure 6.8 Double

Exponential method for smoothing by MAPE,MSD & MAD as accuracy measures and as

MAPE is suitable value to measure which is 2.94230 but however smallest value of MSD

0.69692 is selected, but this value unlike friction stir welding is higher when the

parameters are made to real time tuning. α smoothing constant in IB is 0.448324, γ is

0.066837 and for FSW it is 0.34561 and 0.412215 respectively, choosing FSW for

optimization and validation of the same.

The figure 6.9 to 6.12 shows DOE real time of parameters which by Blender simulation

shows as captured in camera does not show retained smart material feature specifically at

nugget zone as shown in figure 6.12 and 6.13. The paired t-test shows the comparative


104

analysis of IB and FSW with 0.43169 difference of α of FSW compared to IB is favorable

with parameter of power, voltage, frequency comparison of vo, tool angle and v1 tool

velocity ,v2 axial force,v3 rpm,v4 coefficient friction,v5 axial load with 90 % favorable

chance as shown in figure 6.11 and 6.12.

Figure 6.9 Screening design

Figure 6.10 Paired test for the mean of V0 and V1, summary report


105

Hence, after comparative analysis of two processes of Induction Brazing and Friction Stir

Welding, FRICTION STIR WELD is found to make solid state welding of NiTinol on

AISI 304 A with retained Smart material feature feasible. As shown in Figure 6.9,

screening it states that using 12 runs of experiment it gives 1.68 value of standard deviation

and with 24 run 1.06, based on this 18 runs were made of experimental trial.

As shown in figure 6.10 and 6.11 paired t test is used to study relationship of these two

parameters of Power and Velocity to decide experimental run value.

Figure 6.11 Paired test for the mean of V0 and V1, diagnostic report

As shown in figure 6.13 (a) & (b) the specimen is analyzed by Blender software to

adjudge Real time parameter analysis of Friction Stir Welded specimen and Induction

Brazed specimen. The image shows that in Friction Welded specimen the flow of weld is

tangential unlike Induction Brazing, hence retained values of NiTinol traces are found in

Friction Stir Welded specimen for almost 35 seconds, which makes this process of welding

by optimized real time parameters in Friction Stir welding method. However, in Induction

Brazing traces of NiTinol were not there in Welded specimen though hardness of joint was

of good quality also it lacked aesthetic finish like Friction stir welded specimen.


106

Figure 6.12 DOE of Real-time parameters welding by calculation and camera captured the

flow of weld (a)

Figure 6.13 DOE of Real-time parameters welding by calculation and camera captured the

flow of weld (b)

STUDY OF DOE, SIMULATION AND ANALYTICAL RESULTS OF VARIOUS JOINERIES

107

CHAPTER 7

STUDY OF DESIGN OF EXPERIMENT,

SIMULATION AND ANALYTICAL RESULTS

OF VARIOUS

JOINERIES AND THEIR DISCUSSIONS

This chapter deals with experimentation results presented after verification by numerical

assessment for FSW & Induction Brazing joinery methods by analytical validation by

Poisson, Johnson-Cook Model calculation at various modes of parameter testing for

comparative analysis of optimized parameters of DOE with Linear Regression & Fitness to

Good Test, Simulation & Lab Test Report which arrives with finding the bias error for

deciding the suitable range of parameter for selected two joinery methods for NiTinol wire

on AISI 304 plate. These processes tend to find analysis in various forms.

7.1 Parameter Validation by Design of Experimentation using Poisson & Johnson-

Cook Model for the test run of Welding later to be validated by computational

Method

Parameter for experimentation of Friction Stir Welding & Induction Brazing was first set

by DOE method and each parameter was further validated by Poisson process, Johnson-

Cook Model and linear regression fit and Chi-square % defective samples after an

optimized parameter with the further diagnostic report is shown in figure 7.1. Butt-welded

AISI 304 A 250 L×100W×1 thick and NiTinol basic properties are shown in Table 7.1.

NiTi (SMA), martensitic Nickel content 50.8 ± 0.4 at − % 49.7 ± 0.4 at − % Titanium

content Balance Balance Young’s modulus 70-80 GPa 23-41 GPa Tensile strength,

annealed ~ 900 MPa Tensile strength, cold-work hardened Up to 1900 MPa Poisson’s ratio

0.33 Elongation at break, annealed 20-60% Elongation at break, cold-work hardened 5-

20%, Melting point ~ 1310 °C, Density 6.45-6.5 g/cm3, Thermal conductivity ~ 18 W/mK

to ~ 9 W/mK.


108

Table 7.1 Basic Properties of AISI 304 A & NiTinol

C Cr Ni M n Mo Si P S Fe

0.03 16 10 2 2 1 0.045 0.03 balance

Parameter NiTi SMA

Martensite 304

Density [g/cm3] 6,5 8

Fusion Temp [ºC] 1240-1310 1450

Thermal Conductivity

[W/m ºC] 18 16

Heat Capacity [J/g ºC] 0,32 0,5

Thermal expansion ratio

[10-6/ºC]

Thermal Conductivity (W/mK)

11

~ 9

17,5

Ultimate Tensile

Strength [MPa] 754-960 500

Young’s modulus

[GPa],Poisson’s Ratio

23+41

0.33 193


Figure 7.1 shows the Chi square test conducted for Friction stir welded specimen by

providing hypothesis test of parameter of temperature with subset range of temperature

frequency available, stating value of p is less than 0.005 so null hypothesis is rejected for

defectives at temperature produced at more than 1200 rpm is rejected stating there is

significance association with this parameter.

Figure 7.1 Chi-square test for Nitinol wire by Temperature


109

As shown in figure 7.2 for mean defect per unit (DPU) upper CI is lower in Friction stir

welded specimen as upper CI, confidence Interval is less than target with sample specimen

adequate tested for measuring process percentage defective of 12 specimen tested with

frequency target of 8 with lower control limit of 941.8 and chart show the process is in

control limits and Poisson plot shows that point follows straight line limits which shows

Poisson distribution is true for 900 rpm and 1200 rpm.

