Manufacturing Engineering: Select Proceedings of CPIE 2018 [1st ed.] 978-981-13-6286-6, 978-981-13-6287-3

Table of contents :
Front Matter ....Pages i-x
A Variable Viscosity Technique for the Analysis of Static and Dynamic Performance Parameters of Three-Lobe Fluid Film Bearing Operating with TiO2-Based Nanolubricant (Ashutosh Kumar, Sashindra Kumar Kakoty)....Pages 1-16
Friction Stir Welding of Shipbuilding Grade DH36 Steel (Avinish Tiwari, Pardeep Pankaj, Abhishek Bharadwaj, Piyush Singh, Pankaj Biswas, Sachin D. Kore)....Pages 17-34
Experimental Investigation on the Effect of Cryogenic CO2 Cooling in End Milling of Aluminium Alloy (M. Pradeep Kumar, M. Jebaraj, G. Mujibar Rahman)....Pages 35-47
Transient Thermal Analysis of CO2 Laser Welding of AISI 304 Stainless Steel Thin Plates (Pardeep Pankaj, Avinish Tiwari, Pankaj Biswas)....Pages 49-65
Transient Thermal Analysis on Friction Stir Welding of AA6061 (Nandan Kanan Das, Arun Kumar Kadian, Avinish Tiwari, Pardeep Pankaj, Pankaj Biswas)....Pages 67-82
Recycling of H30 Aluminium Alloy Swarfs Through Gravity Die Casting Process (C. Bhagyanathan, P. Karuppuswamy, K. Gowtham Kumar, M. Ravi, R. Raghu)....Pages 83-96
Effect on Mechanical and Metallurgical Properties of Cryogenically Treated Material SS316 (Jitendra Upadhyay, Anuj Bansal, Jagtar Singh)....Pages 97-107
Microstructure and Mechanical Properties of Lamellar Ti–6Al–4V ELI Alloy (Anil Kumar Singla, Jagtar Singh, Vishal S. Sharma)....Pages 109-116
Influence of Process Parameters on Surface Roughness Hole Diameter Error and Burr Height in Drilling of 304L Stainless Steel (Vipin Pahuja, Suman Kant, Chandrashekhar S. Jawalkar, Rajeev Verma)....Pages 117-135
Investigation of Impression Creep Deformation Behavior of Boron-Modified P91 Steel By High-End Characterization Techniques (Akhil Khajuria, Raman Bedi, Rajneesh Kumar)....Pages 137-150
Tribological and Machining Performance of Graphite-, CaF2- and MoS2-Coated Mechanical Micro-textured Self-lubricating Cutting Tool (Kishor Kumar Gajrani, Y. Bishal Singha, Mamilla Ravi Sankar, Uday S. Dixit)....Pages 151-165
Chemical Assisted USM of Acrylic Heat Resistant Glass (Kanwal Jit Singh, Jatinder Kapoor)....Pages 167-183
Study of Temperature Distribution During FSW of Aviation Grade AA6082 (Shubham Verma, Joy Prakash Misra, Meenu Gupta)....Pages 185-202

Citation preview

Lecture Notes on Multidisciplinary Industrial Engineering Series Editor: J. Paulo Davim

Vishal S. Sharma Uday S. Dixit Noe Alba-Baena Editors

Manufacturing Engineering Select Proceedings of CPIE 2018

Lecture Notes on Multidisciplinary Industrial Engineering Series editor J. Paulo Davim, Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal

“Lecture Notes on Multidisciplinary Industrial Engineering” publishes special volumes of conferences, workshops and symposia in interdisciplinary topics of interest. Disciplines such as materials science, nanosciences, sustainability science, management sciences, computational sciences, mechanical engineering, industrial engineering, manufacturing, mechatronics, electrical engineering, environmental and civil engineering, chemical engineering, systems engineering and biomedical engineering are covered. Selected and peer-reviewed papers from events in these fields can be considered for publication in this series.

More information about this series at http://www.springer.com/series/15734

Vishal S. Sharma Uday S. Dixit Noe Alba-Baena •

•

Editors

Manufacturing Engineering Select Proceedings of CPIE 2018

123

Editors Vishal S. Sharma Department of Industrial and Production Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar, Punjab, India

Uday S. Dixit Department of Mechanical Engineering Indian Institute of Technology Guwahati Guwahati, Assam, India

Noe Alba-Baena Department of Industrial and Manufacturing Engineering Universidad Autónoma de Ciudad Juárez Ciudad Juárez, Mexico

ISSN 2522-5022 ISSN 2522-5030 (electronic) Lecture Notes on Multidisciplinary Industrial Engineering ISBN 978-981-13-6286-6 ISBN 978-981-13-6287-3 (eBook) https://doi.org/10.1007/978-981-13-6287-3 Library of Congress Control Number: 2018968399 © Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

The present book “Manufacturing Engineering” is a detailed exposition of various manufacturing processes. Most of the chapters in this book have experimental work on varied processes that are conventional, micro-conventional, non-conventional, etc. Thus, the results reported could be of great value to industry and researchers. The Conference on Production and Industrial Engineering (CPIE) series, from which this special issue has been derived, was started by the Department of Industrial and Production Engineering, Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India, in March 2007. Subsequently, CPIE 2010, CPIE 2013 and CPIE 2016 were organized which could attract renowned academicians/ researchers, noted industry representatives and the delegates from countries like Canada, UK, France, Australia, Russia, Singapore, Iran, Egypt, Algeria, Bangladesh, Israel, Mauritius, Turkey and India. We would like to express our gratitude towards all the authors for contributing their valuable articles for our conference. Finally, we would like to acknowledge the reviewers for their pain-staking and time-consuming effort in reviewing manuscripts and providing their thorough evaluations for improving the quality of the articles. We would also like to express our sincere gratitude towards Springer Book Series and the team. Last but not least, we would also like to express our sincere gratitude towards our worthy Director (Professor) Lalit Kumar Awasthi for his full-hearted support for the smooth conduct of the conference. Jalandhar, India Guwahati, India Ciudad Juárez, Mexico

Vishal S. Sharma Uday S. Dixit Noe Alba-Baena

v

Contents

1

A Variable Viscosity Technique for the Analysis of Static and Dynamic Performance Parameters of Three-Lobe Fluid Film Bearing Operating with TiO2-Based Nanolubricant . . . . . . . . Ashutosh Kumar and Sashindra Kumar Kakoty

1 17

2

Friction Stir Welding of Shipbuilding Grade DH36 Steel . . . . . . . . Avinish Tiwari, Pardeep Pankaj, Abhishek Bharadwaj, Piyush Singh, Pankaj Biswas and Sachin D. Kore

3

Experimental Investigation on the Effect of Cryogenic CO2 Cooling in End Milling of Aluminium Alloy . . . . . . . . . . . . . . M. Pradeep Kumar, M. Jebaraj and G. Mujibar Rahman

35

Transient Thermal Analysis of CO2 Laser Welding of AISI 304 Stainless Steel Thin Plates . . . . . . . . . . . . . . . . . . . . . . Pardeep Pankaj, Avinish Tiwari and Pankaj Biswas

49

4

5

6

7

8

Transient Thermal Analysis on Friction Stir Welding of AA6061 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nandan Kanan Das, Arun Kumar Kadian, Avinish Tiwari, Pardeep Pankaj and Pankaj Biswas Recycling of H30 Aluminium Alloy Swarfs Through Gravity Die Casting Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Bhagyanathan, P. Karuppuswamy, K. Gowtham Kumar, M. Ravi and R. Raghu Effect on Mechanical and Metallurgical Properties of Cryogenically Treated Material SS316 . . . . . . . . . . . . . . . . . . . . Jitendra Upadhyay, Anuj Bansal and Jagtar Singh

67

83

97

Microstructure and Mechanical Properties of Lamellar Ti–6Al–4V ELI Alloy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Anil Kumar Singla, Jagtar Singh and Vishal S. Sharma

vii

viii

9

Contents

Influence of Process Parameters on Surface Roughness Hole Diameter Error and Burr Height in Drilling of 304L Stainless Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Vipin Pahuja, Suman Kant, Chandrashekhar S. Jawalkar and Rajeev Verma

10 Investigation of Impression Creep Deformation Behavior of Boron-Modified P91 Steel By High-End Characterization Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Akhil Khajuria, Raman Bedi and Rajneesh Kumar 11 Tribological and Machining Performance of Graphite-, CaF2- and MoS2-Coated Mechanical Micro-textured Self-lubricating Cutting Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Kishor Kumar Gajrani, Y. Bishal Singha, Mamilla Ravi Sankar and Uday S. Dixit 12 Chemical Assisted USM of Acrylic Heat Resistant Glass . . . . . . . . 167 Kanwal Jit Singh and Jatinder Kapoor 13 Study of Temperature Distribution During FSW of Aviation Grade AA6082 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Shubham Verma, Joy Prakash Misra and Meenu Gupta

About the Editors

Dr. Vishal S. Sharma is a Professor at the Department of Industrial and Production Engineering at Dr. B. R. Ambedkar National Institute of Technology, Jalandhar. He obtained his bachelor’s degree (Production Engineering) from Shivaji University, Kolhapur; masters in Mechanical (Production) Engineering from Punjab University Chandigarh; and his Ph.D. in Mechanical Engineering from Kurukshetra University. He also received a postdoctoral fellowship from ENSAM Cluny, France. He has published more than 70 scientific papers in international journals and conferences, and edited more than 15 books and proceedings. His current research interests include additive manufacturing and 3D printing, machining, condition monitoring, industrial IOT/Industry 4.0. Dr. Uday S. Dixit is a Professor at the Department of Mechanical Engineering at IIT Guwahati. He received his bachelor’s degree (Mechanical Engineering) from IIT Roorkee in 1987; and his masters and Ph.D. (Mechanical Engineering) from IIT Kanpur in 1993 and 1998, respectively. He has published over 200 scientific papers in international journals and conferences, and edited more than 12 books and proceedings. He has also undertaken 19 research and consultancy projects. In addition to developing course material on mechatronics for IGNOU, and on engineering mechanics for NPTEL, he has produced QIP course material in the area of “Finite Element Method in Engineering and its applications in manufacturing”, and “Introduction to Micro-manufacturing Technologies”. His research interests include plasticity, metal forming, laser-based manufacturing, finite element modeling, and optimization. He has authored/edited more than 15 books and proceedings. Dr. Noe Alba-Baena is a Professor at the Department of Industrial and Manufacturing Engineering, UACJ, Mexico. He received his bachelor’s degree in Industrial and Systems Engineering from the University of Juarez City, Mexico in 1999 and his masters (Industrial Engineering) and Ph.D. (Material Science & Engineering), both from University of Texas at El Paso in 2002 and 2006, respectively. He was awarded an M.Ed. (Educational Administration) degree by the same university in 2009. He has published more than 50 scientific papers in international ix

x

About the Editors

journals and conferences. He also holds two patents: “Methods for industrial-scale production of metal matrix nanocomposites” and “Apparatus and methods for industrial-scale production of metal matrix nanocomposites”. His current research interests include aluminum alloys, nanocomposites, ultrasonic treatment, product design, and manufacturing processes.

Chapter 1

A Variable Viscosity Technique for the Analysis of Static and Dynamic Performance Parameters of Three-Lobe Fluid Film Bearing Operating with TiO2 -Based Nanolubricant Ashutosh Kumar and Sashindra Kumar Kakoty Abstract Static and dynamic performance parameters of three-lobe fluid film bearing, operating with TiO2 -based non-Newtonian lubricant, are obtained. The Krieger–Dougherty model of effective is used to obtain the viscosity of nanolubricant for a fixed concentration of nanoparticle dispersed in base lubricant. Reynolds equation is modified to incorporate couple stress effect, and then, finite difference method (FDM) is used to solve it to obtain different performance parameter. For varying concentration of nanoparticle in base lubricant, direct and cross-coupled dynamic coefficients (stiffness and damping) are obtained. Results show that flow coefficient and load carrying capacity increases, whereas friction variable decreases, but it does not disturb the stability of three-lobe fluid film bearing working with TiO2 -based non-Newtonian lubricant. Dynamic coefficients and attitude angle do not vary with the concentration of solid nanoparticle for a fixed couple stress parameters.

Nomenclature C Radial clearance in meter Film thickness for a cantered shaft in meter Cm Cx x , Cx z , Damping coefficients in Ns/m C zx , C zz C¯ x x , C¯ x z , Damping coefficients in non-dimensional form C¯ x x  C x x (ωC/W ) C¯ zx , C¯ zz e Eccentricity in meter A. Kumar (B) · S. K. Kakoty Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India e-mail: [email protected] S. K. Kakoty e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_1

1

2

ε e1 , e2 , e3 h h¯ Kxx , Kxz, K zx , K zz K¯ x x , K¯ x z , K¯ zx , K¯ zz L Dd D¯ d Dw D¯ w Rd R¯ d Rw R¯ w m ω M¯ N D p p¯ R U μ¯ ψ φ S f¯ μn f μb f W W¯ p¯ 1 , p¯ 2 δ d t τ ωp ω¯ j Wx

A. Kumar and S. K. Kakoty

Eccentricity ratio ε  e/C Eccentricity for each lobe in meter Oil-film thickness in meter Film thickness non-dimensional form h¯  h/C Stiffness coefficients in N/m Stiffness coefficients in non-dimensional form K¯ x x  K x x (C/W ) Bearing length in m Depth of pressure dam in meter Depth of non-dimensional pressure dam D¯ d  D/C Width of pressure dam meter Width of non-dimensional pressure dam D¯ w  Dw /L Depth of relief track meter Depth of non-dimensional relief track R¯ d  Rd /C Width of relief track in meter Depth of non-dimensional relief track R¯ w  Rw /L Rotor mass per bearing in kg Journal angular velocity in rad/s Mass parameter M¯  mCω2 /W Journal speed in rps Journal diameter in meter Pressure ( p  W/L D) in N/m2 Film pressure non-dimensional form p¯  pC 2 /6μU R Radius of bearing in meter Sliding speed in m/s Effective viscosity Attitude angle in radian Volume fraction of solid additive Sommerfeld number S  μN / p(R/C)2 Friction variable in non-dimensional form f¯  f (R/C) Nanolubricant viscosity Base lubricant viscosity Load capacity in N Load capacity in non-dimensional form W¯  W C 2 /6μU R 2 L Perturbed pressure Ellipticity ratio δ  d/C Distance between lobe center and center of entire bearing geometry in meter Time (s) Time in non-dimensional form τ  ω p t Whirling velocity in rad/s Speed parameter Resultant load in vertical direction in N

1 A Variable Viscosity Technique for the Analysis of Static …

Wz θs θe θr Q¯

3

Resultant load in horizontal direction in N Groove starting angle Groove end angle Film cavitation angle Flow coefficient

1.1 Introduction Nowadays, tribologists face a challenge due to an increase in speed and load in practical application, and thus, it is a need of the hour to develop better solution to handle increased speed and load. Multilobe bearing was introduced to overcome the shortcomings of plain journal bearing such as high friction variable, low load carrying capacity, stability issues, and low stiffness. Performance of multilobe bearing was analyzed by many researchers (Soni et al. [1], Lund and Thomson [2], Singh and Gupta [3], Kumar et al. [4]) and found that these bearing to be more stable than the plain bearing, thus solving the main issue of high-speed machineries. Along with the geometric configuration of bearing, properties of lubricating oil were studied very extensively and found that there is a substantial improvement in lubricating properties if nano-solid particles are dispersed in base lubricants. In the same line, micro-continuum theory of couple stress model was studied by many researchers (Ariman and Sylvester [5, 6], Stokes [7]). On the basis of the same theory, researchers have focused their study for fluids dispersed with very fine small solid structured particles (Lin [8], Wang et al. [9, 10], Mokhiyamer et al. [11], Lin [12]) and found that stability and load carrying capacity increased significantly for finite fluid film bearing. In the current study, the effect of variation in viscosity of lubricant due to different volume fraction of solid nanoparticle and influence of this variation on static and dynamic performance parameters of three-lobe journal bearing working with TiO2 -based non-Newtonian lubricant is carried out. The Krieger–Dougherty model of variation in viscosity is used to include the variation in viscosity. Keeping the couple stress parameter constant, pressure profile for different concentration of solid nanoparticle is compared. Reynolds equation is modified to incorporate couple stress parameter. The modified equation is then solved by Gauss–Siedel method along with successive over relaxation in a finite grid.

1.2 Theory Centers of lobe 1 and lobe 2 of three-lobe journal bearing are O1 and O2 as shown in Fig. 1.1. A 10° oil supply hole is provided for continuous supply of lubricating oil which is 180° apart from each other. In the study, ellipticity (δ) ratio is considered e   as 0.5 which is defined as δ  Cp . e p is known as ellipticity which is the distance

4

A. Kumar and S. K. Kakoty X

Fig. 1.1 Three-lobe journal bearing

Lobe 2 Lobe 3

Cm O2

R

C-Cm

Z

O1

O3

R+C R Oil Supply

Lobe 1

Load

between bearing center and lobe center. Individually lobes are circular, but bearing as a whole is non-circular. In the current study, Krieger–Dougherty viscosity model is taken into consideration which suggests that effective viscosity of nano-fluid depends on the percentage of solid nanoparticle in the base lubricant. The Krieger–Dougherty viscosity model is expressed as [13]: μ¯ 

  μn f φ −[η]φm  1− μb f φm

(1.1)

The η is a material constant which is responsible for couple stress property of nonNewtonian lubricant.  Characteristic length (l) of solid additives in a nanolubricant is defined as l  μη . Effect of couple stress parameter on the characteristics of the bearing system is characterized with the help of parameter d  Cl which is a non-dimensional term. In the ongoing study, concentration of solid nanoparticle is varied (φ  0.001, 0.005, 0.01, and 0.02), whereas the value of the couple stress remains fixed at d  0.4. The performance characteristics of three-lobe fluid film bearing are affected very significantly by the higher concentration of solid nanoparticle in base fluid. Eccentricity ratios of each individual lobe are given as: ε1 



ε2 + δ 2 + 2εδ cos(φ)

 ε2 

ε2 + δ 2 − 2εδ cos

π 3

+φ

(1.2)

(1.3)

1 A Variable Viscosity Technique for the Analysis of Static …

5



π −φ ε3  ε2 + δ 2 − 2εδ cos 3

(1.4)

In the same line, attitude angle of each individual lobe can be written as:   ε sin φ −1 φ1  tan δ + ε cos φ  π  ε sin + φ 2π 3   − tan−1 φ2  3 δ − ε cos π3 + φ     ε sin π3 − φ 2π −1   − tan φ3  − 3 δ − ε cos π3 − φ For couple stress model, the Reynolds equation can be modified as [14]:



 ∂p ∂ ∂p ∂h ∂h ∂ f (h, d) + f (h, d)  6μU + 12μ ∂x ∂x ∂z ∂z ∂x ∂t

(1.5) (1.6) (1.7)

(1.8)

where, 

h f (h, d)  h − 12d h + 24d tanh 2d 3

2



3

(1.9)

Following substitutions can be used to write the non-dimensionalised form of Eq. (1.8): θ

μn f x ¯ h z pC 2 ; h  ; z¯  ; τ  ωt; μ¯  ; p¯  R C 6μU R μb f (L/2)

The final non-dimensional equation obtained is expressed as:

  2  ∂ ¯ ¯ ¯  ∂ p¯ D ∂ h¯ ∂ h¯ ∂ ¯ ¯ ¯  ∂ p¯ +  μ¯ + 2μ¯ f h, d f h, d ∂θ ∂θ L ∂ z¯ ∂ z¯ ∂θ ∂τ

(1.10)

where   ¯ d¯  h¯ 3 − 12d¯ 2 h¯ + 24d¯3 tanh f¯ h,

 ¯  h 2d¯

(1.11)

For dynamic-state condition, Reynolds equation in non-dimensional form is expressed in Eq. (1.10). Attitude angle ψ0 and eccentricity ratio ε0 are taken for steady state condition. If whirling of the journal takes place about its mean position with small amplitude and perturbing the system in first order and if higher-order term is neglected, then film thickness of lubricant and pressure can be expressed in non-dimensional form as [14].