Figure 7.2 Poisson process capability report for rpm

As shown in figure 7.3 original parameter used and transformation data follows normal

distribution, α is 0.05, p value is less than 0.005, however transferred data is closely

follows the fitted value stated that normal distribution is not a good fit, but this was due to

less specimen welded put on test as a result probability plot was subsequently evaluated for

result analysis with Poisson test as shown in figure 7.4 to 7.8 which assessed susceptibility

of Friction stir welded specimen.


110

Figure 7.3 Johnson transformation for V0, rpm, mm/s

Figure 7.4 Before/after Poisson capability comparison for run order vs 1, diagnostic report


111

Figure 7.5 Before/after Poisson capability comparison for run order vs 1, summary report

Figure 7.6 Poisson capability analysis for f


112

Figure 7.7 Probability plot for rpm

Figure 7.8 Before/after Poisson capability comparison for centre Pt v/s Std Order_1


113

As shown in figure 7.9 of IB variable unlike figure 7.10 main signal plot of FSW main

effect parameter plot for signal stating how each parameter affects Response characteristic

stating output voltage has maximum with maximum coating of friction stir welded

specimen thickness minimal and as the lines are not parallel there is interaction amongst

all the variables.

Figure 7.9 Main effects plot for signal

Figure 7.10 Main effect plot for signal (b)


114

Figure 7.11 shows the contour plot of operating current vs max coating thickness for FSW

darker areas indicates good quality of welded specimen at that parameter range. These

parameters are connected as they have same response values deduced from previous

graphs. As the contour lines are arranged closely stating that the values of parameters

changes rapidly as shown optimized as shown in figure 7.12 which shows 3 dimensional

view of parameters upset force, rpm and hot rolled and contour plot showing two

dimensional view shows optimization of parameters in limits of FSW procedure.

Figure 7.11 Contour plot of Power v/s Operating Current, Max. Coating thickness

Figure 7.12 Surface plot of RPM v/s Upset force v/s Hot rolled %


115

The Chi-square test was conducted to find an association between rpm and frictional heat

generated, test report reveals that p=0.078 and the % level defective is not significant after

analyzing parameters range stating the association between rpm and frictional force

depends significantly. Hence Poisson process capability report for rpm was conducted for

samples which stated 1200 rpm with the optimized parameter for defect-free joinery.

Johnson Cook Model analyzed the strain rate and based on this pseudoelasticity which

determined the range of parameter set for the heating rate and temperature, for results

confirmation with experimentation procedure. The range of parameters resulted in an

increase in 91 MPa tensile strength at HAZ with strain hardening of 0.004. Signal Noise

ratio determined the rank of parameter affecting joinery, stating that rpm has a major effect

amongst all the parameter set for experimentation procedure.


As shown in figure 7.13 Poisson Capability report states that chance of producing defective

items deteriorated from 78.17 % to 51.3% with CI level before and after increased stating

that overall process capability yield is -27.3 % stating that parameter subset cannot be

optimized further.

Figure 7.13 Before/after Poisson capability comparison for run order vs 1


116

Figure 7.14 shows Johnson transformation for optimized parameter of power current for IB

with NiTinol wire which shows p value is > than α value, even scatter values of z states

that parameters optimized for IB process is not appropriate for retained smart material

feature at specific temperature.

Figure 7.14 Johnson transformation for power

As the number of selected specimen was small probability plot was made which shows as

shown in figure 7.15 that from parallel line the points fall apart so this optimization in

terms of finding the retained smart material feature with measured temperature in nugget

zone reveals devoid of traces.

Figure 7.15 Formation for current density in coil


117

As shown in figure 7.16 Pareto chart analysis of parameter of IB, grey lines depict that

non-significant values which were in hindrance to increased hardness was removed but

despite the results of IB were not as favorable unlike Friction stir welded specimen.

Figure 7.16 Fit linear model for V3.1

Figure 7.17 Interaction plot for signals


118

As shown in figure 7.17 signal to noise ratio is plotted, which identified power, output

voltage, cooling rate, coating thickness as control factor levels for optimizing parameters

of Induction brazing process which were further assessed by process capability. Based on

this, as shown in figure 7.19, 2 D and figure 7.20 3D surface plot generated of optimized

parameter Power frequency and current density.

Figure 7.18 Interaction plot for signals (b)

Figure 7.19 Contour plot of Std Order vs f, j


119

Figure 7.20 Surface plot of STd Order v/s f, j

For determining the parameter under specification limit, however compared to process

capability report of Friction stir welding process the parameters optimization done, unlike

of Induction brazing process comparatively parameters are not under specification range,

hence parameters of Induction Brazing are not analytically validated for the same.

Table 7.2 DOE Parameter comparison for FSW and IB

Distribution Location Shape Scale Threshold

Normal* 1038.46154 155.66236

Box-Cox

Transformation*

0.00000

0.00000

Lognormal* 6.93517 0.14927

Exponential 1038.46154

2-Parameter Exponential

149.99473

888.46194

Weibull 8.00775 1104.65400

Smallest Extreme Value

1113.66574

130.22607


120

Largest Extreme Value

965.77236

119.09036

Gamma 48.59457 21.36991

Logistic 1033.31562 96.60068

Loglogistic 6.93024 0.09263

Table 7.3 Parameter Exponential by Poisson’s Method

Distribution AD P LRT P

Normal 2.195 <0.005

Box-Cox Transformation 2.195 <0.005

Lognormal 2.195 <0.005

Exponential 4.613 <0.003

2-Parameter Exponential 4.586 <0.010 0.000

Weibull 2.332 <0.010

Smallest Extreme Value 2.332 <0.010

Largest Extreme Value 2.458 <0.010

Gamma 2.354 <0.005

Logistic 2.088 <0.005

Loglogistic 2.088 <0.005

Hence as shown in Table 7.2 and 7.3 parameter comparison of FSW and IB is done by

mentioned methods, for additional parameter LRT P (likelihood ratio test) p value along

with AD (Anderson Darling) test Logistic and Log logistics of AD is smallest which states

fit value of 2.088 for Friction Stir welding process, all the distribution values of p is below

0.005 and hence it falls under normal process for LRDP including and hence further

validation of optimized parameters of Friction Stir welding was done by 2-parameter

Exponential by Poisson method.

The DOE method parameters comparison stated as shown in Table 7.4 and 7.5, that 2-

Parameter Exponential is the suitable method as the threshold is 888.46194. Poisson

Capability report and DOE report statistics defined the range for analytical validation of

parameters.


121

Table 7.4 Induction Brazing DOE t value and p-value

Difference

of Levels

Difference

of Means

SE of

Difference 95% CI T-Value

Adjusted

P-Value

70 - 60 7.44 7.75 (-12.40, 27.27) 0.96 0.807

80 - 60 49.26 8.64 (27.16, 71.36) 5.70 0.000

90 - 60 4.11 9.00 (-18.92, 27.14) 0.46 0.989

100 - 60 0.26 8.01 (-20.23, 20.76) 0.03 1.000

110 - 60 0.82 8.22 (-20.23, 21.86) 0.10 1.000

Robotic& Manual Friction Stir Welding DOE t value and p-value

Table 7.5 Mechanized & Manual Friction Stir Welding DOE t value and p-value

Difference

of Levels

Difference

of Means

SE of

Difference 95% CI T-Value

Adjusted

P-Value

70 - 60 7.44 7.75 (-7.94, 22.81) 0.96 0.340

80 - 60 49.26 8.64 (32.13, 66.39) 5.70 0.000

90 - 60 4.11 9.00 (-13.74, 21.96) 0.46 0.649

100 - 60 0.26 8.01 (-15.63, 16.15) 0.03 0.974

110 - 60 0.82 8.22 (-15.49, 17.13) 0.10 0.921

80 - 70 41.83 8.30 (25.37, 58.29) 5.04 0.000

90 - 70 -3.33 8.68 (-20.54, 13.88) -0.38 0.702

100 - 70 -7.17 7.65 (-22.34, 7.99) -0.94 0.350

110 - 70 -6.62 7.87 (-22.23, 8.99) -0.84 0.402

90 - 80 -45.15 9.48 (-63.95, -26.36) -4.77 0.000

100 - 80 -49.00 8.54 (-65.94, -32.06) -5.74 0.000

110 - 80 -48.44 8.74 (-65.78, -31.10) -5.54 0.000

100 - 90 -3.85 8.91 (-21.52, 13.82) -0.43 0.667

110 - 90 -3.29 9.10 (-21.34, 14.76) -0.36 0.718

110 - 100 0.56 8.12 (-15.56, 16.67) 0.07 0.946

7.4 Computational Validation of Optimized parameters of Friction Stir Welding and

Induction Brazing

As DOE parameters and simulations in Friction stir welding and Induction brazing

processes are dependent on the flow stress input data, the flow stress is computed from

empirical models based on material parameters, the values of which are derived from

various mathematical optimization techniques. The derived flow stress parameters vary

based on the nature of techniques used and the flow stress testing procedure utilized. These

results are in variations in the numerical simulation results when working with different

models. In this work, the Johnson-Cook flow stress model is tested for its sensitivity


122

towards the finite element (FE) results. The test is conducted with AISI 304 A with NiTinol

Wire and the process is simulated in MATLAB. The flow stress computed from the Johnson-

Cook model is input to the FE code and the cutting force and chip thickness are recorded.

The FE results are input to the Minitab statistical code and an optimization process is

conducted based on the concept of the orthogonal array. Calculating the sensitivity of the

five parameters of the material model towards the tensile strength determination is the basic

procedure. Simeon Denis Poisson for describing the probability event in allotted time interval

wherein means is known with time as an independent factor. λ is the mean for rpm and the

following formula states the probability for mean equals to variance. The size of the plate is

350 mm × 150 mm butt welded AISI 304 A with NiTinol wire.

Probability event in allotted time interval wherein means is known with time as an

independent factor. λ is the mean for rpm and the following formula states the probability

for mean equals to variance.

(𝑌 = 𝑦|𝜆) = 𝜆 𝑦𝑒 –𝜆/ 𝑦! ----------------------------------------------------------------------------7(1)

(𝑌 = 𝑦|𝜆) is the probability mass function for specific rate y given in mean. The following

formula describes the Normal distribution also known as Gaussian function which is the

density function.

ϕ (𝑥) = 1 𝛿√2𝜋 𝑒 − 1 2 (− ) 2 , 𝜆 = 𝑒 𝑋β ------------------------------------------------------7(2)

X value determines the predictor’s vector and β is the regression coefficient vector,

Following is linear regression.

�̂�𝑖 = 𝛽0 + 𝛽1𝑥t

𝑦𝑖 = 𝛽0 + 𝛽1𝑥𝑖 + 휀t

휀𝑖 = 𝑦𝑖 − 𝑦̂ t --------------------------------------------------------------------------------------7(3)

Multivariable linear regression

𝑦𝑖 = 𝛽0 + 𝛽1𝑥t1 + 𝛽2𝑥t2 + 휀t --------------------------------------------------------------------7(4)

As per Okerblom, this formula is limited to fast welding

⸹L=0.355Q/AV

⸹T=17.4Q/sv×10-4

--------------------------------------------------------------------------------7(5)

Using the law of energy conservation and Fourier’s Law, considering the thermal


123

conductivity k being isotropic material, considering transition temperature of cured

NiTinol wire, 𝜃 (x, y, z, t) can be determined by:

∫ 𝜌𝑈𝛿𝜃𝑑𝑉 + ∫ 𝑘∇2 = ∫ 𝛿𝜃𝑞𝑉𝑑𝑉 + ∫ 𝛿𝜃𝑞𝑠𝑑𝑆 ----------------------------------------------------7(6)