6

A. Kumar and S. K. Kakoty

h¯  h¯ 0 + ε1 eiωτ cos θ + ε0 ψ1 eiωτ sin θ

(1.12)

p¯  p¯ 0 + ε1 eiωτ p¯ 1 + ε0 ψ1 eiωτ p¯ 2

(1.13)

If h¯ and p¯ are substituted (1.10) and coefficients of ε0 , ε1 eiωτ , and ε0 ψ1 eiωτ are equated, a set of equation are obtained by neglecting higher-order terms. These equations are expressed as Eqs. (1.14), (1.15), and (1.16). Static pressure distribution is expressed in Eq. (1.14), and dynamic pressure is expressed in (1.15) and (1.16) for each lobe separately.   2   ¯     ∂ ¯ d¯ ∂ p¯ 0 + D ¯ d¯ ∂ p¯ 0  μ¯ ∂ h 0 f h, f h, (1.14) ∂θ L ∂ z¯ ∂ z¯ ∂θ    2       ∂ ∂ ¯ 2 ∂ p¯ 0 ∂ ¯ ¯ ¯  ∂ p¯ 1 ¯ d¯ ∂ p¯ 1 + D +3 cos θ f¯ h, f h, d h0 ∂θ ∂θ L ∂ z¯ ∂ z¯ ∂θ ∂θ   2  D ∂ ¯ 2 ∂ p¯ 0 cos θ  −μ¯ sin θ + 2μiω ¯ cos θ (1.15) +3 h L ∂ z¯ 0 ∂ z¯    2       ∂ ∂ ¯ 2 ∂ p¯ 0 ∂ ¯ ¯ ¯  ∂ p¯ 2 ¯ d¯ ∂ p¯ 2 + D +3 sin θ f¯ h, f h, d h0 ∂θ ∂θ L ∂ z¯ ∂ z¯ ∂θ ∂θ  2   D ∂ ¯ 2 ∂ p¯ 0 +3 sin θ  μ¯ cos θ + 2μiω ¯ sin θ (1.16) h L ∂ z¯ 0 ∂ z¯ ∂ ∂θ



Equations (1.14), (1.15), and (1.16) are solved by FDM using central difference method to obtain static and dynamic pressures which are expressed in Eqs. (1.17), (1.18), and (1.19).         C1 p¯ 0i+1, j + p¯ 0i−1, j + C0 C1 p¯ 0i, j+1 + p¯ 0i, j−1 + C2 p¯ 0i+1, j − p¯ 0i−1, j + C3 p¯ 0i, j  2C1 [1 + C0 ] (1.17) 

p¯ 1i, j   p¯ 2i, j 

         C1 p¯ 1i+1, j + p¯ 1i−1, j + C0 C1 p¯ 1i, j+1 + p¯ 1i, j−1 + C2 p¯ 1i+1, j − p¯ 1i−1, j − C4 p¯ 0i+1, j − p¯ 0i−1, j +     C5 p¯ 0i+1, j − 2 p¯ 0i, j + 2 p¯ 0i−1, j + C0 C5 p¯ 0i, j+1 − 2 p¯ 0i, j + 2 p¯ 0i, j−1 + C6 2C1 [1 + C0 ]          C1 p¯ 2i+1, j + p¯ 2i−1, j + C0 C1 p¯ 2i, j+1 + p¯ 2i, j−1 + C2 p¯ 2i+1, j − p¯ 2i−1, j + C7 p¯ 0i+1, j − p¯ 0i−1, j +     C8 p¯ 0i+1, j − 2 p¯ 0i, j + 2 p¯ 0i−1, j + C0 C8 p¯ 0i, j+1 − 2 p¯ 0i, j + 2 p¯ 0i, j−1 − C9 2C1 [1 + C0 ]

(1.18) (1.19)

where 

2 

2

    ¯ d¯ ( θ ); C3  με ¯ d¯ ; C2  1 f¯ h, ; C1  f¯ h, ¯ sin θ( θ)2 ; 2   3 ¯ C4  θ h¯ 0 sin θ h¯ 0 + 2ε cos θ ; C5  3h¯ 20 cos θ; C6  (sin θ − 2iω cos θ)μ( θ )2 ; 2

3 2 ¯ C7  θ h¯ 0 h¯ 0 cos θ − 2ε sin2 θ ; C8  3h¯ 20 sin θ; C9  (cos θ + 2iω sin θ)μ( θ) 2

C0 

D L

θ ¯z

1 A Variable Viscosity Technique for the Analysis of Static …

7

For static and dynamic pressure, the following boundary condition is used. ∂ p¯ i  0 and p¯ i  0 at θ  θr ; ∂θ p¯ i (θ, z¯ )  0 when θs ≤ θ ≤ θe ;

(1.20)

where, p¯ i  p¯ 0 , p¯ 1 , and p¯ 2 . The pressure distribution equations which are in non-dimensional form are by finite difference method by using central difference method. Whole bearing is divided into two half, and each half is divided into 88 × 16 grids, where 88 grids are in circumferential direction and 16 grids are in axial direction. As the pressure is distributed symmetrically about bearing central line, only half part of the bearing is considered for analysis of bearing. For numerical integration, Gauss–Siedel method is used along with successive over-relaxation technique which satisfies the boundary conditions. ( pi, j )new  ( pi, j )old + (Err or )i, j × or f Equation (1.22) represents the convergence criterion:       p¯ i, j N −1 − p¯ i, j N      ≤ 10−6  p¯ i, j 

(1.21)

(1.22)

N

Equation (1.23) gives dynamic load component along vertical and horizontal directions due to dynamic pressure component p¯ 1 and p¯ 2 . W¯ z1 

θe 1 θs

W¯ x1 

0

θe 1 θs

0

p¯ 1 sin θ dθ d z¯ ; W¯ z2 

θe 1 p¯ 2 sin θ dθ d z¯ ; θs

p¯ 1 cos θ dθ d z¯ ; W¯ x2 

0

θe 1 p¯ 2 cos θ dθ d z¯ ; θs

(1.23)

0

In order to make the horizontal component zero, the attitude angle keeps changing for every eccentricity ratio which means the load is acting only in vertical direction. Stiffness and damping coefficient (cross-coupled and direct) in non-dimensional form are obtained by isolating imaginary and real part of vertical and horizontal load. Equation (1.24) represents stiffness and damping coefficients both direct and cross-coupled. K¯ x x  −Re(W¯ x1 ); K¯ x z  −Re(W¯ x2 ); K¯ zx  −Re(W¯ z1 ); K¯ zz  −Re(W¯ z2 ) ¯ zz  −Im(W¯ z2 ) (1.24) C¯ x x  −Im(W¯ x1 ); C¯ x z  −Im(W¯ x2 ); C¯ zx  −Im(W¯ z1 ); C

8

A. Kumar and S. K. Kakoty

Non-dimensional friction variable, Sommerfeld number, and flow coefficient are given as: 2π ∂ p¯0 3h¯ ∂ z¯ +

  R  f¯  f C

0

μ¯ h¯ 0

dθ (1.25)

6W¯

1 6π W¯   2π ¯ ¯ ¯  f h, d ∂ p¯ 0 1 D 2 S

q¯ z 

2

L 0

μ¯

∂ z¯

(1.26)

dθ

(1.27)

1.3 Results and Discussion 1.3.1 Validation Due to the absence of standard results for three-lobe bearing working with nonNewtonian lubricant with couple stress model, the present result for basic model is validated with Lund and Thomson [2] for three-lobe bearing working with Newtonian lubricant (Table 1.1). The current results are well comparable with published result for different models. Once the validation is done successfully, the basic code has been extended for threelobe journal bearing with couple stress model with nanolubricant. The results and discussion are explained in the following section.

1.3.2 Three-Lobe Fluid Film Bearing 1.3.2.1

Steady-State Performance Parameter

Figure 1.2 shows the three-dimensional pressure profile for the fixed parameters. Figure 1.3 shows the static pressure in non-dimensional form at the mid-plane of bearing along the circumferential node. The couple stress parameter is taken as d  0.4 and DL  1. Percentage of solid nanoparticle has been changed from 0 to 2%. From the figure, it can be observed that with an increase in percentage of nanoparticle in nanolubricant, pressure increases. The dominance of increase in pressure can be seen beyond 0.5% (volume fraction of 0.005) of nanoparticle in base lubricant. When percentage of solid structured nanoparticle in base lubricant increases, it affects the steady-state parameters of fluid film bearing. These variations are shown in Figs. 1.4, 1.5, 1.6, and 1.7. As the percentage of solid nanoparticles increases in base

1 A Variable Viscosity Technique for the Analysis of Static …

9

Table 1.1 Comparison of non-dimensional steady-state and dynamic performance parameters of three-lobe fluid film bearings for Newtonian lubricant Characteristics

φ

ε  0.103

ε  0.285

ε  0.441

Present

Lund and Thomson [2]

Present

Lund and Thomson [2]

Present

Lund and Thomson [2]

65.08

60.95

59.46

58.22

48.38

47.19

S

0.547

0.574

0.137

0.138

0.035

0.034

Q

0.142

0.139

0.177

0.173

0.232

0.232

Kxx

7.08

7.24

5.36

5.54

9.23

9.70

Kxz

8.08

8.55

4.11

4.22

4.56

4.65

K zx

−7.56

−7.90

−2.16

−2.12

0.05

0.11

K zz

4.26

4.24

2.03

1.92

1.48

1.42

Cx x

19.94

20.73

10.22

10.39

9.86

10.03

C x z  C zx

−0.51

−0.37

0.96

0.98

1.70

1.67

C zz

13.41

14.27

3.84

3.81

1.32

1.23

Fig. 1.2 Pressure profile of three-lobe bearing operating with non-Newtonian lubricant with d  0.4, eccentricity ratio  0.203, and volume fraction of nanoparticle  0.001

fluid, there is an enrichment in hydrodynamic pressure which results in increase in load carrying capacity as shown in Fig. 1.4. Load carrying capacity and Sommerfeld number are related to each other mathematically and these are inversely proportional to each other hence as the concentration of solid nanoparticle increases Sommerfeld number decreases as shown in Fig. 1.5. Figure 1.6 shows the variation in flow coefficient with concentration of solid nanoparticle in base fluid. With an increase in concentration of nanoparticle, flow coefficient increases. At the same time, it also increases with an increase in eccentricity ratio for a fixed percentage of solid nanoparticles in base fluid. Under normal

10 Fig. 1.3 Hydrodynamic pressure distributions at bearing mid-plane for different nanoparticle volume fractions at an eccentricity ratio of 0.203 and couple stress parameter of 0.2

Fig. 1.4 Variation in load carrying capacity with volume fraction of nanoparticle

Fig. 1.5 Variation in Sommerfeld number with volume fraction of nanoparticle

A. Kumar and S. K. Kakoty

1 A Variable Viscosity Technique for the Analysis of Static …

11

Fig. 1.6 Variation in flow coefficient with volume fraction of nanoparticle

Fig. 1.7 Variation in friction variable with volume fraction of nanoparticle

circumstances in journal bearing, heavy friction occurs during startup and slows down of shaft. During these situations, solid nanoparticle starts behaving as a rolling element between shaft and bearing which drastically reduces the friction. Hence with an increase in concentration of solid particles in base lubricant, the friction variable decreases as depicted in Fig. 1.7.

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1.3.2.2

A. Kumar and S. K. Kakoty

Dynamic Coefficients

With a change in concentration of nanoparticle, load changes in both horizontal and vertical direction and the ratio of horizontal component and vertical component affect the attitude angle. Here, load changes in a manner that attitude angle remains constant as depicted in Fig. 1.8. Effect of concentration of solid nanoparticle in base fluid on stiffness and damping coefficients both direct and cross coupled is depicted in Figs. 1.9, 1.10, 1.11, 1.12, 1.13, 1.14, 1.15 and 1.16. The dynamic coefficient shows the behavior which is totally different than that of steady-state parameters. As the eccentricity ratio increases, the dynamic coefficient also increases for a given concentration, but dynamic coefficients do not vary with concentration of solid nanoparticle in the base fluid.

Fig. 1.8 Variation in attitude angle with volume fraction of nanoparticle

Fig. 1.9 Variation in direct stiffness coefficient with volume fraction of nanoparticle

1 A Variable Viscosity Technique for the Analysis of Static …

13

Fig. 1.10 Variation in cross-coupled stiffness coefficient with volume fraction of nanoparticle

Fig. 1.11 Variation in cross-coupled stiffness coefficient with volume fraction of nanoparticle

The coefficients C6 and C9 are the function of concentration of solid particle in base lubricant, and these coefficients are not a function of P1 and P2 . Dynamic pressure is the only parameter which affects the stiffness and damping coefficients. This could be a reason for not changing the dynamic coefficients with concentration of solid particle in base fluid.

14 Fig. 1.12 Variation in direct stiffness coefficient with volume fraction of nanoparticle

Fig. 1.13 Variation in direct damping coefficient with volume fraction of nanoparticle

Fig. 1.14 Variation in cross-coupled damping coefficient with volume fraction of nanoparticle

A. Kumar and S. K. Kakoty

1 A Variable Viscosity Technique for the Analysis of Static …

15

Fig. 1.15 Variation in cross-coupled damping coefficient with volume fraction of nanoparticle

Fig. 1.16 Variation in direct damping coefficient with volume fraction of nanoparticle

1.4 Conclusions The influence of concentration of solid nanoparticles in base fluid on the bearing performance parameter is noticeable. Increase in concentration of solid nanoparticles in base lubricant gives enrichment in the load capacity, it can also be seen that there is a reduction in friction variable. If we observe the flow coefficient, it can be seen that with an increase in eccentricity ratio flow coefficient increase for a given concentration and also an increment can be observed with an increase in concentration of solid particle in base fluid. In all these cases, couple stress remains constant. Results also reveal that as the concentration of solid nanoparticle increases, the non-dimensional pressure increases, and for volume fraction more than 0.005, the increment becomes

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more pronounced as depicted in Fig. 1.3. The stiffness and damping coefficients of bearing remain unaltered for different concentration of solid nanoparticle. Hence by varying concentration of nanoparticle, static characteristics of three-lobe journal bearing can be bettered without disturbing the dynamic performance parameter vis-à-vis stability of the bearing. The lubricants that we use are not always Newtonian lubricant, and mostly, we use non-Newtonian lubricant which opens up the area of research of nano-fluids as lubricants and work is going on in different laboratories by different researchers. In the same line, the results obtained from the current study should be of enormous importance for the future.

References 1. Soni, S.C., Sinhasan, R., Singh, D.V.: Performance characteristics of noncircular bearings in laminar and turbulent flow regimes. ASLE Trans. 24(1), 29–41 (1981) 2. Lund, J.W., Thomson, K.K.: A calculation method and data for the dynamic coefficient of oillubricated journal bearings. In: Proceedings of the ASME Design and Engineering. Conference, pp. 1–28, New York, NY, USA (1978) 3. Singh, A., Gupta, B.K.: Static and dynamic properties of oil films in displaced centres elliptical bearings. Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 197(3), 159–165 (1983) 4. Kumar, A., Sinhasan, R., Singh, D.V.: Performance characteristics of two-lobe hydrodynamic journal bearings. J. Tribol. 102(4), 425–429 (1980) 5. Ariman, T.T., Sylvester, N.D.: Microcontinuum fluid mechanics-A review. Int. J. Eng. Sci. 11, 905–930 (1973) 6. Ariman, T.T., Sylvester, N.D.: Application of microcontinuum fluid mechanics. Int. J. Eng. Sci. 224, 194–201 (1974) 7. Stokes, V.K.: Couple stresses in fluids. Phys. Fluids 9, 1709–1715 (1966) 8. Lin, J.R.: Squeeze film characteristics of finite journal bearing: couple stress fluid model. Tribol. Int. 31, 201–207 (1998) 9. Wang, X.I., Zhu, K.Q., Wen, S.Z.: On the performance of dynamically loaded journal bearings lubricated with couple stress fluids. Tribol. Int. 35, 185–191 (2002) 10. Wang, X.I., Zhu, K.Q., Wen, S.Z.: Thermohydrodynamic analysis of journal bearings lubricated with couple stress fluids. Tribol. Int. 34, 335–343 (2001) 11. Mokhiamer, U.M., Crosby, W.A., El-Gamal, H.A.: A study of journal bearing lubricated by fluids with couple stress considering the elasticity of liner. Wear 224, 194–201 (1999) 12. Lin, J.R.: Effect of couple stresses on the lubrication of finite journal bearing. Wear 206, 171–178 (1997) 13. Kumar, A., Kakoty, S.K.: Effect of dam depth and relief track depth on steady-state and dynamic performance parameters of 3-lobe pressure dam bearing. Adv. Tribol. 14. Das, S., Guha, S.K., Chattopadhyay, A.K.: Linear stability analysis of hydrodynamic journal bearings under micropolar lubrication. Tribol. Int. 38, 500–507 (2005)

Chapter 2

Friction Stir Welding of Shipbuilding Grade DH36 Steel Avinish Tiwari, Pardeep Pankaj, Abhishek Bharadwaj, Piyush Singh, Pankaj Biswas and Sachin D. Kore