V is considered the volume of AISI 304 plate, S as its surface area, U NiTinol time rate of

internal energy, r2 is Laplace operator, qs as heat flux per unit area, and qv is external heat

supplied per volume determined by moving frictional heat source in manual as well as

Robotic Welding method. For friction stir welding, the welding speed, tool rpm, axial

pressure on the tool, tool tilt, and design of tool are the main independent variables that

controlled its process whereas heat generation rate, temperature field, longitudinal

direction force, cooling rate, the torque of tool and the power are dependent variables

based on these independent variables. The peak temperature increases with an increase in

rotational speed of works piece and axial pressure as a tool in mandrel are held stationary,

whereas the increase in welding speed decreases peak temperature. AISI 304 butt welded

due to frictional heat generated using NiTinol wire as filler material which is considered

part of welding plate and is deformable bodies in FE Simulation. The dimension of the

plate is 400 mm×200mm and thickness 3.00 mm and 3.5 mm for simulation. Whorl

tapered with thread was used for this experimentation with the ratio of pin volume to

cylindrical volume is 0.4 with swept volume to pin volume is 1.8 .⸹L is longitudinal

shrinkage, Q is energy input defined by welding current its voltage and efficiency. A is

denoted by the cross-sectional area of AISI 304 A plate butt welded, v is the welding

speed, a is the coefficient considered for thermal expansion, q is density, specific heat cp,

⸹T transverse shrinkage of the plate, thickness of NiTinol Wire. Free Energy function for

NiTinol Wire two-phase.


124

The temperature modulation after post-weld treatment of Mechanized Friction Stir, Manual

Friction Stir Combined & Induction Brazing is validated by MATLAB software. The

results show that Nitinol wire welded in Robotic Friction Stir welding at the contact point

has minimum distortion and the UV texture report shows that coating is maximum at the

periphery of joinery. The surface of contact point temperature of AISI 304 A plate welded

by NiTinol Wire for Johnson-Cook Model & Chi-square and goodness to fit test using the

given formulas, validating temperature by macrographs with frustum stud for friction stir

welding showed that consuming less weld power unlike square with less temperature.

Poisson Capability before and after optimized parameter analysis for temperature

validation for Friction Stir welding for speed rpm, by computational with 0.4 mean for

p>0.013 approves the hypothesis & DOE Method as shown above Poisson capability

report. Shielding gas used was Argon as the inert gas, weld travel speed for selected two

process parameter validation was 55 cm/minute, NiTinol wire feed rate was 8 m/min with

contact tip to tool traverse of 12 mm using the base current of 30 A for calculation.

As shown in figure 7.21 and 7.22 graphically and simulative comparison of all processes

done based on Parameter subset as shown in Table 7.6 with characteristic feature.


125

Figure 7.21 Graphical Comparison of Six Welding Process based on Joint Analysis

Figure 7.22 Simulation result


126

Table 7.6 Analytical Comparative analysis of Experimental Data Parameter

.Para

met

er

s/R

esu

lts

P

uls

ed A

rc

Wel

din

g

Mic

ro P

lasm

a

Arc

Wel

din

g

La

ser

Wel

din

g

Fri

ctio

n S

tir

Man

ual

&

Rob

oti

c

Wel

din

g

In

du

ctio

n

bra

zin

g

C

ap

aci

tor-

Dis

charg

e

Ampere

55 Ampere

22(0.5LpM &

8LpM of

Argon

Shielding gas

66 Ampere

304 A steel plate

8Ø 50×80 mm

240 A & 280 A

2 KW

power

supply.

62 A

Voltage

9 V to 10 V

40

9-10 V

Upset force 2.1

tons, Friction

force 1 ton

220 V I

Phase

220 V I Phase

Pulse frequency

3.5

----

----

------

250 KHz

110KHz

Secondary 50% of 1200 rpm suitable

from

900,1000,1100

rpm,10 mm/sec

for Robotic

Current/ main

Traverse current

speed (27.5 amp)

Pulse Duty

Cycle/

Temp. of

operation

50%

----

-------

345º C

Manual

FSW 300º C

Robotic FSW

80%

(Nitinol

at liquidus

temperat

ure above

470°C

80%

(Nitinol at

liquidus

temperatur

e above

410ºC

Travel

Speed/Axial

Load/Upsetting

force

Power

Force Control

140 mm/min

----

-------

Upset time: 1-sec

Soft force-time :

2.5

sec,115mm/sec

welding speed

with traverse

speed 2.76

mm/min

1 KVA

3000 N Down

(Robotic)

7 seconds

Upsetting

force 20

KN

UTS Actual N/mm2

218.79

514.5

4.07

Partial

No

UTS DOE 297 82.17 N/mm2 502.47 441.12 334.27

Load KN 495 310 552.34 477.5 417.8

Pseudoelasticity 4.9 1.53 7.83 6.11 5.280

behavior in the No Partial YES Partial No

tensile test

Bending Test

Straightness No No YES Partial No

Recovery


127

7.5 Simulation Results of Joinery Process

Simulation of parameters of FSW is done by MATLAB & Blender Software. As shown in

figure 7.23 simulation process done by MATLAB determines of tensile strength of

200N/mm2 for FSW and as shown in figure 7.24 the best fit value for process parameter of

FSW is 0.491302 with current temperature of frictional force is 0.99804 best functional

value as validated of FSW.

Figure 7.23 Simulation result (b)

Figure 7.24 Simulation result (c)


128

Figure 7.25 Simulation results (d)

Figure 7.26 Surface plot


129

Figure 7.27 Surface plot (b)

The Table 7.7 below shows the validated parameter subset of FSW, however as validated

optimized parameters of FSW for NiTinol joinery on AISI 304A, based on Tensile strength

bias error of all three processes of simulation, analytical & experimental shows minimum

bias error of 0.00278 for friction stir welding at 1200 rpm with 90 mm/sec tool velocity at

3.5 KN axial load and 2.5° tilt of tool angle at tool post of lathe machine, whereas for

Robotic Friction at 1200 rpm with welding speed 10 mm/sec and 1 KVA force control

3000 down force and 300 °C. Based on DOE results of mean and Chi-square and Pareto

analysis stated the frequency of defect of FSW and IB with the count of 26 for further

analytical validation procedure done.