Abstract DH36 is commonly known hull structure steel widely used in shipbuilding industries. Fusion joining of this high-strength steel results in degradation of weld quality. This article focuses on friction stir welding of DH36 steel. Single-pass butt joints were performed on 4-mm thick plates of DH36 steel using tungsten carbide (WC-10 wt.% Co) alloy tool. Welding was carried out at rotational speed of 300 and 450 rpm keeping traverse speed of 132 mm/min as constant. Transient thermal history was recorded using K-type thermocouples. It was observed that the temperature on the advancing side was higher than that of the retreating side. Peak hardness values were observed in the stir zone. No heat-affected zone softening was observed in the welded joints. The welds were obtained with superior tensile strength and comparable ductility to the base material. During fractography analysis for the tensile sample, dimples were observed which indicated the ductile mode of fracture. Tensile properties and microhardness were correlated with the microstructure obtained in the stir zone. Tool wear was observed during welding which was characterized by visual inspection, FESEM-EDS analysis, and surface roughness of the tool pin. From the investigation, it was observed that sound-quality welds could be produced in DH36 steel with superior tensile strength and comparable ductility. A. Tiwari (B) · P. Pankaj · A. Bharadwaj · P. Singh · P. Biswas · S. D. Kore Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India e-mail: [email protected] P. Pankaj e-mail: [email protected] A. Bharadwaj e-mail: [email protected] P. Singh e-mail: [email protected] P. Biswas e-mail: [email protected] S. D. Kore e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_2

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Nomenclature FSW SZ TMAZ HAZ AS RS ASTM EDM FESEM EDS HV YS UTS F P ACF BN FS Ra

Friction stir welding Stir zone Thermomechanically affected zone Heat-affected zone Advancing side Retreating side American Society for Testing and Materials Electrodischarge machining Field emission scanning electron microscope Electron dispersion X-ray spectroscopy Vickers hardness Yield strength Ultimate tensile strength Ferrite structure Perlite structure Acicular ferrite Bainite structure Widmanstatten ferrite Surface roughness

2.1 Introduction FSW is a novel solid-state joining technique in which joints can be produced without actual melting of the parent metal. FSW has been proven a green technology due to absence of toxic gases, unlike fusion welding techniques. FSW needs nonconsumable tool which plunges into the workpiece and produces the joint by the combined rotational and traverse movement of the tool. The necessary heat required to produce the joint is provided by both friction and plastic deformation. FSW technology has been widely implemented in the joining of aluminum and other softer materials for aerospace, automobile, and shipbuilding industries [1]. Schematic diagram of FSW process is shown in Fig. 2.1. Steel is highly used structural material due to its excellent mechanical properties and good weldability. Steel has wide variety of alloys as compared to any other materials. There are so many fusion welding processes in which steel can be joined on industrial scale depending upon their thickness and applications. However, fusion joining of steel is associated with various defects like solidification cracking, liquefaction cracking, hydrogen cracking, alloying element segregation, porosity, high distortion, and formation of dendritic structure [1, 2]. Fusion joining of steel requires expensive preheat and postheat treatments to control the weld joint properties. Addi-

2 Friction Stir Welding of Shipbuilding Grade DH36 Steel

19

Fig. 2.1 Schematic diagram of friction stir welding process

tionally, fusion joining of advanced steel alloys becomes challenging as it requires new filler material. To overcome these issues, FSW technique has gained huge attention in joining of ferrous alloys these days. FSW technology offers more advantages over conventional welding of steels. It removes all welding defects associated with fusion welding techniques. In addition to that, lower heat inputs of FSW can reduce the heat-affected zone (HAZ) section which is one of the critical issues in fusion welding of steel. Additionally, the hydrogen cracking associated with the fusion welding of steel is completely absent in this process. The additional benefits of being low heat input process are low distortion which results in minimizing residual stress in the joining of large structural steels parts. Minimization of distortion and residual stress are most important criteria in welding of thick plates, used in the shipbuilding industries, marine industries, and other heavy manufacturing industries. FSW of aluminum and other softer materials were carried out extensively by previous researchers [3–6]. The literatures available on FSW of steel are very limited. The main reason for this is that the there are various fusion welding processes in which steel alloys can be joined. Another important reason is the severe wear of FSW tool during welding of steel [1]. Few of the relevant studies of FSW of steel is focussed in detail. Lakshminarayanan et al. [7] reported higher yield strength, ultimate strength, and lower notch impact toughness of the weld joints as compared to the base material in FSW of 1018 steel. However, in their study no effect of process parameters on the joint quality was investigated. Sebkan et al. [8] reported lower ductility and improved impact toughness of the weld joints in FSW of Grade A shipbuilding steel. It was observed that the higher impact toughness of the weld joints was due to grain refinement and presence of high-angled grain boundaries in the weld nugget zone. Reynolds et al. [9] observed the influence of peak temperature and cooling rate by varying the traverse speeds in FSW of DH36 steel. It was observed that the microstructural evolution and mechanical properties were strongly affected by the traverse speeds. The martensite and bainite structures in the weld nugget confirmed that the temperature during welding reached above the A3 line. However, no effect of rotational speed on the weld quality was investigated. Saeid et al. [10] investigated the effect of welding speeds on FSW of stainless steel. Successful welds were obtained

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up to traverse speeds of 200 mm/min. It was observed that hardness and tensile strength were increasing with increase in traverse speed due to larger reduction in the grain size. Karami et al. [2] investigated the effect of process parameters on FSWed mild steel plates. It was observed that the rotational speed and traverse speed play an important role in determining weld quality. Their result indicated higher tensile strength and lower elongation than that of the base metal. It was observed that improper selection of process parameters resulted in the lower heat input that yielded tunneling defect in the weld nugget. They found that the microstructure of the stir zone consisted of fine ferrite and pearlite. Ghosh et al. [11] investigated the effect of tool rotational speed and traverse speed on the weld quality in FSW of plain carbon steel. Tensile strength of weld joints was superior than that of the base material for miniature specimens and reduced for standard-size specimens. It was observed that the reason for low tensile strength was increased grain size in HAZ and unfilled cavities due to improper selection of process parameter. Cui et al. [12] investigated the effect of carbon composition on the weld quality during FSW of plain carbon steel having carbon content (0.12–0.50 wt.% C). The tensile strength of the weld joints was higher than that of the base material. Microstructure evolution was strongly affected by percentage of carbon content and welding parameters. Lowering heat input yielded the process without phase transformation and with considerable grain refinement. Miles et al. [13] carried out FSW on high-strength steels like dualphase (DP 590) steel and transformation-induced plasticity (TRIP 590) which are extensively used in automotive applications. Effect of rotational and traverse speed on weld quality was investigated. The weld joints exhibited tensile strength superior than that of the base material. Effect of process parameters mainly the rotational speed and traverse speed was investigated. They observed that high rotational speed and low traverse speed exhibited the high hardness in the weld zone as compared to that of the base material. At tool rotational speeds of 800 and 1200 rpm, the increase in hardness of the weld zone was 23 and 36% higher than that of the base metal. At traverse speed of 17 mm/s and rotational speed of 1200 rpm, the increase in hardness of the weld zone was around 46% than that of the base material. They [13] proposed that this was due to the formation of higher percentage of martensite at low traverse speed. Primary ferrite was the majorly found in the microstructure at high traverse speed. Miles et al. [14] attempted to evaluate the tool performance in two different tools, i.e., Q60 and Q70, made up of polycrystalline cubic boron nitride (PCBN) and tungsten rhenium (W-Re) by changing the percentage composition. Both the Q60 tool (60% PCBN and 40% W-Re) and Q70 tool (70% PCBN and 30% WRe) had successfully performed joining on high-strength dual-phase (DP90) steel. Wear was observed in form of chemical and abrasives rather than brittle fracture. It was found that the Q70 tool provided the best combination for minimum wear and high strength of the weld joint for the parameters investigated in the study [14]. It was also observed that the higher hardness in the weld joint produced by the Q60 tool which was due to high heat input caused by increased coefficient of friction. Tingey et al. [15] investigated effect of tool centerline deviation on FSW of DH36 steel. Three different types of fracture mechanisms were observed in the weld joint. Ductile fracture was observed up to 2.5 mm deviation from the centerline. Centerline

2 Friction Stir Welding of Shipbuilding Grade DH36 Steel

21

deviation upto 4 mm towards both the AS and RS side, sample fractured with high strength and ductile manner. Critical deviation was observed at 4 mm from centerline along both AS and RS, beyond that brittle fracture was observed. From the above literature, it was observed that FSW has potential to join various grades of steel. Due to its advantage of low heat input process, FSW becomes an attractive choice in joining of DH36 steel in shipbuilding industries. This article focuses on the experimental characterization of the weld joints and tool performance evaluation in FSW of DH36 steel. Tool wear was observed in welding of this steel and was reported in terms of surface roughness at the tool pin and shoulder surface. A suitable relationship was developed between the microstructural evolution and mechanical properties of the weld joints. Finally, FESEM-EDS analyses of the weld joint were carried out to investigate the tool wear.

2.2 Experimental Procedures Figure 2.2 shows the photograph of the welding machine and experimental setup used to carry out the experiments. The material selected for the present study is DH36 steel. The chemical composition and mechanical properties of the base material are presented in Table 2.1. The plates were machined to dimensions of 250 mm × 100 mm × 4 mm and cleaned with acetone to make it free from oxide layer and other surface impurities. Welding was done in the butt joint configuration along the rolling direction using a non-consumable tungsten carbide (WC-10 wt.% Co) tool. The schematic diagram and the photograph of the FSW tool are shown in Fig. 2.3. Fixtures were developed to clamp the workpiece material to avoid the separation of plates during the welding. FSW tool holder was designed and developed as shown in Fig. 2.4.

Fig. 2.2 Photograph of a FSW machine and b experimental setup used in the present study

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Fig. 2.3 FSW tool a schematic illustration and b photograph of tool

Fig. 2.4 FSW tool holder a schematic diagram and b photograph of the tool holder

2 Friction Stir Welding of Shipbuilding Grade DH36 Steel Table 2.1 Chemical composition and mechanical properties of DH36 steel

Table 2.2 Welding process parameters

Chemical composition Elements

Wt (%)

C

0.12–0.18 max

Mn S

23

Mechanical properties YS (MPa)

385

1.7 max

UTS (MPa)

514

0.025–0.035

% Elongation

P

0.025–0.035

Hardness (HV0.5 )

Si

0.45–0.6

Cu

0.25–0.60

Ti

0.05–0.06

V

0.11–0.15

Nb

0.02–0.06

Al

0.02

Fe

Rest

S. No.

Rotational speed (rpm)

Traverse speed (mm/min)

Weld 1

450

132

Weld 2

300

132

16 145

Initially, trials were made to select the range of process parameters in which successful joints were achieved. The details of experiments carried out in the present investigation are reported in Table 2.2. Thermal history was recorded using K-type thermocouples. The thermocouples were connected to the data acquisition system (Agilent-34970 A) to record the thermal history. Weld joints’ characterization was carried out using metallographic study and mechanical testings. For detailed metallographic study, welded samples were extracted including all welding zones, namely stir zone (SZ), thermomechanically affected zone (TMAZ), heat-affected zone (HAZ), and the base material. Samples were polished to different grades of emery papers, i.e., coarser to finer (320 grade to 2000), and mirror finished was achieved on cloth polishing by alumina solution. After that, etching was done by 2% Nital solution to reveal the microstructure of the weld joints. Microhardness measurement was carried out at load of 5N on Vickers microhardness testing machine. Transverse tensile specimens were cut on wire-EDM as per the ASTM E8 standards. Tensile properties of the joints were evaluated at a crosshead speed of 1 mm/min on universal tensile testing machine (Model: MEDIAN 250 and Make: BISS). The fractured tensile surfaces were analyzed under high magnification using field emission scanning electron microscope (FESEM Model: Sigma and Make: Zeiss) to study the fracture mechanism.

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2.3 Results and Discussion After performing welding, the weld characterization was described in subsequent sections. Initially, the weld joint was inspected by visual inspection, and then detailed microstructural and mechanical characterizations were carried out. Mechanical properties (like hardness and tensile strength) and microstructure were evaluated and compared with the base material.

2.3.1 Visual Inspection Figure 2.5 shows the photograph of red-hot FSW tool during welding and the image of welded joint. Figure 2.6 shows the photograph of the top surface of the weld 1 and weld 2, respectively. The visual inspection of the weld is carried out at both the top and bottom surfaces. It is observed that the good-quality weld joints are produced without any surface defects.

Fig. 2.5 Photograph of a red-hot FSW tool during welding and b successful weld joint produced Fig. 2.6 Photograph of the welded samples at rotational speed of a 300 rpm and b 450 rpm

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Fig. 2.7 Thermal history. a Layout of thermocouples’ location in the weld joint and b thermal profile obtained at 30 mm from the weld centerline on both the AS and RS

2.3.2 Weld Thermal History Figure 2.7a shows the schematic diagram of thermocouple location in weld 2. Two Ktype thermocouples are attached at the top surface of the workpiece to record thermal history during welding on both sides of the weld joint. The thermocouples’ location is exactly in the middle length of the weld plates along the transverse direction. Figure 2.7b presents a typical transient temperature profile during the welding at the rotational speed of 450 rpm and the traverse speed of 132 mm/min. It is observed that the peak temperature is different on both sides of the weld joint. The temperature recorded on the advancing side (AS) is higher than that of the retreating side (RS). The temperature on AS is approximately 18% higher than that of the RS. This asymmetry in the temperature profile can be explained by difference in relative velocities, material movement, and strain rates across the advancing and retreating sides of the weld joint [16].

2.3.3 Macrostructure Evaluation Figure 2.8 shows the photographs of the macrostructure of the weld joints. From Fig. 2.8a, it is observed that the shape of the weld nugget is inverted trapezoidal at 300 rpm. At high rpm, i.e., 450 rpm, basin-shaped weld zone is observed as shown in Fig. 2.8b. Width of the weld nugget is measured at three different layers, namely the top layer, middle layer, and bottom layer. The width of the weld zone is higher at the top which is decreasing gradually from top to bottom. At the top of the weld, material is influenced by the combined action of the tool shoulder and the tool pin whereas at bottom of

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Fig. 2.8 Photograph of the macrostructure analysis at a 300 rpm and b 450 rpm

the weld, material is influenced by tool pin only. Another important observation is that with increase in rotational speed, the size of the weld zone increased. The width of the weld zone at top middle and bottom layers of weld 2 is higher than that of the width of weld 1. This difference in the shape formation of the weld zone is mainly due to the difference in the heat input and material deformation rate.

2.3.4 Microstructure Characterization Figure 2.9 shows the microstructure of the typical weld produced at the rotational speed of 450 rpm and traverse speed of 132 mm/min. The boundary between the thermomechanically affected zone (TMAZ) and heat-affected zone (HAZ) is marked with red color. From the macroscopic image, it can be seen that the boundary at the advancing side is more clearly visible than that of the retreating side. This difference is attributed to material movement due to the combined action of rotational and traverse movement of the tool. Material movement is a very complex phenomenon in FSW process which alters the mechanical properties of the weld joint. Figure 2.9b demonstrates the formation of swirl zone in the weld joint. The swirl zone originates in the advancing side of nugget zone due to flow collision of shoulder-driven and pin-driven material flow. The upward material movement from bottom side by pin rotation and downward movement from top side by shoulder forging action yield the swirl zone. The swirl zone in the weld nugget is more prone to the defect formation (i.e., ‘wormholes’ or ‘tunnels’) due to insufficient plasticization. These defects can be eliminated by the proper selection of welding operating parameters. However, in the present investiga-

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27

Fig. 2.9 Optical images of weld 2 a macrostructure, b microstructure of the weld produced at the AS, and c formation of band structures in the advancing side

tion no volumetric defects are observed as confirmed by the microstructural analysis as shown in Fig. 2.9b. Figure 2.9c shows the banded structure due to extruding and stacking behaviors by rotating action of tool pin. Banded structure is mainly present in the AS and gradually disappeared on moving toward RS. The shoulder-driven flow and pin-driven flow are collectively responsible for the banded structure development in the weld nugget zone (WNZ). These banded structures consisted of black lamellae, and each band layer is separated by a distance. The separation between the two consecutive band layers depends on the welding parameters and tool geometry [17]. Figure 2.10 shows the optical images of the microstructure of the stir zones of weld 1, weld 2, and the base material. Microstructure, i.e., the grain size and morphology plays an important role in determining the mechanical properties of the weld joints. Figure 2.10a shows the microstructure of base material where the ferrite (F) and perlite (P) microstructure was observed with ferrite as the major phase. From Fig. 2.10b, c, it can be concluded that the structural morphology of the grains in the stir zone is quite different and can be distinguished easily. All grains are highly deformed and misoriented in the stir zone as compared to that of the base material. This is due to the intense stirring action of the FSW tool (mainly the tool pin) in the stir zone. It is confirmed that the stir zone is subjected to grain refinement as well as phase transformation. These transformations in the SZ can be annotated as phase transformation from austenite to bainitic (BN), acicular ferritic (ACF), and Widmanstatten ferrite (FS) microstructure. At both rotational speeds of 300 rpm and 450 rpm, the peak temperature attained in the weld nugget was sufficient to cause phase transformation. Toumpis et al. [18] also reported the evidence of acicular ferrite structures in the stir zone in FSW of DH36 steel. The microstructural grain refinement can be attributed continuous dynamic recrystallization due to low stacking fault energy of the steel. This may be attributed due high heat input and

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Fig. 2.10 Microstructure images a base material, b weld 1, and c weld 2

higher deformation rate (i.e., strain rate) in the stir zone. The temperature and high strain rates are sufficient to cause the phase transformation in the stir zones in both weld 1 and weld 2.

2.3.5 Microhardness Figure 2.11 shows the hardness distribution maps of weld 1 and weld 2. The Vickers microhardness measurements are carried out at the top layer, middle layer, and bottom layer along the transverse cross section of the weld joint. Hardness is studied transverse to the weld line and along the thickness direction. The hardness contour offers a better idea to evaluate the microhardness characteristics than the lines profiles. From the hardness maps, it is clear that the peak hardness values are observed in the stir zone in both weld 1 and weld 2. Hardness values are found overmatching in the thermomechanically affected zone (TMAZ) as well as in the heat-affected zone (HAZ) as compared to the base material. No HAZ softening is observed in both the weld joints. Hardness values are decreasing gradually on moving from SZ toward both the AS and RS of the weld joints. From the hardness contour, it can be easily concluded that the hardness is increasing gradually from base material (about 145 HV0.5 ) to the stir zone (243 HV0.5 ) as shown in Fig. 2.11a. Figure 2.11b shows the hardness contour of weld 2 from peak hardness 208 HV0.5 in SZ to 145 HV0.5 in BM. This significant variation of hardness values from weld nugget to heat-affected zone occurred due to the heterogeneity of evolved microstructure in various zones.

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Fig. 2.11 Hardness distribution maps of the FSW cross sections at a 300 rpm and b 450 rpm

The hardness values variations are more in the retreating side (RS) as compared to the advancing side (AS) of the weld joint. This asymmetric nature of hardness distribution can be due to difference in heat input, material flow, and strain rates across the advancing and retreating sides of the weld joint. Hardness values are also varying significantly along the thickness direction from top to bottom across the transverse weld cross section. From the hardness contours, it can be concluded that the high hardness values are achieved at the top layer (i.e., shoulder and pin influenced region) as compared to bottom layer (i.e., only pin influenced region). Peak hardness is reduced from 243 HV0.5 to 208 HV0.5 on increasing rotational speed from 300 to 450 rpm. This reduction in hardness can be explained due to grain coarsening in the stir zone at higher rotational speeds.

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2.3.6 Tensile Properties Figure 2.12 shows the tensile properties of the base material and welded samples. The yield and ultimate strength of the base material are 385 MPa and 514 MPa, respectively. Tensile properties of the joints such as the yield strength, ultimate strength, and percentage elongation are recorded as shown in Fig. 2.12. From Fig. 2.12, it is observed that the weld joints’ strength is superior than the strength of base material. It is also observed that the joint strength is decreasing with the increase of rotational speed. Tensile samples failed in the base material, i.e., outside the weld zone. Failure location of the weld joint is at the boundary of heataffected zone and the base material. Tensile sample shows the significant elongation before fracture, though the elongation of welded samples up to fracture is less as compared to the base material. The increase in tensile strength of the weld joint may be attributed to phase transformation, change in dislocation density, and grain refinement in the stir zone [10]. Figure 2.13a shows the fracture locations in the tensile specimens. It is observed that the location is outside the weld joint confirming the good-quality weld. Figure 2.13b shows the photograph of the fracture surface of the welded samples. Figure 2.13c, d shows the FESEM images of fracture surface of the welded samples. Dimples are observed in abundance with different sizes. These dimples are formed by the coalescence of microvoids which generally grow on tensile loading. The FESEM images of fracture surface confirm the ductile failure mode of the weld joints.

Fig. 2.12 Tensile properties of the welded joints and the base material

BaseMetal Weld produced at 300 rpm Weld produced at 450 rpm

600

Strength (MPa)

500 400 300 200 100 0 0

2

4

6

8

10

12

Percentage Elongation(%)

14

16

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Fig. 2.13 Photograph of a tensile samples showing fracture locations b fracture surface, c FESEM image of fracture surface of the weld 1, and d FESEM image of fracture surface of the weld 2

2.3.7 Tool Performance Evaluation Significant tool wear is observed in FSW of DH36 steel. The tool degradation mechanism is studied by visual inspection, surface roughness, and FESEM-EDS analysis. Figure 2.14a, b shows the FSW tool before and after welding. It can be concluded that the FSW tool is subjected to severe wear due to high stresses at the elevated temperature reached during the welding. Surface roughness is the most important characteristic feature of the surface integrity to evaluate the productivity of machine tools as well as machined components. Hence, good-quality surface finish is responsible for less wear and higher tool life. The surface finish is characterized by average roughness (Ra) values. Roughness (Ra) is evaluated at three different equidistance positions at the shoulder and pin surfaces. Figure 2.14c and 2.14d show the surface roughness profile at the tool shoulder and pin surfaces, respectively. The measured Ra value at the tool shoulder and tool pin are 0.293 µm and 0.343 µm, respectively. It is observed that the surface roughness values are higher at the tool pin than that of the tool shoulder [19]. It can be concluded that tool pin is more prone to wear than the tool shoulder. Batalha et al. [20] also reported tool degradation as adhesion of workpiece material on the tool pin and abrasion wear at the tool shoulder. Adhesion of the workpiece material on the tool pin may be due to the peak temperature generated at the tool pin. However, abrasion and scratches are mainly responsible for the wear mechanism for the tool shoulder due to huge frictional force at tool workpiece interface.

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Fig. 2.14 Images of FSW tool a before welding, b after weld, c surface roughness profile at the tool shoulder, and d surface roughness profile at the tool pin

Fig. 2.15 Weld microstructure a FESEM micrograph and b EDS spectrum of stir zone

Physical wear of the tool is confirmed by the FESEM-EDS analysis in the stir zone. Figure 2.15 shows FESEM-EDS analysis carried out at stir zone of the welded sample produced at the rotational speed of 450 rpm and the traverse speed of 132 mm/min. Figure 2.15 shows the presence of external particle in the stir zone of weld. The tungsten (W) elements are identified in the EDS analysis as shown in Fig. 2.15b. Lakshminarayanan et al. [7] reported the physical wear of the tool by indicating the presence of the tool debris in the stir zone in FSW of mild steel. Gan et al. [21] also reported the physical wear and mushrooming of the tool pin in FSW of steel. The

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main reason of tool wear is the development of high temperature due to frictional heat generation which leads to reduction in strength of tool material.

2.4 Conclusions FSW was carried out on 4-mm-thick shipbuilding grade DH36 steel using WC-10 wt.% Co alloy. Successful joints were produced at both the rotational speeds of 300 rpm and 450 rpm keeping traverse speed as constant. From the experimental investigations, following conclusions can be drawn • Tensile test results indicated that FSW-processed samples showed relatively higher yield and ultimate tensile strength. All tensile specimens exhibited significant elongation before fracture. The presence of dimples in the fractured surface confirmed the ductile fracture mode. • From the temperature–time plot, it was confirmed that the temperature distribution was asymmetric on both the AS and RS of the weld joint. Temperature on the AS was found approximately 18% higher than that of the RS. • Hardness of the SZ was increased by 67.5% and 43.5% of weld 1 and weld 2, respectively. No HAZ softening was observed in the weld zone. • Microstructure evolution confirmed grain refinement and the formation of bainitic structure, acicular ferrite structure, and Widmanstatten structure in the stir zone of both the weld 1 and weld 2. The microstructural results revealed that the peak temperature generated at 300 and 450 rpm was sufficiently enough to cause the phase transformations in the SZ. Grain refinement was observed due to dynamic recrystallization in the stir zone. • Tool wear was observed after performing the welding. Wear was characterized by visual inspection and surface roughness (Ra). Ra values obtained at the tool shoulder and tool pin were 0.293 µm and 0.343 µm, respectively. More systematic studies could be done by controlling the process parameters to investigate the process capability for industrial application. Acknowledgements The authors gratefully acknowledge the financial support provided by Naval Research Board (NRB), Government of India. The authors are also grateful to the Management and Department of Mechanical Engineering Department, Indian Institute of Technology Guwahati (IITG), Guwahati, India. The authors are also thankful to the Central Instruments Facility of IITG for providing the required research facilities.

References 1. Mishra, R.S., Ma, Z.Y.: Friction stir welding and processing. Mater. Sci. Eng. R Rep. 50(1–2), 1–78 (2005)

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2. Karami, S., Jafarian, H., Eivani, A.R., Kheirandish, S.: Engineering tensile properties by controlling welding parameters and microstructure in a mild steel processed by friction stir welding. Mater. Sci. Eng. A 670, 68–74 (2016) 3. Biswas, P., Mandal, N.R.: Experimental study on friction stir welding of marine grade aluminum alloy. J. Ship Prod. 25(1), 21–26 (2009) 4. Tikader, S., Biswas, P., Puri, A.B.: A study on tooling and its effect on heat generation and mechanical properties of welded joints in friction stir welding. J. Inst. Eng. (India) Ser. C 99(2), 139–150(2018) 5. Jain, R., Pal, S.K., Singh, S.B.: Finite element simulation of temperature and strain distribution during friction stir welding of AA2024 aluminum alloy. J. Inst. Eng. (India) Ser. C 98(1), 37–43(2017) 6. Mohanty, H., Mahapatra, M.M., Kumar, P., Biswas, P., Mandal, N.R.: Study on the effect of tool profiles on temperature distribution and material flow characteristics in friction stir welding. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 226(9), 1527–1535 (2012) 7. Lakshminarayanan, A.K., Balasubramanian, V., Salahuddin, M.: Microstructure, tensile and impact toughness properties of friction stir welded mild steel. J. Iron Steel Res. Int. 17(10), 68–74(2010) 8. Sekban, D.M., Aktarer, S.M., Xue, P., Ma, Z.Y., Purcek, G.: Impact toughness of friction stir processed low carbon steel used in shipbuilding. Mater. Sci. Eng. A 672, 40–48 (2016) 9. Reynolds, A.P., Tang, W., Posada, M., DeLoach, J.: Friction stir welding of DH36 steel. Sci. Technol. Weld. Join. 8(6), 455–460 (2003) 10. Saeid, T., Abdollah-Zadeh, A., Assadi, H., Ghaini, F.M.: Effect of friction stir welding speed on the microstructure and mechanical properties of a duplex stainless steel. Mater. Sci. Eng. A 496(1–2), 262–268 (2008) 11. Ghosh, M., Hussain, M., Gupta, R.K.: Effect of welding parameters on microstructure and mechanical properties of friction stir welded plain carbon steel. ISIJ Int. 52(3), 477–482 (2012) 12. Cui, L., Fujii, H., Tsuji, N., Nakata, K., Nogi, K., Ikeda, R., Matsushita, M.: Transformation in stir zone of friction stir welded carbon steels with different carbon contents. ISIJ Int. 47(2), 299–306 (2007) 13. Miles, M.P., Nelson, T.W., Steel, R., Olsen, E., Gallagher, M.: Effect of friction stir welding conditions on properties and microstructures of high strength automotive steel. Sci. Technol. Weld. Join. 14(3), 228–232 (2009) 14. Miles, M.P., Ridges, C.S., Hovanski, Y., Peterson, J., Santella, M.L., Steel, R.: Impact of tool wear on joint strength in friction stir spot welding of DP 980 steel. Sci. Technol. Weld. Join. 16(7), 642–647 (2011) 15. Tingey, C., Galloway, A., Toumpis, A., Cater, S.: Effect of tool centerline deviation on the mechanical properties of friction stir welded DH36 steel. Mater. Des. 1980–2015(65), 896–906 (2015) 16. Arora, A., Zhang, Z., De, A., DebRoy, T.: Strains and strain rates during friction stir welding. Scripta Mater. 61(9), 863–866 (2009) 17. Material-flow behavior during friction-stir welding of 6082–T6 aluminum alloy 18. Toumpis, A., Galloway, A., Cater, S., McPherson, N.: Development of a process envelope for friction stir welding of DH36 steel–a step change. Mater. Des. 1980–2015(62), 64–75 (2014) 19. Tiwari, A., Singh, P., Biswas, P., Kore, S.D.: Friction Stir Welding of Low-Carbon Steel. In: Sahoo P., Davim J. (eds) Advances in materials, mechanical and industrial engineering. INCOM (2018). Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham (2019) 20. Batalha, G.F., Farias, A., Magnabosco, R., Delijaicov, S., Adamiak, M., Dobrza´nski, L.A.: Evaluation of an AlCrN coated FSW tool. J. Achiev. Mater. Manuf. Eng. 55(2), 607–615 (2012) 21. Gan, W., Li, Z.T., Khurana, S.: Tool materials selection for friction stir welding of L80 steel. Sci. Technol. Weld. Join. 12(7), 610–613 (2007)

Chapter 3

Experimental Investigation on the Effect of Cryogenic CO2 Cooling in End Milling of Aluminium Alloy M. Pradeep Kumar, M. Jebaraj and G. Mujibar Rahman

Abstract In this experimental investigation, the end milling operations were carried out on an aluminium alloy at three machining conditions (dry, wet and cryogenic CO2 ). The machining input parameters of the end milling processes were the depth of cut, cutting speed and feed rate. The cutting temperature (T c ), axial force (F z ), normal force (F y ), feed force (F x ), the surface roughness (Ra), surface morphology, chip morphology and shape were analysed. The experimental results showed cryogenic CO2 reduced the cutting temperature (T c ) by about 8–9% and 38–39% in comparison with wet and dry conditions, respectively. The high axial force (F z ) values were recorded in CO2 coolant condition. The surface roughness and morphology, and chip shapes were compared. In a higher feed rate, the better surface roughness (Ra) values were obtained using CO2 coolant. In addition, the absence of black spots on the chip surface was obtained by cryogenic CO2 coolant condition.

Nomenclature CO2 LN2 Tc Fx Fy Fz Ra

Carbon dioxide Liquid nitrogen Cutting temperature Feed force Normal force Axial force Surface roughness

M. Pradeep Kumar (B) · M. Jebaraj · G. Mujibar Rahman Department of Mechanical Engineering, College of Engineering Guindy Campus, Anna University, Chennai 600025, India e-mail: [email protected] M. Jebaraj e-mail: [email protected] G. Mujibar Rahman e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_3

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Depth of Cut Computer Numerical Control Face Centered Cubic Scanning Electron Microscopy

3.1 Introduction Aluminium alloys are most commonly used lightweight metallic materials in automotive, aerospace and construction industries. The special tool geometries are needed to avoid major problems that occur during dry cutting of Al alloys. The main problems are sticking of the workpiece material, built-up edge or layer onto tool edges at high speeds and low speeds, respectively [1]. Aluminium alloys have higher ductility when compared to titanium, nickel and ferrous metals. Dry machining of Al alloys has a difficult chip control and poor surface finish because of its ductility [2]. At a high cutting speed, the rate of cutting tool wear is high as machining of silicon precipitates and hard tiny particles are present in the aluminium alloy. Higher cutting temperature alters surface layer microstructure and increases residual stresses of Al alloys during machining. Wet machining reduces the friction, decreases heat generation, slow down the tool wear, improves surface roughness, decreases oxidation and corrosion, and cleans the tool and the workpiece surface. It reduces the chip sticking to the cutting surface while high-speed machining [3]. The important functions of metal cutting coolant are to reduce friction, reducing heat generation, to avoid undesirable influences on the material structure and take out the chips from the cutting region when machining [4]. Thus, good lubrication system enables highefficiency processes in practice. Despite, metalworking fluid can vaporize at the high cutting temperature and prevent heat dissipation due to localized hot vapour barrier around the cutting zone. In addition, manufacturing industry workers are significantly affected by various typical cancers and respiratory diseases such as cervical cancer, colon cancer, lung cancer, bladder cancer, hypersensitivity pneumonitis, occupational asthma and bronchial hyper-responsiveness on continuous exposure to metalworking coolants/lubricants. Cryogenic coolant is used to overcome the drawbacks of the normal cutting coolant such as human health diseases [5], high cutting fluid maintenance and disposal cost [6, 7]. Cryogenic cooling reduces machining temperature by more heat dissipation, lower cutting tool diffusion and adhesion wear, enhances the material friction coefficient, preventing the alteration of tool material and workpiece properties, higher productivity, lower production cost and better dimensional accuracy [8]. Using LN2 in end milling operation reduced the Ra up to 43% and increased the machinability of Al 6061-T6 alloy as compared to dry end milling [9]. Turning of Al 6061-T6 alloy with LN2 coolant, the cutting temperature reduced by about 27–40%, chip thickness decreased up to 25%, more effective in the chip breaking over dry machining and reduced the workpiece stickiness [10]. Using LN2 as a cutting coolant for the milling of Al–Li alloy, less residual compressive stress improved the structural

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fatigue as compared to wet machining [11]. LN2 cooling reduced the cutting force by 29–33% and 42–49% in comparison with wet and dry machining conditions [12]. Cryogenic CO2 cooling reduced the formation of burr on the workpiece surface and provided better surface quality in face milling of 6082-T651 aluminium alloy [13]. Using cryogenic CO2 as cooling medium, the material removal rate increased by 72%, tool wear reduced up to 63% in end milling of stainless steel and improvement in surface finish over dry machining [14]. With cryogenic CO2 , the tool life increased up to 60%; white layer was not present on the workpiece surface when using the positive insert. It also provided superficial surface finish during turning of steel grade ASP23 [15]. Benefits of CO2 cooling were lower cutting forces, better chip breaking capability and accepted chip formation in cutting of AISI 316 steel [16]. In cryogenic machining, the cutting temperature was reduced for ductile materials (low carbon steel, aluminium alloy) due to a reduction in fracture strain [17], lower cutting energy and higher coefficient of heat transfer [18]. The more desirable and superior surface integrity of components under cryogenic machining significantly contributes to improving its functionality. Cryogenic cooling, particularly in the cutting of high-temperature aerospace metals, is highly suitable for not only improving the performance such as Ra, cutting forces, tool life, but also for significantly enhancing the machined product performance [19, 20]. End milling having high spindle speed, high feed and low DOC increased the volume of metal removal and shortened time need for production [21]. The recent researches on cryogenic machining have recommended more experiments on cryogenic milling should be carried out with different work piece-cutting tool combination [4, 22]. The key point of this article is to study the impact of cryogenic CO2 coolant in machining of Al 6082-T6 alloy and to compare T c , F x , F y , F z , Ra, surface morphology and chip morphology with dry and wet conditions.

3.2 Materials and Methods The CNC machine (ARIX VMC 100) was used for end milling of Al 6082-T6 alloy workpiece (dimensions 165 mm × 100 mm × 20 mm). The two indexable uncoated carbide inserts (ISO designation XDHT 090308 THM) were clamped by screws at one end of the tool holder (Ø16 mm (WIDIA M680-90)). The cryogenic CO2 parameters and milling parameters were selected from the recent articles. The liquefied CO2 was kept under a pressure and temperature of approximately 57 bar and −78.5 °C or −109.3 °F inside the tank, respectively. The gaseous CO2 flows through the Ø12 mm thermally insulated rubber hose at 3 g/sec flow rate and 5.88 bar flow pressure. The cryogenic CO2 coolant was supplied externally into the cutting region during machining [16]. The research work was performed under CO2 , wet and dry machining conditions with cutting speed of 150 m/min [23], three feed rates of 0.01, 0.015 and 0.02 mm/tooth [12], and DOC of 1.0 mm [12, 23, 24]. The transverse slots were machined on the workpiece surface having the cutting length of 40 mm in each pass.

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Fig. 3.1 Cryogenic CO2 experimental set-up

The experimental results such as chip-cutting tool interface temperature and metal cutting forces were measured in each pass by an infrared pyrometer, and three components piezo-electric Kistler type (9257B) dynamometer, respectively. The noncontact type infrared pyrometer with ±1 °C accuracy was used to measure the T c . The cutting forces, namely, F x , F y , F z were calculated by the piezo-electric dynamometer. This dynamometer was connected with a data acquisition system and a charge amplifier. The machined workpiece Ra value (sampling length  4 mm) was measured by surface roughness tester (Taylor–Hobson) with tip radius 5 µm, resolution −0.014 µm and range ±150 µm. The cut surface morphology was examined by the Hitachi-SEM apparatus. The chip morphology was investigated by using optical microscope. Figure 3.1 shows the cryogenic CO2 experimental set-up.