Table 7.7 Micro grain Structure of Joinery Method to determine shape memory alloy

features

Test DF Estimate Mean Chi-Square P-Value

Deviance 112 32.99525 0.29460 33.00 0.004

Pearson 112 18.00000 0.16071 18.00 0.049

AS shown in Table 7.7 for FSW, deviance and Pearson Method validation opts for

deviance with higher Chi value and lower P value which validates optimized parameters of

FSW. Deviance method further measured the discrepancy of parameters of FSW

formulated and experimental value maximizing the log likelihood functions using the

scaled deviation of the Poisson Model. Further, based on computation and the graphical


130

analysis, for validation and acceptance criteria research data were validated of FSW, of

research paper [121], compared which proves the correctness of experimentation of FSW

by optimized parameters as bias error of 0.002078 of performed experimentation of FSW

method is less compared to Research paper of 0.0234, hence validating the propounded

parameter subset with optimum module for Friction stir welding comparing UTS, impact

strength & elongation of 18 samples as shown in series form in figure 7.28 with

parameters.

Figure 7.28 Graphical analysis based on comparative analysis

However, table 7.8 finally depicts the comparative analysis of computational, simulation,

linear regression with parameters of FSW of Tool angle(Vo), Axial Load (V1), Tool RPM

(V2), Tool Velocity (V3), Tool Thickness (V4) which is 1mm, hence in Table 7.28 is not

taken. Bias % Error of welded specimen of FSW by Nitinol Wire on AISI 304A is

compared of each parameter by Computational, Linear Regression Simulation to formulate

the best fit optimized parameter set, which is validated by Research paper. The validated

parameter shows less % bias Error as per Research paper [121].

The formulated parameter for FSW is shown in Table 7.8 with highlighted of 14 series.

Vo-2.5 mm, V1 3.5 mm, V2 1200 rpm, V3 90 mm/sec with % bias error 0.00278 is

selected for the same.


131

Table 7.8 Comparative analysis of computational simulation linear regression with

experiment value of FSW

Vo V1 V2 V3 V4 Experimental

Value Computational

% Bias Error

Linear Regression

% Bias Error

Simulation % Bias Error

3 3 900 80 1 211.325 211.0901 -0.2344 198.3421 0.0614 199.43 0.056

2 3 900 90 1 219.146 219.3668 0.2212 196.1549 0.1049 195.15 0.109

2 3 900 120 1 223.237 223.4688 0.2321 204.3422 0.08464 205.34 0.08008

2 4 1100 90 1 209.124 209.3372 0.2133 212.9732 -0.01840 213.8 -0.022

3 4 1100 120 1 221.237 221.0251 -0.2116 216.3211 4.9159 217.23 -0.0181

3 4 1100 90 1 205.633 205.4197 -0.2131 211.18732 -0.02222 212.32 -0.0325

3 3 1200 80 1 227.239 227.5812 0.3421 213.4321 0.0707 215.65 0.055

2 3 1200 90 1 234.367 234.1361 -0.2311 214.5732 0.0844 211.43 0.097

2 3 1200 120 1 241.29 240.9686 -0.3211 216.1733 0.114099 217.21 0.09979

2 4 900 90 1 220.129 220.3603 0.2314 210.432 0.04405 213.43 0.0304

3.5 4.5 900 80 1 218.324 218.5784 0.2543 206.7231 0.05313 208.21 -0.083

3.5 4.5 1100 120 1 232.122 231.9986 -0.1232 212.3224 0.08529 211.12 0.090

3.5 3.5 1100 80 1 227.13 227.253 0.1232 209.7654 0.07645 208.21 0.0833

2.5 3.5 1200 90 1 238.322 238.483 0.00278 224.1232 0.05957 225.23 0.054

2.5 3.5 1100 120 1 238.232 237.911 -0.3211 213.5432 0.1041 214.21 0.099

2.5 4.5 900 90 1 227.33 227.30666 0.02314 208.6543 0.0821 208.12 0.0845

3 4 1100 80 1 224.239 234.47007 0.2311 210.2145 0.06254 210.13 0.1038

3 4 1200 90 1 239.363 239.57725 0.21445 211.2345 0.11751 210.21 0.121

Based on figure 7.29 and 7.30 the above values of Linear Regression have been deduced.

Further Pareto Chart of IB and FSW is done to analyses that though strength results of

Induction Brazed specimen shows positive results but the main objective of retained smart

material after welding by NiTinol on AISI 304A is not present, however FSW specimen of

optimized and validated results shows the traces of Smart material as has been propounded

in previous chapters based on Lab reports of grain structure, simulation by MATLAB fitted

value & Blender software by surface texture, to show the presence of NiTinol material

which is decisive of contraction, expansion, pseudo elasticity and light weight of welded

part, which is found only FSW specimen as shown in figure 7.32 by stress strain diagram

after optimized parameter.


132

Figure 7.29 Residual’s v/s fitted values and observation order

Figure 7.30 Multiple regression for current dens


133

Figure 7.31 Comparative analysis of all three methods for FSW & IB for block 1 and

block 2

Figure 7.32 NiTinol & AISI 304A Stress-Strain Curve for FSW

The stress-strain curve depicts the stress-strain plateau of retained smart material

characteristics after well, due to different martensite properties of Ni-Ti and AISI 304.

Steel, during Friction stir welding unlike Induction Brazing welding due to changed

solidification modes, microstructure study revealed epitaxial growth of NiTi which

identified martensite structure during cooling of weld resulting into crack-free weld zone.


134

The formation of fine intermetallics which is higher than base material AISI determines the

hardness strength of repaired joinery by FSW. However, test results show that when

frictional heat generated is made to tend closer to base material compared to farther in the

sample the prior one shows more UTS results.

7.6 Comparative Results of Friction Stir Welding and their discussions

The experimental results reveal that welding NiTinol requires utmost calculative

parameters control of amperage, voltage, pulse frequency, pulse duty cycle, secondary

current and travel speed which played vital role in characteristic weld strength. As Nitinol

is a very hard material presence of oxide with 45% Titanium makes difficult task for

welding. The properties of super elasticity and shape memory did not remain intact while

performing these welding processes except in friction stir welding process. However,

tensile strength tests revealed that degradation and resistance to permanent deformation in

nugget zone was noticed in particular to Plasma Arc, Capacitor Discharge & TIG Welding.

Tensile strength almost 70-72% of the base metal maintained permanent deformation

below 0.2 % after a 6% deformation of welded specimen proved to undergo the least

thermal degradation except in Friction stir welding. The tensile strength of Capacitor

discharge welding process was prominently affected by welding time and stud material.

Following are the implications of NiTinol wire on AISI 304 A by six selected joinery

process as elaborated in Table 7.9.

Table 7.9 Analytical Comparative analysis of Experimental Data Parameter

Parameters /Remarks

TIG PAW LW FSW- Lathe

IB CD

Experimental UTS N/mm2

218.79 219.12 82.17 238.478 227.12 221.27

DOE 224.5 229.53 110.12 243.127 234.46 219.81

Load 4.07 4.9 1.53 7.83 6.11 5.280

Pseudoelasticity behaviour

Partial No Partial YES Partial No

Bending 136 137 132 145.6 138 139.1

Straightness Recovery

No No No YES Partial No


135

Amongst all six-joinery experimental investigation done after parameter subset obtained by

DOE, it was found that Friction Stir Welding was the most apt method for NiTinol wire

joinery, hence its parameters were further optimized by computational, Simulation by

MATLAB & Blender Software. Table 7.10 gives comparative analysis between

experimental and analytical as based on research paper for validation and it was found less

compared to research which showed 0.02854 to actual with 0.00287% bias error which

showed the fit, based on calculations of research paper [121] & if superior value.

Table 7.10 Friction Stir Computational Validation based on Research Paper

As shown in figure 7.33 graphically comparative analysis of optimized parameters of FSW

validated by three methods of analytical based on Research paper validated formula of

Tensile, Impact and hardness and Simulation value by MATLAB & Blender along with

Lab Reports and Linear Regression in comparison to actual experimentation result show

simulation shows better results and Experimental and actual values are close to each other.

Tensile strength

174.2-1.03V0+9.09V1+0.01463V2+0.1243V3+0.12V4 ------------------------------7(14)

Elongation

1.76+1.832V0+0.615V1-0.000659V2 ------------------------------------------------7(15)


136

Impact Strength

0.915+0.0031V0-0.0376V1+0.000118V2+0.000119V3-0.0422V4 --------------------7 (16)

Figure 7.33 Comparative analysis of FSW Experimental, Analytical & Simulation Data

Parameter With bias error

As shown in figure 7.34 comparative analysis of parameter is done and as shown in figure

7.35 comparative analysis of properties of optimum four welding processes from six

selected technologies after analyzing graphically, shows that ultimate tensile strength of

Friction Stir Welding is 238.483 MPa unlike all other processes as well retained smart

material properties of pseudoelasticity as shown in joint analysis phases stages from 0 to 8

with phase transformation Ar. Hence, solid state Friction Stir Welding method is found to

be the most appropriate joinery technique for welding AISI 304A with NiTinol Wire.


137

Figure 7.34 Comparative analysis of Parameter subset

Figure 7.35 Comparative analysis of properties of optimum four welding processes from

six processes

CONCLUSION AND FUTURE SCOPE

138

CHAPTER 8


This chapter finally depicts the summary with concluding remarks marking the future

scope of this research work. The perspective of this research is to understand the

phenomenal transition of phases of NiTinol during welding and retaining its smart material

characteristic features post-weld with AISI 304 A plate using selected six joineries. The

parameters for Experimental Investigations are propounded based on research and then

based on the Design of Experimentation Taguchi Method, these subsets of parameters were

used to conduct respective joinery by NiTinol Wire. Comparative analysis of these six

selected joinery methods based on joint strength, pseudoelastic features based on

Compression, UTS, bend test, and micro-grain structure by optical microscope, further

zeroed down on two joinery methods of Friction Stir Welding – Manual Lathe & Robotic

Friction and Induction Brazing. The parameters of these processes were further optimized

to make the defect-free joint.

The research of the validation of optimized parameters was further based on

Computational Poisson Johnson-Cook Model, Energy distribution and Simulation UV

surface Texture and Mesh analysis. Based on these statistics and graphical analysis,

Friction Stir Welding based on a Manual Lathe process for batch work of repair finds

suitability & Robotic Friction for mass production with complex geometry components.

The study showed that joining NiTinol with NiTinol is showing good results compared to

dissimilar materials due to the formation of oxides during welding. Also, the heat input

source played a crucial role in retaining smart material features in the welded specimen

which was kept minimal up to 1 J as the diameter of NiTinol wire used is 0.98 mm for the

experiment.

The study showed that as heat input source increased above I J embrittlement in the

specimen was found. Therefore, to overcome it curing of NiTinol wire was used after

acetone bath for 15s and AISI 304A plate base plate was further etched to remove

oxidation content.


139

8.1 Conclusion from various joinery techniques

Manual & Mechanized Friction Stir Welding produced quality repair strength amongst

selected six joinery methods. Lab reports showed retained pseudo elasticity & smart material

characteristics for Friction Stir Welded specimen unlike Induction Brazing, also tensile

strength in Friction Stir Welding almost 60-62% of the base metal was maintained with

permanent deformation below 0.3 % after a 7% deformation of welded specimen proved to

undergo the least thermal degradation. It was observed that AISI 304 A steel welded with

NiTinol wire is less prone to cracking in FSW. Also, it was observed that Ti laced curing

in NiTinol wire and dip in HCL bath for removing oxides resulted in epitaxial NiTi film at

the contact zone of FSW. Tool angle and tool velocity for frictional heat generation at the

contact zone is an important parameter for FSW. Future scope for Friction Stir Welding

process can be using this optimized process welding parameters for dissimilar welding of

AISI 304 repairing and exploring on gravity pool of melt zone of nugget area and curing

technique.