3.3 Results and Discussions Al 6082-T6 alloy workpiece with hardness 89 HB and the milling cutter with two uncoated carbide indexable inserts were used in this study. The cutting temperature (T c ), feed force (F x ), normal force (F y ), axial force (F z ), the surface roughness (Ra), morphology of surface and chip, and shape of the chip were measured.

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3.3.1 Effect of Cryogenic CO2 Coolant on Cutting Temperature Figure 3.2 illustrates the variation of cutting temperature (T c ) for different feed rate, constant speed and DOC in dry, wet and cryogenic CO2 machining conditions. The T c increased with the increase in feed rate as shown in Fig. 3.2. The T c values were 37.5 °C, 25.6 °C and 23.2 °C at a feed rate of 0.01 mm/tooth, cutting speed 150 m/min, DOC 1 mm for dry, wet and cryogenic CO2 conditions, respectively. The T c values were 38.5 °C, 25.9 °C and 23.8 °C at the feed rate of 0.015 mm/tooth, cutting speed 150 m/min, DOC 1 mm for dry, wet and CO2 conditions, respectively. Similarly, the T c values were 39.8 °C, 26.5 °C and 24.1 °C at the feed rate of 0.02 mm/tooth, cutting speed of 150 m/min, DOC 1 mm. In a dry machining operation, there were more adhesion and friction at the workpiece-tool interface that was subjected to a greater thermal load and high cutting temperature values. The conventional cutting fluid was spreading the entire cutting surface and transferring the heat from the tool, workpiece and chip. The cutting temperature value in wet machining was lower than the dry condition but more than cryogenic CO2 temperature. The lowest cutting temperature was achieved in cryogenic CO2 machining. The cryogenic CO2 reduced the friction between the workpiece and the cutting tool edge. Also, it transferred more heat from the machining zone by the convection heat transfer mechanism [4]. The cryogenic CO2 provided a high cooling effect on the cutting area. It absorbed more heat from the cutting surface thereby reducing the cutting temperature. In the CO2 condition end milling, the cutting temperature reduced by about 38–39% and 8–9% compared to dry and wet conditions, respectively.

Fig. 3.2 Effect of feed rate on T c at DOC 1 mm and cutting speed 150 m/min

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3.3.2 Effect of Cryogenic CO2 Coolant on Cutting Forces Figure 3.3a–c compares the variation of feed (F x ), normal (F y ) and axial (F z ) forces for various feed rates, constant speed and depth of cut under dry, wet and cryogenic CO2 machining conditions. Increasing feed rate increased the cutting forces as given in Fig. 3.3a–c. The lowest cutting forces were achieved in wet condition. In wet milling, the forces were less because of acceptable cooling effect in the cutting region. Thereby, it offered better sharpness to the tool edge. In dry machining condition, the forces increased due to high heat developed in the cutting region. This heat generation affected the tool sharpness; breakage of tool edge which requires the high force to remove the workpiece material. In cryogenic CO2 condition, the cutting forces were increased compared with the wet condition owing to an increase of cooling effect on the workpiece and tool insert. The workpiece hardness, tensile strength and Young’s modulus were increased at the cryogenic temperatures [4]. The spraying cryogenic CO2 jet flow through the workpiece-tool interface reduced heat generation and increased the hardness of the workpiece material. It could be reduced to the workpiece material ductility. Naturally, FCC crystal, aluminium alloy is a ductile material and its ductility is reduced by cold work or strain hardening. Thus high cutting forces are required to

Fig. 3.3 Effect of feed rate on a feed force, b normal force, c axial force at DOC 1 mm and speed 150 m/min

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remove the material from aluminium alloy when the cryogenic CO2 condition is used for machining. In end milling, wet condition reduced the feed force in the range of 33–52% and 30–35% compared to the dry and CO2 conditions, respectively. Simultaneously, wet condition reduced the normal force in the range of 29–46% and 11–37% compared to the dry and CO2 conditions, respectively. Similarly, wet condition reduced the axial force in the range of 0–5% and 6–30% in comparison with the dry and CO2 conditions, respectively.

3.3.3 Effect of Cryogenic CO2 Coolant on Surface Roughness Figure 3.4 indicates the variation of Ra values at a speed 150 m/min, DOC 1 mm and various feed rates. It was noted that the Ra value was high in the dry condition compared with the wet and CO2 condition. In cryogenic CO2 condition, Ra values were low at feed rates 0.015, 0.020 mm/tooth compared with the dry and wet conditions but in the feed rate 0.01 mm/tooth condition the Ra value was somewhat high compared with the wet condition. The cryogenic CO2 condition reduced the Ra value in the range of 27–61% compared with the dry condition. Similarly, CO2 condition reduced the Ra value at feed rates 0.015 and 0.02 mm/tooth in the range of 6–22%. At feed rate 0.01 mm/tooth, the Ra value was increased by 20% under CO2 condition compared with the wet condition. It was concluded that the Ra values were decreased by the cryogenic CO2 condition at feed rates 0.015 and 0.02 mm/tooth. The Ra value was highly depended on the machining parameters for different workpiece-tool material. The lowest Ra values were obtained at a feed rate 0.02 mm/tooth in CO2 condition. Nevertheless, the highest value of Ra attained at the feed rate 0.02 mm/tooth in dry

Fig. 3.4 Effect of feed rate on Ra at DOC 1 mm and cutting speed 150 m/min

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condition. The lowest Ra values were obtained by an increase in cutting speed due to delayed plucking and smearing mechanisms by a diffusion process in the cryogenic milling operation [9, 25]. Similarly, the Ra values were obtained in descending order for feed rate of 0.01, 0.015 and 0.02 mm/tooth with the CO2 condition.

3.3.4 Effect of Cryogenic CO2 Coolant on Surface Morphology The SEM images of 50 µm level in Fig. 3.5a–c display the effect on the machined surface by using dry, wet and CO2 coolants at DOC 1 mm, speed 150 m/min and feed 0.015 mm/tooth. Figure 3.5b shows that the surface created in the wet condition was better than the dry and CO2 environment. The wet coolant’s transportation function diminished the chip adhesion and produced the combination of low depth, parallel, lengthy wide and thin grooves. It was seen evenly distributed grooves in Fig. 3.5b which was indicated to feed bands by the cutting tool inserts geometry. Both rubbing and cutting stroke produced the surface in the slot milling operation. Figure 3.5a, c depicts the embedment of tiny chips; uneven grooves and microwear were formed in the machined surface under CO2 condition. The milling cutter was retracted by leaving the chip, such that chip dragging on the surface of the machined portion. The lower Ra values were obtained by CO2 coolant at the feed 0.015 and 0.02 mm/tooth and speed 150 m/min. There was no significant reduction in Ra value at feed rate of 0.015 mm/tooth by using CO2 coolant compared with wet condition (refer Fig. 3.4). In cryogenic CO2 condition, the chip is adhered on the component’s machined surface owing to strong bonding/adhesion. In addition, the chips couldn’t exit from the cutting area in slot milling operation due to dragging of chips between the tool and workpiece [26]. SEM images reflected that the wet condition produced absence of deep grooves and microwear on the surface compared to the other two conditions.

3.3.5 Effect of Cryogenic CO2 Coolant on Chip Morphology The chip forms influence the economical aspect and precise machining of any metal cutting industry. The machining industries have major problems such as disposal of chips and cutting fluids. Normally, milling is an intermittent metal cutting operation and it cannot produce long and unbroken chips [9]. Table 3.1 displays the chip shape at a speed 150 m/min, DOC 1 mm and three different feed rates. The productivity of machining industries is prominently influenced by the chip formation. Formation of chips besides its breaking aspect suffered the surface texture, workpiece precision and tool lifespan. Therefore, the creations of the adequate form of chips, safe chip control are crucial in the machining process. Table 3.1 clearly depicts three types

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Fig. 3.5 SEM images of a dry condition, b wet condition, c cryogenic CO2 condition

of the chip formed in end milling of aluminium alloy in dry and wet conditions but in cryogenic CO2 condition, there are only two types of chip formation. The chip formation types were elongated end edges chip, shortened end edges chip and welded thin chip. Only, the elongated and shortened end edges chip types were formed in cryogenic CO2 condition. The presence of welded thin chips indicates that there was an occurrence of the chip welding tendency in both dry and wet conditions. The curved shape chips were formed in both dry and wet conditions compared to the cryogenic CO2 condition. Major chip type, i.e. elongated end edges chip was shorter in wet condition. Figure 3.6a–c shows optical microscope images of chip morphology at speed 150 m/min and feed rate of 0.02 mm/tooth. Figure 3.6a indicates black colour chip formed in the dry machining process. It had disjointed serrated edges and shearing surface due to high shear stress, thermal shocks and increased friction. Figure 3.6b exposes the number of black spots on the chip surface, segmentation and very sharp serrated edge in wet machining owing to high heat generation, inadequate heat transfer and lubrication. In comparison with wet and dry environments, the chip in CO2 condition had discontinuous big size saw-toothed chip edges and very few dark spots.

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Table 3.1 Chip shape at a speed 150 m/min, DOC 1 mm and three different feed rates Cutting Feed speed (mm/tooth) (m/min) 150

Dry

Wet

Cryogenic CO2

0.01

0.015

0.02

They are identified in Fig. 3.6c. The cryogenic CO2 coolant penetration was found to be deeper than the conventional coolant into the workpiece and tool interface. It was observed that the chip-tool and workpiece-tool interface had better cooling and lubrication effects. From Fig. 3.6a–c, segmented chips were formed in all conditions; it was found that there was better chip formation under CO2 condition. In dry and wet environments, chip side edge serrations were more compared with the CO2 condition and it was clearly visible from chip images. In dry condition, chip surface had a zigzag pattern owing to the high thermal load; the edges of the chip had more burr particles and uneven chip shapes. In wet condition, the formation of the chip was in curved shape. In contrast, the cryogenic condition had straight chip formation and uniform chip shapes.

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Fig. 3.6 Optical microscope images of chip morphology at speed 150 m/min and feed rate of 0.02 mm/tooth a dry condition, b wet condition, c cryogenic CO2 condition

3.4 Conclusions Experimental study of end milling process was made on Al6082-T6 alloy material with uncoated carbide indexable inserts. The major conclusions are as follows: CO2 condition reduced the cutting temperature in the range of 38–39% and 8–9% in comparison with dry and wet conditions, respectively. Wet condition reduced the feed force in the range of 33–52% and 30–35% compared with dry and CO2 conditions, respectively. Similarly, wet condition reduced the normal force by about 11–37% and 29–46% compared to CO2 and dry conditions, respectively. Likewise, wet condition reduced the axial force in the range of 0–5% and 6–30% compared to dry and CO2 conditions, respectively. The cryogenic CO2 condition reduced the Ra values at a feed rate of 0.015 and 0.02 mm/tooth in the range of 6–22% compared to wet condition. The CO2 condition produced straight chip formation, and uniform chip shapes. Observation from the SEM images that the wet condition produced absence of deep grooves and microwear on the surface in comparison with dry and CO2 conditions. In future, cryogenic coolant can be supplied internally, i.e. through the milling cutter during the end milling of Al 6082-T6 alloy and after that, the results such as T c , cutting forces, chip formation and surface integrity can be examined.

References 1. Songmene, V., Khettabi, R., Zaghbani, I., Kouam, J., Djebara, A.: Machining and machinability of aluminum alloys. In: Kvackaj, T. (ed.) Aluminium Alloys, Theory and Applications. InTech, ISBN: 978-953-307-244-9 (2011)

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2. Mia, M., Singh, G., Gupta, M.K., Sharma, V.S.: Influence of ranque-hilsch vortex tube and nitrogen gas assisted MQL in precision turning of Al 6061-T6. Precis. Eng. (Am. Soc. Precis. Eng.) 53, 289–299 (2018) 3. Mario, C.S., Alisson, R.M., Wisley, F.S., Marcos, A.S., Emmanuel, O.E.: Machining of aluminum alloys: a review. Int. J. Adv. Manuf. Technol. (2016) 4. Shokrani, A., Dhokia, V., Munoz, E.P., Newman, S.T.: State of the art cryogenic machining and processing. Int. J. Comput. Integr. Manuf. 26(7) (2013) 5. Mia, M., Gupta, M.K., Singh, G., Królczyk, G., Pimenov, D.Y.: An approach to cleaner production for machining hardened steel using different cooling-lubrication conditions. J. Clean. Prod. 187, 1069–1081 (2018) 6. Kale, A., Khanna, N.: A review on cryogenic machining super alloys used in aerospace industry. Procedia Manuf. 7, 191–197 (2017) 7. Sivaiah, P., Chakradhar, D.: Influence of cryogenic coolant on turning performance characteristics: a comparison with wet machining. Mater. Manuf. Process. 32(13), 1475–1485 (2017) 8. Shokrani, A., Dhokia, V., Newman, S.T.: A techno-health study of the use of cutting fluids and future alternatives. Flex. Autom. Intell. Manuf. (2014) 9. Dhokia, V., Shokrani, A., Paulino, D.C., Newman, S.T.: Effects of cryogenic cooling on the surface quality and tool wear in end-milling 6061-T6 aluminium. In: 22nd International Conference on Flexible Automation and Intelligence Manufacturing (2012) 10. Dhananchezian, M., Kumar, M.P., Rajadurai, A.: Experimental investigation of cryogenic cooling by liquid nitrogen in the orthogonal machining process. Int. J. Recent Trend Eng. 1(5), 55–59 (2009) 11. Xiaoming, Z., Haikuo, M., Xinda, H., Zhongtao, F., Dahu, Z., Han, D.: Cryogenic milling of aluminium-lithium alloys: thermo-mechanical modelling towards fine-tuning of part surface residual stress. Procedia CIRP 31, 160–165 (2015) 12. Ravi, S., Kumar, M.P.: Experimental investigation of cryogenic cooling in milling of AISI D3 tool steel. Mater. Manuf. Process. 27(10), 1017–1021 (2012) 13. Biermann, D., Helimann, M.: Improvement of work piece quality in face milling of aluminum alloys. J. Mater. Process. Technol. 210(14), 1968–1975 (2010) 14. Susanne, C., Fabian, H., Thomas, S.: Next generation high performance cutting by use of carbon dioxide as cryogenics. Procedia CIRP 14, 401–405 (2014) 15. Pereira, O., Rodriguez, A., Valdivielso, A.F., Barreiro, J., Fernandez, A.I., Lopez, L.N.: Cryogenic hard turning of ASP23 steel using carbon dioxide. Procedia Eng. 132, 486–491 (2015) 16. Jerold, B.D., Kumar, M.P.: Machining of AISI 316 stainless steel under carbon-di-oxide cooling. Mater. Manuf. Process. 27(10), 1059–1065 (2012) 17. Astakhov, V.P.: Metal cutting theory foundations of near-dry (MQL) machining. Int. J. Mach. Mach. Mater. 7(1–2), 1–16 (2009) 18. Woodcraft, A.L.: An Introduction to Cryogenics. SUPA Institute of Astronomy, Edinburgh University, Blackford Hill, United Kingdom (2007) 19. Yusuf, K., Tao, L., Jawahir, I.S.: Cryogenic machining-induced surface integrity: a review and comparison with dry, MQL, and flood-cooled machining. Mach. Sci. Technol. Int. J. 18, 149–198 (2014) 20. Jawahir, I.S., Attia, H., Biermann, D., Duflou, J., Klocke, F., Meyer, D., Newman, S.T., Pusavec, F. Putz, M., Rech, J., Schulze, V., Umbrello, D.: Cryogenic manufacturing processes. In: CIRP Annals Manuf. Technol. 65, 713–736 (2016) 21. Destmobes, Y.: Very high speed machining of ferrous and solid composite materials: test campaign results, high speed machining. In: The Winter Annual Meeting of ASME, vol. 12, pp. 263–289, New Orleans, LA, USA, PED (1984) 22. Yildiz, Y., Nalbant, M.: A review of cryogenic cooling in machining processes. Int. J. Mach. Tools Manuf 48, 947–964 (2008) 23. Singh, G., Gupta, M.K., Mia, M., Sharma, V.S.: Modeling and optimization of tool wear in MQL assisted milling of Inconel 718 superalloy using evolutionary techniques. Int. J. Adv. Manuf. Technol. 97(1–4), 481–494 (2018)

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24. Mia, M., Rifat, A., T Dip, F., Gupta, M.K., Hossain, M.J., Goswami, A.: Multi-objective optimization of chip-tool interaction parameters using Grey-Taguchi method in MQL-assisted turning. Meas. J. Int. Meas. Confed. 129, 156–166 (2018) 25. Truesdale, S.L., Shin, Y.C.: Microstructural analysis and machinability improvement of Udimet 720 via cryogenic milling. Mach. Sci. Technol. 13(1), 1–19 (2009) 26. Ahmed, L.S., Kumar, M.P.: Cryogenic drilling of Ti–6Al–4 V alloy under liquid nitrogen cooling. Mater. Manuf. Process. 31(7), 951–959 (2016)

Chapter 4

Transient Thermal Analysis of CO2 Laser Welding of AISI 304 Stainless Steel Thin Plates Pardeep Pankaj, Avinish Tiwari and Pankaj Biswas

Abstract In present study, experimental and numerical analysis on CO2 laser welding of AISI 304 stainless steel sheet’s thickness of 1 mm was performed. Prediction of transient thermal history is essential while designing the welded joints. A 3D finite element (FE) model was developed using ANSYS 14.5 finite element package to determine the effect of welding process parameters, i.e., laser power and welding speed on thermal history of laser-welded joints. The influence of weld bead geometry obtained from experiment was considered in this 3D finite element (FE) model to simulate the moving volumetric heat source. The element birth and death technique was used in FE thermal analysis to simulate the progression of the laser weld zone. It was observed that the cooling rate was significantly affected by the varying laser power and welding speed. It was also observed that increasing laser power and decreasing welding speed lead to increase in size of fusion zone and heat-affected zone. The transient thermal analysis results obtained from FE model and experimental results were validated, fairly well, with maximum percentage error of 6.47% for the peak temperature.