• Laser Welding not produced a favorable result due to the long pulse used in the

experimentation procedure but the specimen obtained was a clean weld as no

contact was done with the source. Welding speed and shielding gas played a

prominent role in the process. HAZ showed an Af transition change resulting in the

weak zone at the contact area. The corrosion performance when assessed showed

that after post-weld treatment it improved.

• Plasma Arc Welding the plasma arc source heat input impact was drastically

producing significant negative changes in the micro-grain structure of NiTi as

revealed by lab test report also UTS was 297 MPa. The mechanical test showed that

the specimen fractured at HAZ with the presence of rough grains and was devoid of

shape memory features. However, gravity melt pool formation was substantially

progressive which suggests that tooling and proper heat treatment process can

improvise weld strength.

• Tungsten Inert Gas Welding Cyclic loading showed rupture of 10%, this method is

favorable with a short weld distance and had less grain dislocation at fusion zone

but remelting stage caused NiTi forming oxide layers losing pseudoelastic content

& weak joinery. The bead geometry was with a general slope observed.

• Capacitor-Discharge Welding The source location played an important role along

with stud design area but as AISI 304 A plate butt welding area was substantially

less, stud penetration was proper but the force exerted for stud dislocated stress


140

valence at fusion zone hence this welding produced no shape memory properties

but clean & crack free joint was made.

• Induction Brazing Thermal cycles harmed pseudoelasticity content due to remelting

process. The bead geometry, however, was with a gentle slope hence fracture and

embrittlement were reduced producing quality weld with good contact resistance.

8.2 Main Concluding points of Most Apt Joinery Friction Stir Welding

Six joining techniques were selected to experiment parameter subset formulating based on

research analysis to find the most apt method with retained smart material feature in

welded specimen as explained fundamental principle of conventional method and using

Nitinol wire joinery.

Challenges faced in joining the dissimilar material with NiTinol wire in theses selected

techniques of austenite steel was basically reduction in strength as well intermetallics.

Other main challenge was to retain both superelastic and shape memory alloy feature of

NiTinol wire which was done by phase transformation temperature control. Other major

hindrance for desired result was related to non compability of material properties, fusion

zone temperature.

• A slight amount of grain size refinement in the friction Stir processed zone caused

an increase in strength and a decrease in the Ar transformation temperature

compared to the base metal. Friction stir processed specimen was also hot rolled

76% at 850°C without cracking.

• As Spindle Force increased from 900 to 1200 rpm, weld time, burn off length,

actual upset burn off was found to be increased.

• With the increase in the spindle speed, more grain refinement occurred in the weld

compared to base material, ultrafine grained microstructure was obtained and the

twins were not observed like the base region.

• Hardness was found to be increased with the increase in spindle force due to the

increase in the mechanical work of the friction welding process which promotes

grain refining and consequent increase of resistance.

• The tensile strength is found to be increased with the increase in spindle force due

to the microstructure refinement in the welded region compared to base region,

hence higher strength in the weld and specimen is found broken outside the welded

regionFriction Stir Welding process can be using this optimized process welding

parameters for dissimilar welding of AISI 304 repairing and exploring on gravity


141

pool of melt zone of nugget area and curing technique of Nitinol wire with cross

configuration can give better strength of repaired part & NiTinol wire.

• Based on Lab report, software & Computational assessment, lab report showed

PAW & TIG tensile strength was not upto ASTM standards with no smart material

retaining after weld.

• Friction Stir Welding showed promising results showing smart material feature

with positive results.

• These parameters for FSW hence were further optimized and validated with

research paper.

• Manual & Mechanized Friction Stir Welding produced quality repair strength

amongst selected six joinery methods. Lab reports showed retained pseudo

elasticity & smart material characteristics for Friction Stir Welded specimen, also

tensile strength in Friction Stir Welding almost 60-62% of the base metal was

maintained with permanent deformation below 0.3 % after a 7% deformation of

welded specimen proved to undergo the least thermal degradation. Unlike

remaining five selected joineries distinct feature in welded specimen showed:

• Weld was continuous bead with spatter free

• No flux neither any shielding gas used in optimized parameter experimentation

• Devoid of cracks, shrinkage with low peak temperature.

• Narrow Heat affected zone was formed.

• Enabled consistent process of metal fusion.

• Joint preparation set up time was minimal unlike all other joineries.

• Complete surface weld was obtained as also deduced by surface texture with good

martensite and smart material traces at nugget zone. This method was found

suitable for joints with tight Dimensional control requisite. Using the principle of

Design of Experimentation for Parameter deduction and then optimized by

analytical and simulation produced favorable result.

• Friction stir processing of Nitinol with AISI 304 A plate is feasible. The processing

is done with a tungsten-rhenium tool & MS tool.

• The Nitinol retains its shape memory and super elastic properties due to its solid

state joining process, the specimen of AISI 304A in this study for austenitic and

NiTinol wire of 0.08 mm diameter with base plate of 1mm thickness were when

joined at 900, 1000, 1100, 12000 rpm produced desired properties at 1200 rpm.


142

• Grain refinement was observed at bead of fusion due to recrystallization with super

elastic plateau at 1200 rpm.

• The study of phase transformation done by differential scanning calorimetry of

processed samples to determine their austenite and martensite transformation

temperatures.

• Welded specimen showed regain of smart material feature after 34 seconds at

60 °C.

8.3 Future Scope

• Detailed Fatigue analysis and shear tests can be carried out for further

investigations of optimized parameters in selected joinery methods.

• Welding Technique can be investigated for higher thickness AISI 304 steel plates

by employing double-sided Friction Stir Welding.

• Genetic Programming application as well Poisson 2-way Polynomial of Friction

Stir Welding can be extended by employing on other materials such as copper,

titanium and magnesium for future studies.