Nomenclature FZ HAZ FEM

Fusion zone Heat-affected zone Finite element method

P. Pankaj (B) · A. Tiwari · P. Biswas Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India e-mail: [email protected] A. Tiwari e-mail: [email protected] P. Biswas e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_4

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TRIP Transformation-induced plasticity HLAW Hybrid laser-arc welding

4.1 Introduction Many products made by construction and manufacturing industries need some type of joining processes. Welding is a process that joins the metals or thermoplastic by mean of coalescence. Many conventional welding methods, i.e., arc welding, metal, inert gas welding (MIG), submerged arc, welding (SAW) and tungsten, inert gas welding (TIG), exhibit the large heat-affected zone (HAZ), low welding speed, higher residual stress and deformation in comparison to the laser welding process. Laser welding process can be used to join the materials like plastic, steel, aluminum alloys, and high temperature alloy having macro- or micro-level thickness. Many advantages, of laser welding process, i.e., higher speed and non-contact welding, make the interest in the automotive industry to produce the stich or seam welds for joining the auto body panels to subassemblies. CO2 laser has many advantages as compared to old-generation lasers because it exhibits excellent beam quality, better absorption, and higher efficiency. The carbon dioxide laser (CO2 laser) was invented by Kumar Patel of Bell Laboratories in 1964. The CO2 laser is one of the earliest gas lasers nowadays which is most useful in industries for cutting, welding, etc., due to its high density, power, efficiency, and high penetration. A very few researchers were studied on transient thermal analysis of CO2 laser welding process. The keyhole theory-based thermo-mechanical FE model was developed to determine the residual stress, residual strain, and distortion during CO2 laser lap joint welding of aluminum components with focused radius of 2 mm and welding velocity of 50 mm/s. Weld zone exhibited the maximum magnitude of longitudinal residual stress and decreased rapidly to zero value at a very short distance away from the weld line [1]. The numerical model based on program Fluent CFD software was developed to investigate the interaction of the welding pool and keyhole during laser welding process. It was observed that the sulfur content, surface tension, and the molten pool surface temperature had a significant effect on the depth of fusion zone in the laser welding process [2]. The photodiode measurements and spectroscopic measurements characterized the plasma absorption of a laser beam inside the keyhole in 20-kW CO2 laser welding process. The wider bead shape was found in the top region of weld bead due to plasma absorption in this portion [3]. A three-dimensional finite element model was developed to predict the distortion of 3-kW CO2 laser butt-welded specimens. They experimentally measured distortion of welded specimens was verified with the FE approach [4]. A nonlinear transient 3D heat transfer FE model was suggested for the CO2 laser welding of Al-6061-T6 alloy. It was investigated that the transient temperature distribution was influenced by thermal conductivity. It was also observed that the change in thermal conductivity leads to change in tensile residual stresses at the weld zone to compression residual stress at the edge [5]. The study was performed on microstructural, compositional,

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and residual stress estimation in CO2 laser welding of super-austenitic AISI 904L stainless steel plates. The power density and transverse speed were considered as a welding parameters and heat input, as well as shielding gas was properly selected to produce sound weld joints [6]. The microstructure, mechanical properties, defects, and formability of bead on plate of CO2 laser-welded TRIP steel sheets were investigated [7]. The computational analysis was performed using mathematical and finite element model to predict the temperature field and velocity field in laser-arc hybrid welding molten pool. These mathematical and numerical models can be used for analyzing the welding process parameters, i.e., distance between arc and laser beam and welding speed [8]. The FLUENT software-based numerical three-dimensional model was developed to predict the thermal history in laser welding of 304 stainless steel plates. A volumetric heat source with Gaussian distribution was assumed. It was observed that recoil pressure had a significant effect in keyhole formation and the high temperature gradient was obtained at front vicinity of the keyhole [9]. CO2 laser welding was performed to join the 316 stainless steel and low carbon steel. The welding parameters, i.e., laser power, welding speed, and focal length, were optimized. It was investigated that decreasing welding speed, laser power, and focal length resulted in higher tensile strength. The impact strength was increased with increase in laser power and decrease in welding speed [10]. A 3D coupled thermal–mechanical FE model was established to predict the temperature distribution, residual stresses, and distortions in hybrid laser-arc welding (HLAW) of NV E690 welded sheets. Combined uniform conical and Gaussian cylindrical moving heat source was used to perform the transient thermal FE analysis during HLAW. It was observed that increasing heat input leads to increase in peak temperature, residual stresses, and distortions in the welded joints [11]. A three-dimensional FE model was developed to investigate the characteristics of keyhole profile and the influence of keyhole development on the molten pool during high-power deep-penetration 10-kW continuous wave fiber laser welding of SUS316L stainless steel plate. The swelling and column formation were observed near the keyhole due to the influence of keyhole profile oscillation [12]. The temperature and stress distribution were predicted using finite element method in 2-kW CO2 pulse mode laser welding on mild steel sheets. The cooling rate in the molten zone was observed faster than in base metal due to absorption and dissipation of the laser energy in fusion zone [13]. The study was performed on the hot cracking during 3-kW Nd: YAG laser welding of transformation-induced plasticity (TRIP) steel using experimental and numerical methods. A 3D finite element (FE) thermal–mechanical model was developed to determine the temperature and strain distribution in the welded specimen. The critical strain range of 3.2–3.6% for the onset of hot cracking in the TRIP steel was observed [14]. The laser welding of maximum power 6 kW was performed on high strength steel sheets to predict the influence of the oscillation frequency and focal diameter on molten pool size and temperature distribution. It was observed that the influence of the focal diameter strongly depends on the oscillation frequency and welding velocity [15]. The input parameters were optimized for 4-kW CO2 laser butt welding of dissimilar metals, i.e., austenitic stainless steel (AISI 316) and low carbon steel (AISI 1018) plates.

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It was reported that the welding speed strongly influenced the dissimilar welding process [16]. The prediction of the influence of process parameters on temperature distribution, residual stresses, and residual deformation is most important for the designing of key components, i.e., the welded joints in nuclear power plants, design and structural integrity assessments. Experimental prediction of temperature distribution in welding process is very time consuming and costly. Therefore, finite element method is usually preferred to monitor and predict the welding process. In the present study, 3D-coupled transient thermo-mechanical FE model was successfully designed for selecting the CO2 laser weld bead geometry using a comparison of the FE simulation and experimental results with maximum error of 6.47% for the peak temperature. The influence of welding process parameters such as laser power (kW) and welding speed (mm/min) on transient temperature distribution, peak temperature distribution, fusion zone, and heat-affected zone size was determined. The present FE model methodology can be applied to perform the thermal analysis by considering any shape and size of the weld bead for better accuracy.

4.2 Experimental Details In the present study, experiments were carried out on continuous wave CO2 laser machine (LVD, model: Orion 3015) with maximum power of 2.5 kW. Specimens were made up of AISI 304 stainless steel with dimensions of 100 mm × 100 mm × 1 mm. Several numbers of experiments were performed by varying the operating parameters (laser powers and welding speeds) for determining the suitable range of parameters. The welding parameters such as laser powers (1.3, 1.5, and 1.7 kW) and welding speeds (300, 400, and 500 mm/min) were selected. To prevent the misalignment of specimens, tacking method was performed by using tungsten inert gas welding (TIG) process. The samples were clamped over the laser machine bed by using job holding fixture as shown in Fig. 4.1a. Transient temperature distribution over the surface of specimen was recorded using K-type thermocouples which were attached to data accusation system (DAQ) as shown in Fig. 4.1b. When the welding process was finished, the welded specimens were allowed to cool down near about room temperature.

4.3 Finite Element Modeling Finite element method (FEM) was used to examine the transient temperature distribution in AISI 304 thin welded sheets using CO2 laser. A 3D finite element model was developed using Ansys 14.5 software package in which the temperature-dependent thermal material properties was incorporated with 26 °C as ambient temperature. To consider the cooling phase during the laser welding process, the time step was gradually increased up to 400 s in developed thermal FE model. Welding speed was

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Fig. 4.1 a LBW experimental setup and b temperature measurement setup

Fig. 4.2 Thermal analysis of laser butt welding

estimated using time and distance travelled by laser moving heat source. The thermal analysis performed in the present work for laser butt welding of AISI 304 stainless steel is represented in a block diagram as shown in Fig. 4.2.

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4.3.1 Thermal Analysis Finite element model for a homogenous and isotropic material was based on the heat conduction differential equation without considering heat generation for the rectangular coordinate system (x, y, z) represented as:       ∂T ∂ ∂T ∂ ∂T ∂T ∂ K + K + K  ρc (1) ∂x ∂x ∂y ∂y ∂z ∂z ∂t where K  thermal conductivity (W/mo C), ρ  density of the, material (kg/m3 ), T  temperature (°C), c  specific, heat capacity (J/kg°C), and t  time (s). The thermal boundary conditions were applied in present thermal analysis as follows: (i) Initial condition The initial temperature which was considered for all the elements in FE model of laser butt welding can be expressed as: T = T∞ at t = 0

(2)

where T∞ is the ambient temperature, which was considered as constant (T∞  26 °C). The second boundary condition was developed by considering energy balance in the workpiece surface, and we consider as: Heat supply  Heat loss. (ii) First thermal boundary condition A specific, heat flow was acting over surface S2 in welded specimen as shown in Fig. 4.3. qn  −qsup

(3)

The quantity qn and qsup indicates the component of the conduction heat flux vector normal to the workpiece surface and heat flux supplied to the workpiece surface in W/m2 from the laser heat source, respectively. qn  {q}T {n}

(4)

(iii) Second thermal boundary condition Convection heat loss was considered over surface S1 (except the weld zone) as shown in Fig. 4.3. Newton’s law of cooling states that: Qconv  h(T − T∞ )

(5)

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Fig. 4.3 Schematic representation of CO2 laser-welded specimen

where h convection coefficient (W/m2 K) T∞ ambient temperature (°C) T sheet temperature (°C)

4.3.2 Modeling Details In thermal analysis, FE model was meshed using eight-node SOLID70 brick elements having linear shape function. SOLID70 element has advantages over the other elements like eight nodes with single degree of freedom (i.e., temperature) at each node and 3D conduction capability to perform the transient thermal analysis. FE model exhibited the 34,000 elements and 52,560 nodes after the meshing. Weld bead was formed at the middle of the welded specimen. Hence, fine mesh was applied near the weld bead to predict the temperature distribution in weld zone and heat-affected zone (HAZ) with better accuracy. To reduce the simulation time, coarse mesh was used away from the weld zone. Fusion zone was exhibited the uniform fine mesh of square size 0.5 mm × 0.5 mm. FE model was divided into 40 elements in outer region with spacing ratio of 0.05. Along through thickness of the FE model, four numbers of the elements were taken. Figure 4.3 shows the schematic representation of CO2 laser butt-welded joint of AISI 304 stainless steel sheets with location of temperature measurement point. The finite element model (FEM) of the CO2 laser butt-welded joint and meshing of model are shown in Fig. 4.4a, b.

4.3.3 Volumetric Heat Source To perform the thermal analysis of FE model of welded specimen, the moving heat source plays a very important role. In present finite element model, dimensions of the weld bead were taken from experimentally obtained weld bead after the laser

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Fig. 4.4 a Finite element model of butt weld joint and b detail of the mesh of model

welding process. Uniform volumetric heat generation was applied on the weld zone to perform the thermal analysis of the laser welding process. The element birth and death technique was used to develop the moving volumetric laser heat source. In which, initially all the element positioned at the weld bead were killed resulted in empty weld zone. Then moving heat source produced the weld bead by activating these killed elements bead by bead with time steps. The reactivated elements return to their original values of stiffness, element loads, mass, etc. The following equation can be used to calculate the heat generation per unit volume in welding process. Qgen 

η×P V

(6)

where η absorption efficiency of the material P laser power (W) V volume of the weld bead (mm3 ).

4.4 Material Properties The chemical composition of material [17] is shown in Table 4.1. Temperature-dependent thermal properties of AISI 304 steel [18] are represented in Fig. 4.5.

Table 4.1 Chemical composition of AISI 304 stainless steel Elements

Cr

Ni

Fe

Mn

C

Si

P

S

Cu

Mo

Weight %

18.4

8.9

71.2

1.06

0.06

0.34

0.03

0.011

0.05

0.05

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Thermal,conductivity, (W/,m°C) Specfic,heat, (x10) (J/kg,°C) 3 Density,,(×10),(kg/m ) 2 Convective heat transfer coefficient, (×10) (W/m °C) -1 Thermal expension,coefficient, (×10 ) (°C )

120

Thermal properties

100 80 60 40 20 0 0

200

400

600

800

1000

1200

1400

1600

Temperature (°C)

Fig. 4.5 Temperature-dependent thermal properties of AISI 304 stainless steel

4.5 Results and Discussion Numerically and experimentally obtained transient thermal profiles were compared fairly well at absorption coefficient of 21.35% which was determined by back substitution in volumetric heat source (Eq. 6). Figure 4.6a, b shows the transient temperature contour under laser power of 1.7 kW and welding speed of 400 mm/min over the top surface of welded specimen at time 9.6 s and 220 s during welding and cooling phase, respectively. From Fig. 4.6, it is observed that the peak temperature distribution in the weld zone noted to about 1749.99 °C and 46.86 °C during welding and cooling phase at time of 220 s, respectively. The peak temperature decreases gradually in the transverse direction of weld zone. Figure 4.7a, b shows the transient temperature distribution under varying laser welding speeds and laser power at weld center, respectively. Figure 4.8a, b shows the transient temperature distribution at 7 mm away from weld line in traverse direction under varying laser power and welding speed, respectively. From Fig. 4.7, it is observed that initially temperature increases rapidly to its maximum value and then starts to decreasing smoothly with same rate as the laser heat source travels away from the weld center zone, representing that the steep temperature gradient collapsed speedily. From Figs. 4.7 and 4.8, it is also observed that the increasing welding speed and decreasing laser power resulted in faster cooling rate. The peak temperature increases with decrease in welding speed and increase in laser power due to high heat input. It is also observed the base metal is heated above its melting point temperature (1440 °C) [19] for different laser welding parameters (welding speed and laser power).

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Fig. 4.6 Temperature distribution during welding process at time a 9.6 s and b 220 s

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(a) 1800

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1400 1200 1000 Y 800 600 400 200 0 0

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Fig. 4.7 Transient temperature profile at weld center under varying a welding speed and b power

Figure 4.9a, b represents the peak temperature distribution at varying laser power and welding speed along the path perpendicular to the weld centerline, respectively. Figure 4.10a, b shows the width of fusion zone (FZ) and heat-affected zone (HAZ) in welded specimen under laser power of 1.7 kW and 1.9 kW with constant welding speed of 400 mm/min, respectively. Figure 4.11a, b represents the width of fusion zone and heat-affected zone at varying welding speed and laser power, respectively.

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(a)

Power = 1.3 kW Power = 1.5 kW Power = 1.7 kW Welding speed = 400 mm/min

500

Temperature (°C)

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Temperature (°C)

500 400 300 200 100 0 0

10

20

30

40

50

60

70

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Time (sec)

Fig. 4.8 Transient temperature profile at 7 mm away from weld centerline under varying a power and b welding speed

Maximum temperature was observed at the center of the weld zone, and it decreases gradually transverse to the welding direction as shown in Fig. 4.9a, b. The peak temperature increases with an increase in laser power and a decrease in welding speed, respectively, due to an increase in heat input. The vertical line made corresponding to the temperature value of 1440 °C represents the fusion boundary from weld centerline which was extended 1.862 mm and 1.99 mm at laser power of 1.7 kW and 1.9 kW with constant 400 mm/min welding speed, respectively, as shown in Fig. 4.10. The phase transformation would occur in the region which

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Power, = 1.3 kW Power, = 1.5 kW Power, = 1.7 kW Welding,speed = 400 mm/min

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1600 1400 Temperature (°C)

25

1200 1000 800 600 400 200 0 0

5

10

15

20

25

30

Distance away from,weld,line (mm)

Fig. 4.9 Peak temperature profile away from weld center at varying a laser power and b welding speed

lies between the temperatures 1440–950 °C under equilibrium conditions [19]. This region is known as heat-affected zone (HAZ) which was extended 1.127 at laser power of 1.7 kW and 1.32 mm at laser power of 1.9 kW from fusion boundary. From Fig. 4.11a, b, it is also observed that increasing laser power and decreasing welding speed lead to increase in size of fusion zone and heat-affected zone. Figure 4.12 represents the peak temperature distribution for varying rate of heat input (i.e., heat per unit length).

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(a)

(b) 2000

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600

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Temperature (°C)

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3

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Distance from weld center line (mm)

Fig. 4.10 Fusion zone (FZ) and heat-affected zone (HAZ) at laser power of a 1.7 kW and b 1.9 kW with constant welding speed of 400 mm/min

(a)

(b)

1.8 1.5 1.2 0.9 0.6 0.3 0.0 300

400

FZ HAZ

2.1

FZ HAZ

Size of fz & Haz (mm)

Size of Fz & Haz (mm)

2.1

500

Welding speed (mm/min)

1.8 1.5 1.2 0.9 0.6 0.3 0.0 1.4

1.5

1.6 1.7 1.8 Power (kW)

1.9

2.0

Fig. 4.11 Size of FZ and HAZ at varying a welding speed and b laser power

From Fig. 4.12, it is observed that the peak temperature distribution increases with increases in heat input per unit length. It is also observed that the change of peak temperature distribution is not linearly proportional to the rate of heat input and peak temperature increment is more in lower value of heat input compare to higher value of rate of heat input as shown by red arrows in Fig. 4.12.

4.6 Validation of Thermal Model Figure 4.13a shows the comparison between transient thermal history obtained by experimentally and numerical analysis at 7 mm away from weld line. Figure 4.13b shows the comparison between the FE predicted and experimentally observed different zones of thermal contour.

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Rate of heat input vs. maximum peak temperature

Peak temperature (°C)

1800 1750 1700 1650 1600 1550 1500 180

200

220

240

260

280

300

320

Rate of Heat input (J/mm)

Fig. 4.12 Maximum peak temperature distribution for varying rate of heat input

From Fig. 4.13a, it is observed that there is a close agreement between transient thermal analysis results obtained from finite element analysis and experimental investigation with maximum error of 6.47% for the peak temperature in weldment. Figure 4.13b shows that the maximum temperature of 1558.4–1749.9 °C was obtained in the fusion zone (FZ) where melting occurs by the laser heat source. When the welding phase was finished, the sheets were allowed to cool down to the ambient temperature (i.e., 26 °C). Temperature decreases as further moving away from the weld line in the traverse direction.

4.7 Conclusions From the present study, the following conclusions can be drawn: • 3D finite element model was developed by considering the weld bead geometry of laser butt-welded AISI-type 304 stainless steel thin sheets. The temperature distribution obtained from numerical thermal analysis and experiment using Ktype thermocouples was matched fairly well with maximum error of 6.47% for peak temperature. Comparison between the numerical and experimental results revealed that the developed model had good capability for predicting the temperature history of thin laser-welded plates. • From the studies on the effect of laser welding parameters, it was observed that the cooling rate significantly influenced by the varying laser power and welding

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(a) 450

at 7 mm distance (Experimental) at 7 mm distance (FEM)

400

X-axis

Temperature (°C)

350

Welding line

Temperature measurement point

300 250 7 mm

200 Y-axis

150 100 50 0 0

50

100

150

200

250

300

350

400

450

500

Time (s)

(b)

Fig. 4.13 Comparison of simulation and experimental results a transient thermal profiles at 7 mm distance away from weld line in transverse direction and b cross-sectional views of weld bead

speed. The temperature near the fusion zone (FZ) and the heat-affected zone (HAZ) reduced rapidly with the distance from the center of the laser heat source. • On the basis of obtained peak temperature distribution from numerical thermal analysis, fusion zone (FZ) and heat-affected zone (HAZ) size were determined. It was observed that with increasing the laser power and decreasing the welding speed, peak temperature during welding, heat-affected zone (HAZ) and fusion zone (FZ) increase due to high heat input per unit length. This results in higher melting temperature zone and phase transformation temperature zone. It was also investigated that peak temperature increment decreases with an increase in heat input per unit length. When further moving, away from the center of the weld line in transverse direction, temperature value decreases gradually.