Experimentation process of welding by all joinery process has further scope of findings for

future research work. NiTi to NiTi welding showed promising results in Laser Welding

unlike dissimilar materials so study should be done about fusion welding and its material

characteristic structure. Dissimilar materials joineries failed to retain pseudoelastic content

except Friction Stir Welding and the prominent reason was when remelting stage took

place NiTi formed the tenacity layer.

Proper curing and heat input source study can explore some positive results. During

experimentation it was found that set up as well configuration of NiTinol wire produced

different results which can be further studied. Post weld heat treatment as well as fusion

joining methods like crimping, swaging, adhesive bonding has wide area of scope of study.

Basic study of melting point control during amalgamation, formulating specific thermal

coefficient of expansion, controlling difference of electrochemical constituent with its

solubility can affect result if material chemistry studied. Nugget zone transition

temperature produced change in Af for phase transition from austenite to martensite which

needs to be studied. Validation by Finite Element can produce better results for optimized

parameter range.

143

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LIST OF PUBLICATIONS

1. Kripalani. Kavita, & Jain. P (2020), “Comprehensive Study of Laser Cladding by

NiTinol Wire”, Materials Today Proceedings by Elsevier Journal

https://doi.org/10.1016/j.matpr.2020.05.631 : ISSN: 2214-7853.

2. Kripalani. Kavita, & Jain. P (2020), “Experimental Investigations of Various joinery

methods repaired AISI 304 A plate with NiTinol Wire.”, by Elsevier Journal, Science

Direct, https://doi.org/10.1016/j.matpr.2020.07.522: ISSN: 2214-7853.

3. Kripalani Kavita & Jain P(2021)” Repair Work Done By Additive Manufacturing

Welding of Optimized Parameters by NiTinol Wire on 304 A Plate”, by Juni Khyat

Journal, ISSN:2278-4632

4 Kripalani Kavita & Jain.P (2021) “Experimental analysis of NiTinol wire joinery on

AISI 304 by selected technologies and comparative analysis of its optimized

parameters” by Journal of the Maharaja Sayajirao University of Baroda, published in

volume No:55 No.1(X) ISSN :0025-0422(UGC Care listed & indexed)

155

APPENDIX-I

LAB REPORTS

Invoice of NiTinol Wire

Inspection Certificate of NiTinol

Divine Metallurgy Report for PAW

156

Divine Metallurgy Report for PAW

157

HERTZ Metallurgy Report for FSW

158

Divine Metallurgy Report for Grain Structure of FSW

Divine Metallurgy Report for Mechanized FSW

159

APPENDIX-II

CALCULATIONS FOR FSW

Comparative analysis of computational simulation linear regression with experiment value

of FSW

Vo V1 V2 V3 V4 Experimental

Value Computational

% Bias Error

Linear Regression

% Bias Error

Simulation % Bias Error

3 3 900 80 1 211.325 211.0901 -0.2344 198.3421 0.0614 199.43 0.056

2 3 900 90 1 219.146 219.3668 0.2212 196.1549 0.1049 195.15 0.109

2 3 900 120 1 223.237 223.4688 0.2321 204.3422 0.08464 205.34 0.08008

2 4 1100 90 1 209.124 209.3372 0.2133 212.9732 -0.01840 213.8 -0.022

3 4 1100 120 1 221.237 221.0251 -0.2116 216.3211 4.9159 217.23 -0.0181

3 4 1100 90 1 205.633 205.4197 -0.2131 211.18732 -0.02222 212.32 -0.0325

3 3 1200 80 1 227.239 227.5812 0.3421 213.4321 0.0707 215.65 0.055

2 3 1200 90 1 234.367 234.1361 -0.2311 214.5732 0.0844 211.43 0.097

2 3 1200 120 1 241.29 240.9686 -0.3211 216.1733 0.114099 217.21 0.09979

2 4 900 90 1 220.129 220.3603 0.2314 210.432 0.04405 213.43 0.0304

3.5 4.5 900 80 1 218.324 218.5784 0.2543 206.7231 0.05313 208.21 -0.083

3.5 4.5 1100 120 1 232.122 231.9986 -0.1232 212.3224 0.08529 211.12 0.090

3.5 3.5 1100 80 1 227.13 227.253 0.1232 209.7654 0.07645 208.21 0.0833

2.5 3.5 1200 90 1 238.322 238.483 0.00278 224.1232 0.05957 225.23 0.054

2.5 3.5 1100 120 1 238.232 237.911 -0.3211 213.5432 0.1041 214.21 0.099

2.5 4.5 900 90 1 227.33 227.30666 0.02314 208.6543 0.0821 208.12 0.0845

3 4 1100 80 1 224.239 234.47007 0.2311 210.2145 0.06254 210.13 0.1038

3 4 1200 90 1 239.363 239.57725 0.21445 211.2345 0.11751 210.21 0.121

Bias Error in % = Experimental Value-Analytical Value × 100

Experimental Value

= 0.00278

160

Tensile Strength

174.2×2.5+9.09×3.5+0.014641200+0.12×1=238.483N/mm2

--Computational,

Experimental = 238.483 N/mm2 Bias Error = 0.00278

Vo =Tool Angle in °

V1 =Axial Load in KN

V2 =Tool RPM

V3 =Tool Velocity in mm/sec

V4 = Thickness of Plate, mm

Thickness of Plate V4 is same so value not taken in table Dimension

mentioned.

Elongation

1.76+1.8322×2.5+0.615×3.5-0.000659×1200 =7.7022

Impact Strength

0.915+0.0031V0-0.0376V1+0.000118V2+0.000119V3-0.0422V4

0.915+0.00775-0.1316+0.1428-0.0422=0.89175

161

Welding

Method

Nitinol to

Fused metal

AISI 304 A

As (°C)

Af (°C)

Ms (°C)

Mf (°C)

FSW Nitinol/AISI 61/65 94/96 51/54 6/29

IB Nitinol/AISI 52/54 87/93 41/67 4/23

Experimental Investigations on Repaired AISI 304 A by ...

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