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References 1. Moraitis, G.A., Labeas, G.N.: Residual stress and distortions calculation of laser beam welding for aluminium lap joints. J. Mater. Process. Technol. 198, 260–269 (2008) 2. Ronda, J., Siwek, A.: Modelling of laser welding process in the phase of keyhole formation. Arch. Civ. Mech. Eng. 11, 739–752 (2011) 3. JayFTu, Takashi Inoue, Miyamoto, Isamu: Quantitative characterization of keyhole absorption mechanisms in 20 kW-class CO2 laser welding processes. J. Phys. D Appl. Phys. 36, 192–203 (2003) 4. Tsirkas, S.A., Papanikos, P., Kermanidis, T.: Numerical simulation of laser welding process in butt-joint specimens. J. Mater. Process. Technol. 134, 59–69 (2003) 5. Mohammed, S.N.: Analysis of temperature and residual stress distribution in CO2 laser welded aluminum 6061 plates using FEM. Al-Khwarizmi Eng. J. 7, 48–58 (2011) 6. Zambon, A., Ferro, P., Bonollo, F.: Micro-structural, compositional and residual stess evaluation of CO2 laser welded super-austenitic AISI 904L stainless steel. Mater. Sci. Eng. 528, 7350–7356 (2006) 7. Han, T.-K., Park, S.S., Kim, K.-H., Kang, C.-Y., Woo, I.-S., Lee, J.-B.: CO2 laser welding characteristics of 800 MPa class TRIP steel. ISIJ Int. 45, 60–65 (2005) 8. Piekarska, W., Kubiak, M.: Three-dimensional model for numerical analysis of thermal phenomena in laser–arc hybrid welding process. Int. J. Heat Mass Transf. 54, 4966–4974 (2011) 9. Wang, Renping, Lei, Yangping, Shi, Yaowu: Numerical simulation of transient temperature field during laser keyhole welding of 304 stainless steel sheet. Otics Laser Technol. 43, 870–873 (2011) 10. Olabi, A.G., Alsinani, F.O., Alabdulkarim, A.A., Raggiera, A., Tricarico, L., Benyounis, K.Y.: Optimizing the CO2 laser welding process for dissimilar materials. Opt. Lasers Eng. 51, 832–839 (2013) 11. Sun, G.F., Wang, Z.D., Lu, Y., Zhou, R., Ni, Z.H., Gu, X., Wang, Z.G.: Numerical and experimental investigation of thermal field and residual stress in laser-MIG hybrid welded NV E690 steel plates. J. Manuf. Process. 34, 106–120 (2018) 12. Ai, Yuewei, Jiang, Ping, Wang, Chunming, Mi, Gaoyang, Geng, Shaoning: Experimental and numerical analysis of molten pool and keyhole profile during high-power deep-penetration laser welding. Int. J. Heat Mass Transf. 126, 779–789 (2018) 13. Yilbas, B.S., Arif, A.F.M., Abdul Aleem, B.J.: Laser welding of low carbon steel and thermal stress analysis. Opt. Laser Technol. 42, 760–768 (2010) 14. Gao, H., Agarwal, G., Amirthalingam, M., Hermans, M.J.M., Richardson, I.M.: Investigation on hot cracking during laser welding by means of experimental and numerical methods. Weld. World 62, 71–78 (2018) 15. Mann, V., Hofmann, K., Schaumberger, K., Weigert, T., Schuster, S., Hafeneckera, J., Hübner, S., Lipinski, L., Roth, S., Schmidt, M.: Influence of oscillation frequency and focal diameter on weld pool new methodology to analyze the functional and physical architecture of existing products for an assembly oriented. Procedia CIRP 74, 470–474 (2018) 16. Prabakaran, M.P., Kannan, G.R.: Optimization and metallurgical studies of CO2 laser welding on austenitic stainless steel to carbon steel joint. Ferroelectrics 519, 223–235 (2017) 17. Berrettaa, J.R., de Rossi, W., das Neves, M.D.M., de Almeida, I.A., Junior, N.D.V.: Pulsed Nd: YAG laser welding of AISI 304 to AISI 420 stainless steels. Opt. Lasers Eng. 45, 960–966 (2007) 18. Vakili-Tahami, F., Ziaei-Asl, A.: Numerical and experimental investigation of T-shape fillet welding of AISI 304 stainless steel plates. Mater. Des. 47, 615–623 (2013) 19. Kim, K., Lee, J., Cho, H.: Analysis of pulsed Nd: YAG laser welding of AISI 304 steel. J. Mech. Sci. Technol. 24(11), 2253–2259 (2010)

Chapter 5

Transient Thermal Analysis on Friction Stir Welding of AA6061 Nandan Kanan Das, Arun Kumar Kadian, Avinish Tiwari, Pardeep Pankaj and Pankaj Biswas

Abstract In this analysis, a 3D finite element transient thermal model of friction stir welding (FSW) has been proposed. The heat generation in FSW consists of two main phenomena, i.e., heat generation due to friction between the tool and the workpiece and due to plastic deformation inside the material that is often termed as sliding and sticking conditions, respectively. A new heat source model is proposed in the article that accounts for both the heat generation conditions. The temperature distribution profile has been studied on the FSW butt joint of AA6061 plates. From the comparative study, a significant difference has been observed between the temperatures which have been obtained by only sliding heat source and the proposed heat source model in peak temperature. The proposed heat source model has been validated with the experiments and the error range in peak temperature lies within 5% with the experimental results.

Nomenclature TWI The Welding Institute FSW Friction Stir Welding FEM Finite Element Method N. K. Das (B) · A. K. Kadian · A. Tiwari · P. Pankaj · P. Biswas Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India e-mail: [email protected] A. K. Kadian e-mail: [email protected] A. Tiwari e-mail: [email protected] P. Pankaj e-mail: [email protected] P. Biswas e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_5

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5.1 Introduction Friction stir welding is a solid-state welding process, first introduced by The Welding Institute (TWI), [1]. The friction stir welding process uses a non-consumable rotational tool as shown in Fig. 5.1. The heat required for the welding process is generated due to the combined action of frictional resistance between the tool and the material and mechanical deformation of the material to be welded. The welding takes place above the recrystallization temperature but below the melting point temperature. It is well known in conventional joining process that if the materials are in molten state, the welding joint can easily be achieved. But, below the MP, the material joining needs external help to make a perfect welding joint, which is provided by FSW tool. In this process, the main process parameters are tool rotational speed, traverse velocity, plunging force, and tilt angle but some time right tool geometry is also essential. Since its invention, the welding technique has shown promising results in joining almost all types of materials. The technique is very effective for softer materials like aluminum (Al), magnesium (Mg), copper (Cu), etc. Aluminum is widely used by many industries due to its properties like corrosive resistant, low density, high strength, and other mechanical properties. The transportation industries like automobile, space, marine, etc., incorporating more and more Al-based parts in their product to reduce the weight of the vehicle, and thus reduction in fuel consumption is achieved. This advancement/adaptation of Al in transportation industries leads to greater challenges to achieve different types of weld. Compare to the conventional welding process, it has many advantages such as it is a green process and has no adverse effect on the environment. Requirement of post-weld cleaning and machining is very less. It eliminates almost all defects of liquid phase, such as porosity, alloy segregation, cracking, and grain growth. The mechanical properties of the welded

Fig. 5.1 Friction stir welding process

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part are also found superior. Though it has many advantages over fusion welding, but it has some disadvantages too such as it is a slower process. It requires large downward force to plunge and large clamping force to hold the workpiece. It is not yet a well established in joining of high melting point alloys like steel and titanium alloys.

5.2 Background and Literature Review Research had been done in this field by experimental as well as the numerical simulations. In the initial phase, that is before year 2000 the work done in this field was mostly experimental but soon after that, the researchers like Chao et al. [2] were among the first researchers who worked on the numerical and simulation models. The model involved a trial-and-error procedure for the heat source to predict the thermal history. The study of thermal history is significant in finding the thermal stresses and the distortion in the weld plate. The parameters like tool geometry and rotational speed impact the thermal history by influencing the heat input in the weldments. After that, many attempts were made by the researchers to find out the effect of parameters on thermal history using simulations and experimental methods. The modal proposed by Chao and Qi [3] used Coulomb’s law to calculate the heat source caused by friction between the tool shoulder and base plate but ignored the heat generation part produced by the probe surface. The thermal model developed by Gould and Feng [4] implemented Rosenthal equations for a moving heat source and predicted the temperature profiles. The tool geometry greatly affects the heat generation. The tool shoulder and pin geometry cause the heat generation depending on the process parameters. Colegrove [5] investigated the heat generation distribution on the plate and found the probe produced approximately 20% of the total heat generation which could not be neglected. However, Chao et al. [6] worked in the flow of heat between the tool and the workpieces and found 95% of the total heat generation went into the material. The influence of the preheating or dwell period on the temperature fields was investigated by Song and Kovacevic [7] which included only sliding condition in the heat source expression. The thermal studies were further extended to calculate the stresses induced by Chen and Kovacevic [8] who also studied the effect of parameter on the weldment later. Khandkar et al. [9] used a completely different torque based thermal model to study the thermal patterns using machine power input. To study the dwell period, Song and Kovacevic [10] adopted a moving mesh technique and studied the thermal patterns on the tool and the workpiece. Hamilton et al. [11] incorporated plastic deformation heat generation along with the frictional heat generation according to the ratio of the plastic energy to the total effective energy. It has been seen that the most of the simulation carried out in research paper have taken a temperature independent heat source; i.e., they have only considered the sliding condition. This type of heat source often produces error such as the temperature of the simulation may rise above the melting point temperature of the

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material which is practically impossible. So, this method for heat source calculation needs alteration. To improve the heat source calculation, both the sliding and sticking conditions need to be considered. In this study, the heat generation calculation is first done by considering the sliding condition, as the temperature increased the heat generation with the sliding condition decreased and at a high-temperature sticking condition dominates. For the present analysis, a mathematical heat source has been developed in which both sticking and sliding has been considered.

5.3 Mathematical Model Although in the actual process of welding, both the sticking and sliding conditions are present simultaneously. But for the sake of better understanding, the heat generations are calculated separately and merged together later on. Based on the phenomenon, mathematical equation has been developed. For the two conditions, the forces responsible for heat generation are different.

5.3.1 Friction at the Surface of the Tool Due to Rotation A frictional stress between the tool and workpiece is taken as ‘μP’. The tool rotational speed is taken as ‘ω’, where speed of a point on the tool surface is ‘ωr’ and that the speed of the material due to mass flow is ‘v’ at that point. The heat generated per unit area due to friction between the tool and the workpiece will be as stress multiplied by the relative velocity as shown below Q 1  μP(ωr − v)

  W/m2

(5.1)

But in this initial condition, the frictional stress is equal to the shear stress i.e. μP τ Thus, the equation becomes Q 1  τ (ωr − v)

  W/m2

(5.2)

5.3.2 Plastic Deformation of the Metal Due to the Visco-Plastic Mass Flow The tool movements force the material around the tool to flow with the tool. This leads to the plastic deformation of the material. Due to the interlayer friction between the flowing material heat is generated, this heat generation between the interlayer

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Fig. 5.2 Heat production due to friction

has to be calculated. The different layers of the materials have different velocities. This difference between velocities between the layers causes the heat generation. The layer closest to the tool will have maximum velocity (let, v), and the layer farthest away from the tool will be static or have no velocity. The difference between the velocities between the two layers of the material is ‘dv’ and the frictional stress of τ between them will be ‘τ · dv’ as shown in Fig. 5.2. By integrating this expression, the total heat generation has been calculated in the material flow layers. It has been assumed that the τ is constant across the layer and is equal to the frictional stress between the tool and the workpiece. Therefore, the heat generated due to plastic deformation per unit area has been given by: Q 2  ∫ τ · dv  τ ∫ dv  τ · v

  W/m2

(5.3)

By adding the Eqs. (5.2) and (5.3), the total heat generation has been calculated as: Q   Q 1 + Q 2  τ · ω · r

  W/m2

(5.4)

Considering the heat generation stress (k) between the tool and workpiece, the equation finally became: Q   Q 1 + Q 2  k · ω · r

  W/m2

(5.5)

There are other processes in which heat is generated such as the friction heat generation when the tool enters into the plates. It should also be considered in order to meet the actual phenomenon. But the current analysis is a transient thermal analysis, and it is only considering the thermal aspect of the tool rotation and mass flow.

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Entering and exiting of the tool into the plates are not considered in this simulation. The heat generated during the entering and exiting is negligible in comparison with the heat generation in actual friction stirring process. In the past analysis, performed by the researcher, the value of τ  μP is taken. Most of the researcher used this approach only for calculating the value of τ. This gives disappointing results. Sometimes the predicted temperature rises above the melting point temperature of the material which is contradicting with the FSW a solid-state welding process. Since it is not correct, it requires modification. The main reason for rising the temperature above melting point is the value of τ as μP. This relationship implies that heat generation is proportional to the applied pressure P, which means if the applied vertical pressure is increased the heat generation between the tool and the workpiece also increase. Therefore, the temperature of the workpiece also increases. It is not correct to directly proportionate the heat generation to the applied vertical pressure. To understand the correct value of τ, the following concept must be understood. It is discussed previously, the FSW process has two main conditions while the tool stirring into the workpiece, i.e., the sliding and the sticking conditions. In sliding condition, the tool and the workpiece slide over each other’s surfaces and the heat generation is purely frictional. The frictional heat directly depends upon the vertical force applied on the tool. So, the maximum value the τ can be attained is μP. But in case of sticking condition, τ will be less than the μP as the heat is generated due to the deformation of the material. As the temperature of the material rises, the sticking condition remains prominent, while the sliding condition becomes in effective. With this rise in temperature, the shear yield strength of the material decreases The shear yield strength of the material is the minimum shear stress required to yield (or extensively plastically deform) the material. The sticking condition is said to be take place when the value of τ is equal to the shear strength, because the material is able to deform extensively and flow at the tool velocity. Thus, when the sticking condition is effective, i.e., at higher temperatures, the τ remains less than μP. The process is shown in a flowchart in Fig. 5.3. The flowchart explains how the value of τ changes with the rise in temperature. By this method of change in value of τ, the temperature never rises above the melting

Fig. 5.3 Flowchart of FSW process

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Fig. 5.4 Variation of τ with temperature

Temperature (K)

Shear strength (MPa)

589

9.5

644

6

923

0

Shear Stress in MPa

Table 5.1 Variation of shear strength with temperature

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Value of τ 4 3 2 1 0

0

500 Temperature in Kelvin

1000

point temperature of the material. As soon as temperature reaches near the melting point, the material softens and sticking starts thus reducing the value of τ, which causes the reduction in the heat generation. Therefore, the temperature doesn’t rise above the melting point temperature. For the current analysis, two separate conditions are taken in which each condition exist solely, i.e., completely sliding condition and completely sticking condition. Both conditions do not coexist together. So, it is important to identify the temperature from which completely sticking starts and completely sliding stops. The temperature at which τ becomes equal to the shear strength is the temperature where the heat generation is due to the sticking phenomenon of the process. When the value of τ is less than μP, τ will be equal to the k, i.e., the shear strength. The value of k also varies with temperature which is given in Table 5.1. The value of τ has taken as zero at melting point, 923 K (this is done, as, it takes negligible shear to deform a fluid). The other two values of k are legitimate laboratory test results. The best fitting function for the above values of k is given by Eq. (5.5). The variation of τ with temperature is shown in Fig. 5.4. k  0.0001 ∗ (Temp − 923)2

(5.6)

Equating this curve to the value of μP, we get the temperature as 717 K. Thus, k will be less than μP when temperature > 717 k and sticking will start. Therefore, τ will be (a) μP  0.3 * 11.2 MPa  3.36 MPa till Temperature < 717 K (sliding) (Intersecting points); (b) k  0.0001 * (Temp − 923)2 after Temperature > 717 K (sticking). Linear fitting function of above two equations (i.e. equation (a) and equation (b)) (Linear regression): τ  −(0.0065 · Temp) + 6 (MPa)

(5.7)

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τ is given as a function of temperature into ANSYS. It is possible to find functions which fit extremely well to the points plotted, the application of loads with such a steep fall in heat flux input make the solution difficult to converge. Therefore, a best fitting linear function is implemented. It ensures that the temperature will not rise above the melting point and will be a more accurate simulation of a real FSW.

5.4 Boundary Conditions For the simulation purpose, the governing Eq. 5.7 has been used and various condition taken as follows:       ∂T ∂ ∂T ∂ ∂T ∂T ∂ K + K + K  ρC (5.8) ∂x ∂x ∂y ∂y ∂z ∂z ∂t where K ρ C T t

Thermal Conductivity of material (W/m2 ) density of material (kg/m3 ) specific heat (J/kg C) temperature (°C) time (s) Initial condition T  T∞ for t  0 First boundary condition, for tool surface qn  −qsup at t > 0 Second boundary condition, for remaining surface i.e qn  qconv  h f (T − T∞ ) for t > 0

The following loads were applied to best simulate the thermal aspect of FSW. A surface heat flux has been applied to the top surface of the model to simulate the heat produced at the shoulder of the tool due to friction and plastic deformation of the material. The surface heat flux has been applied for the shoulder region only in which the inner radius is 3 mm (which is the radius of the probe) and outer radius is varied according to the tool shoulder dimensions. As discussed earlier, the total heat generated per unit area due to both plastic deformation and friction is given by: Q   τ · ω · r

  W/m2

(5.8)

For the probe, the heat generation is applied to 3D volume which is in W/m3 . This load is applied such that a volumetric heat generation equal to the given value in magnitude for a selected volume of the geometry.

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For the pin region, i.e., 0–3 mm radius of the tool volumetric heat generation has been applied to the model to simulate the heat produced at thin pin surface of the tool due to friction and plastic deformation of the material. Although the heat generation in the pin taking place at the surface of the pin, it should be applied on the surface, but it is actually difficult to apply the heat flux on the cylindrical surface of the pin into the model. Thus, a volumetric heat generation has been applied in the pin volume. The heat generation in the pin is approximately 20% of the total heat generation. As stated earlier, the total heat generated per unit area due to both plastic deformation and friction is given by τ · w · rp . Multiplying this by the area of the pin surface gives the total heat generated. But since the load is given as a volumetric heat generation (W/m3 ), it is important to divide the total heat generated by the volume of the pin. Thus, the value of the volumetric heat generation load is:    2 · π · rp · Hp  Q   τ · ω · rp ∗  2 · τ · ω W/m3 2 π · r p · Hp

(5.9)

Here τ (the frictional shear stress between the pin’s side walls and the workpiece) has nothing to do with P (the vertical pressure applied). Many papers were published FSW simulations by taking the τ value as the shear strength at 75% of its melting point temperature. In our case, it is k, i.e., 2.272 MPa. This assumption is taken because the material near the pin is heated material which is having a high temperature. Therefore, τ is taken as constant value as 2.272 MPa. To apply the natural convection in the simulation, a convective heat transfer is applied on all the surfaces except the bottom surface. The convective heat transfer coefficient is taken as 10 (W/m2 K). In actual process, the main source of heat loss is due to the conduction of the backing plate on which the workpiece rests. But in this simulation, a convective heat transfer is taken instead of conduction at the bottom surface. The conduction heat transfer is much higher than the convective heat transfer. So, for simulation purpose this convective (instead of conduction) heat transfer coefficient is taken as 100 (W/m2 K). This ensures the amount of heat loss by the bottom surface is the same as that of conduction through the backing plate. For better understanding, the following assumptions and notations are explained in the current analysis. The tool dimensions are assumed in this present study as, (Rs ) Shoulder Radius, (rp ) Pin Radius taken as constant 3 mm, (Hp ) Pin Height-6 mm. P: This is the pressure between the tool and the workpiece. This develops as a result of the downward force applied on the tool. In this current analysis, the downward force (F) is assumed to be 5.5 kN. In terms of the shoulder radius of the tool and the downward force applied, the pressure between the tool and workpiece is: P thus, P  11,200,000 Pa.

F F  A π Rs2

(5.10)

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There are two contact conditions possible at the tool and workpiece interface sliding and sticking. In sliding, the velocity of the material in immediate contact with the tool is less than velocity of a point on the tool. In sticking, velocity of the material in immediate contact with the tool is equal to the velocity of a point on the tool. τ: The frictional stress between the tool surface and the workpiece. The maximum value of τ can be μP; w: This is the rotational speed of the tool; V : This is the traverse speed of the tool, v: This is the velocity of the material layer in contact with the tool, r: This is the distance of a pint from the tool axis at a particular instant.

5.5 Material Properties The properties of AA6061-T6 (like most metals) vary significantly with temperature. Thus, for more accurate results, the properties of the materials are given as different values for different temperatures. Tables 5.2 and 5.3 give the values of the material properties, thermal conductivity, and specific heat for different temperatures. The density of the material is 2700 kg/m3 and is not given as temperature dependent.

Table 5.2 Material properties of AA6061-T6

Property Density

Table 5.3 Temperature dependent thermal properties of AA6061-T6

Value

(kg/m3)

2700

Tensile strength, ultimate (MPa)

290

Tensile strength, yield (MPa)

240

Thermal conductivity at 100 °C (W/m2 K)

175

Melting temperature (°C)

585

Temperature (°C)

Thermal conductivity (W/m °C)

Heat capacity (J/kg °C)

37.8

162

93.3

177

978

148.9

184

1004

204.4

192

1028

260

201

1052

315.6

207

1078

371.1

217

1104

426.7

223

1133

945

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5.6 Results and Discussion The temperature profiles of the two points, with and without sticking conditions are shown in Fig. 5.5. The maximum welding temperature attained when only sliding condition was considered and was found to be much higher than the melting point temperature, i.e., 1020 K. But the maximum temperature attained with sticking and sliding conditions were remained well under the limits. The analyses were done at 1400 rpm rotational speed, 2 mm/s welding, or traverse speed for a 27 mm tool diameter. The results showed the welding temperature a lot higher than melting point temperature of the material. So it was necessary to involve the sticking condition into the heat source computation. The temperature obtained by the implementation of both the condition was more reasonable and close to the real one. The difference in temperature was quite significant. So, implementation of the sticking phenomenon is quite important. While performing the welding, there had been difference in the top and the bottom surface of the weld plate. This difference in top and bottom surface was clearly observed higher at centerline, but it gradually decreased away from the centerline. It ultimately leads to either bending or the residual stress in the plate. This difference in temperature was studied at A and B and shown in Fig. 5.6. The parameters used in this study were 1400 rpm tool rotational speed, 2 mm/s welding speed, and 27 mm tool shoulder diameter. The A (top surface) shows a different temperature curve then others three curves because it lies under the tool shoulder and there had been no heat loss from that point. The heat loss only occurred when the tool completely passed by that point. At the same time, the bottom surface lost heat due to conduction of the base plate. Although heat also lost by the tool conduction from the top surface, but it is very less compared to the heat lost from the base plate. The temperatures of top and bottom surfaces of the point A were observed 710 and 699 K, while at point B they were

A(only sliding) A(sticking and sliding)

1050 1000 950 900 850 800 750 700 650 600 550 500 450 400 350 300

(b)

B (only sliding) B (Sticking and sliding)

900 850 800 750 Temperature (K)

Temperature (K)

(a)

700 650 600 550 500 450 400 350 300

0

20

40

60

80

100

Time (s)

Fig. 5.5 Temperature versus time a point A, b point B

0

20

40

60

Time (s)

80

100

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750 700

Temperature (K)

650 600 550 500 450 400 350 300 0

20

40

60

80

100

Time (s)

Fig. 5.6 Top and bottom surface temperature at A and B points

Fig. 5.7 Recrystallization zone along weld line and at cross section

noted to be 629 and 618 K. The temperature zone along the weld line and at the cross section is shown in Fig. 5.7. Figure 5.8 shows temperature contour obtained by transient thermal analysis using moving heat source.

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Fig. 5.8 Temperature contour obtained by transient thermal analysis using moving heat source

5.7 Experimental Setup Experiments were conducted for 6 mm AA6061 plate of dimension 300 × 150 mm2 . The tool was rotated at 1400 rpm and the welding speed was taken 2 mm/s with a tool shoulder diameter 30 mm. A vertical milling machine with a 7.5 hp motor capacity was used to carry out the FSW experiment as shown in Fig. 5.9. A flat shoulder and conical pin with base diameter 6 mm and pin tip diameter 3 mm were used. SS310 alloy was used to fabricate the FSW tools. The tool material properties are given in Table 5.4. The experimental setup is shown in Fig. 5.10a. The thermocouples were used to obtain the data. Thermocouples were applied at 20 mm from the center line. The thermocouple employed at the center of the plate was taken to validate the simulation results are shown in Fig. 5.10b. The peak temperature in simulation was found to be 2.6% higher than the experimental peak temperature value.

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Fig. 5.9 Vertical milling machine

Table 5.4 Physical properties of SS310

Property

Value

Hardness, Brinell

160

Tensile strength, ultimate (MPa)

655

Tensile strength, yield (MPa)

275

Thermal conductivity at 100 °C (W/m2 K)

14.2

5.8 Conclusions It is quite important to consider heat generation due to plastic deformation in the FSW simulation as it has significant effect at higher temperature on total heat generation. Including sticking condition to the analysis decreases the heat generation at higher

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Fig. 5.10 a Experimental setup and b simulation comparison

tool rotation values. This represents the real condition. If the sticking condition is ignored, the analysis results in wrong prediction of temperature profile. For only sliding condition, the maximum temperature exceeds the melting point temperature of the welding material. The proposed heat source model correctly predicts the temperature profile for the FSW of AA6061. The peak temperature varies with in 5% with the experimental peak temperature values. The top surface and the bottom surface of the weld plate have same temperature near to the weld line but away from the weld line it decreases. This difference in temperature produces a temperature gradient, which is not much significant in case of thin plate but in case of thick plates it will play important role in predicting thermal stresses. Any point in the workpiece has a similar temperature-time curve with the rate of increase in temperature being more in magnitude than the rate of decrease in temperature. This is probably because the power generated by the FSW tool is much more than the cooling offered by natural convection or the backing plate conduction.

References 1. Nicholas, E.D., Needham, J.C., Murch, M.G., Temple-Smith, P., Dawes, C.J., Thomas, W.M.: Friction-stir butt welding, 9125978(8) (1991) 2. Chao, Y.J., Qi, X.: Thermal and thermo-mechanical modelling of friction stir welding of aluminium alloy—6061-T6. J. Mater. Process. Manuf. Sci. 7(2), 215–233 (1998) 3. Chao, Y.J., Qi, X.: Heat transfer and thermomechanical analysis of friction stir joining of AA6061-T6. In: First International Symposium on Friction Stir Welding, Thousand Oaks, CA, USA (1999) 4. Gould, J.E., Feng, Z.L.: Heat flow model for friction stir welding of aluminium alloys. J. Mater. Process. Manuf. Sci. 7(2), 185–194 (1999) 5. Colegrove, P.: 3-Dimensional flow and thermal modelling of the friction stir welding process. In: Second International Symposium on Friction Stir Welding, Gothenburg, Sweden (2000)

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6. Qi, X., Tang, W., Chao, Y.J.: Heat transfer in friction stir welding—experimental and numerical studies. ASME J. Manuf. Sci. Eng. 138–145 (2003) 7. Song, M., Kovacevic, R.: Thermal modelling of friction stir welding in a moving coordinate system and its validation. Int. J. Mach. Tools Manuf. 43, 605–615 (2003) 8. Chen, C.M., Kovacevic, R.: Finite element modelling of friction stir welding—thermal and thermo-mechanical analysis. Int. J. Mach. Tools Manuf. 43, 1319–1326 (2003) 9. Khan, J.A., Reynolds, A.P., Khandkar, M.Z.H.: Prediction of temperature distribution and thermal history during friction stir welding: input torque based model. Sci. Technol. Weld. Join. 8(3), 165–174 (2003) 10. Song, M., Kovacevic, R.: Heat transfer modelling for both workpiece and tool in the friction stir welding process: a coupled model. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 218(1), 17–33 (2004) 11. Sommers, A., Dymek, S., Hamilton, C.: A thermal model of friction stir welding applied to Sc-modified Al–Zn–Mg–Cu alloy extrusions. Int. J. Mach. Tools Manuf. 49, 230–238 (2009)

Chapter 6

Recycling of H30 Aluminium Alloy Swarfs Through Gravity Die Casting Process C. Bhagyanathan, P. Karuppuswamy, K. Gowtham Kumar, M. Ravi and R. Raghu Abstract The turning and boring scraps obtained on machining of aluminium is increasing day by day and these scraps are utilised for degraded applications in its next cycle of usage due to declined level of properties. Hence, recycling of aluminium machining scraps without compromising mechanical properties is highly essential to make it as alternative for primary aluminium made components. Therefore, the present study focused on production of the secondary aluminium alloy by recycling H30 aluminium turning and blocky scraps. Weight loss and energy consumption during production of the secondary aluminium alloy is measured. Chemical composition, porosity examination and mechanical properties were assessed on the secondary aluminium alloys and compared with the properties of the virgin H30 aluminium alloy. The mechanical properties of the secondary aluminium alloy are found lower than that of virgin H30 aluminium alloy. Therefore, alloying elements are added during recycling of blocky and turning scraps, and found that improved mechanical properties are attained. Thus the secondary aluminium alloy developed with better performance can be utilised for the automotive components and other applications wherever high strength is essential.

C. Bhagyanathan (B) · P. Karuppuswamy · K. Gowtham Kumar · R. Raghu Department of Mechanical Engineering, Sri Ramakrishna Engineering College, Coimbatore 641022, India e-mail: [email protected] P. Karuppuswamy e-mail: [email protected] K. Gowtham Kumar e-mail: [email protected] R. Raghu e-mail: [email protected] M. Ravi CSIR-NIIST, Trivandrum 695019, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_6

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Nomenclature AA GDC ASTM SAE OES ASM UTM UTS BHN

Aluminium Alloy Gravity Die Casting American Society for Testing and Materials Society of Automotive Engineers Optical Emission Spectrometer American Society for Metals Universal Testing Machine Ultimate Tensile Strength Brinell Hardness Number

6.1 Introduction In the recent years, the application and usage of the aluminium alloys are increasing in numerous fields as they exhibit low density and high strength combined with superior corrosion resistance. Aluminium usage in transport applications aids in saving of energy and reduces the CO2 emissions significantly for the total lifetime of the component [1–3]. As the resources for the primary production of the aluminium are getting depleted, recycling of aluminium scraps and utilizing the recycled scraps for the production of components becomes essential [4, 5]. Aluminium recycling has considerable impact on saving of resources, energy reduction (up to 95%), cost reduction and protection of environment [6, 7]. Recycling of aluminium reduces the cost greatly when compared to the production of the primary aluminium since it involves mining of bauxite and alumina purification through the Bayer process [3, 8, 9]. The production of secondary aluminium alloy through recycled scraps requires only 10–20 MJ kg−1 whereas primary alloy production requires 186 MJ kg−1 [10, 11]. Hence, investigation on the production of secondary aluminium alloy through recycling is highly essential [12, 13]. Large amount of aluminium scraps are produced in the form of swarfs during the production of the components through machining process. These swarfs are generally recycled through remelting process in the furnaces and transformed into the ingots. There are several difficulties associated in recycling of the machining swarfs by conventional recycling methods [14]. Decrease in yield of the melt, reduction of purity and decline in mechanical properties are the various problems met during the actual recycling of machining swarfs [15]. The resulting scraps from the machining processes are hard to recycle as they are small sized elongated spiral shaped with surface been contaminated with the presence of oxides, greases, oils and other lubricants [14, 16–18]. However difficulties are to be addressed in the recycling process in order to ensure the sustainability of the recycling process. Review on the solid state recycling techniques available for the aluminium alloys has been made and reported on the quality of the samples with respect to the prepa-

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ration of chips, addition of materials, geometry of the die and process parameters. It is inferred that the significant effort in recycling is highly essential in order to match industrial requirements [19, 20]. Recyclability of aluminium alloy AA 336 turnings has been studied under the effect of various compacting pressures. Higher pressure enhanced the density of the samples which in turn decreased the weight loss during melting. Chemical analysis revealed that chemical composition of the recycled samples falls within the range of the AA 336 alloy produced through conventional casting [21]. A study has been carried out on the conversion of the machined chips of A6060 aluminum alloy into finished products through hot extrusion followed by cold extrusion. Results revealed that the products produced out of the chips exhibited relatively similar surface quality to that of the original products [22]. Investigation on the recycling of the aluminium machining scraps through hot extrusion process has been done under different extrusion ratios (10 and 18). The samples produced under the ratio of 18 displayed straight extrusion with absence of warping whereas the samples made out of the ratio of 10 displayed cracks and voids [23]. Direct recycling of aluminium 6061 machined chips through forging process under the influence of the parameters such as chip size, holding time and pre-compaction has been studied using Response Surface Methodology approach. It is observed that the holding time has the significant effect over the properties of the recycled product compared to that of parameters such as pre-compaction and chip size. It is concluded that optimum parametric condition of holding time (120 min), pre-compaction (4 times) and the chip size (large) resulted in the best properties of the product [24]. From the literature review, it has been observed that there was lack in research on the recycling of the aluminium swarfs produced during the machining process and investigation on the mechanical properties of aluminium alloy produced out of the recycled swarfs. Particularly, studies were not reported on the recycling of the 6082 (H30) aluminium alloy swarfs and its mechanical properties. Therefore, the current study aims to recycle the 6082 (H30) aluminium alloy swarfs and blocky scraps under degassing fluxes at laboratory scale. The research is also aimed to assess the chemical composition, microstructural and mechanical properties of the secondary alloys and to compare with that of the virgin H30 aluminium alloy.

6.2 Materials Aluminium 6082 (H30) alloy blocky scraps and turning swarfs (shown in Fig. 6.1) have been considered for recycling since this alloy is commonly subjected to machining process. H30 alloy is mostly used for structural applications since it possess better corrosion resistance combined with higher strength and it replaces the 6061 aluminium alloy in numerous applications. It possess the density of 2.7 gm/cm3 and it has been utilized in the applications such as high stress applications, trusses, bridges, cranes, automotive components, rail coaches, truck frames, ship building and bicycles.

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Fig. 6.1 H30 turning swarfs

6.3 Experimental Procedure Gravity Die Casting (GDC) process was employed for the production of the secondary aluminium alloy out of the H30 aluminium blocky scraps and turning swarfs resulted from the machining process. This casting process produces lesser effluents and clean cast parts. Also this process has greater control over the composition of the cast part. The scraps and swarfs collected separately and were initially subjected to the pre-processing before charging into the furnace. Then the charge was melted and degasification of the melt was carried out. Finally the melt was cleaned before casting of the secondary aluminium alloy through GDC process. The collected scraps and swarfs were crushed in the power press tool (Fig. 6.2). The crushed scraps were further washed (Fig. 6.3) and dried using the heavy duty oven (Fig. 6.4) before melting process, and loaded into the furnace (Fig. 6.5) for melting. The loading time of the scraps and swarfs was greatly influenced by its amount and shape. The solid aluminium gets converted into the molten metal upon the heat transfer from the surface of the scraps/swarfs to its core under melting process. The amount of the scraps/swarfs also influences the duration of the melting process. The melt degasification using nitrogen gas (inert) was done for removal of the hydrogen from the molten metal by using the spinning rotor (Fig. 6.6). Degassing fluxes of Hexachloroethane (C2 Cl6 ) were plunged into the melt and stirred. The melt was held for 20 min at 720 °C to remove hydrogen from the molten metal as well as to lift oxides and particles to top of the bath for easy removal. Degasification mainly eliminates the unwanted gases from the mould by bubbling at the bottom of the container [25]. The degassing should be done at lowest temperature because as the temperature increases, the volume of the gas that passes for degassing increases. The die was simultaneously coated to hinder the effect of direct chilling as the molten metal directly contacts with the mould surface. Preheating in the GDC process was done in an industrial oven to remove the possibility of formation of temperature

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Fig. 6.2 Crushing and shredding press

Fig. 6.3 Washing apparatus

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Fig. 6.4 Heavy duty oven

Fig. 6.5 Furnace used for melting of scraps and swarfs

gradients. If the die was preheated to optimum temperature, defects will not occur and also the cast part can be easily ejected from the die. Hence the die was coated and preheated to an optimum temperature of 200 °C for 30 min. Each die half was first cleaned from the previous injection and then lubricated to facilitate the ejection of the next part. The lubrication time increases with part size, as well as the number of cavities and side-cores. Also, lubrication may not be required after each cycle, but after 2 or 3 cycles, depending upon the material. After lubrication, the two die halves were closed and securely clamped together. Sufficient force has been applied to the die to keep it securely closed while the metal was

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Fig. 6.6 Degassing of the molten metal

Fig. 6.7 Pouring of the molten metal

injected. The H30 molten metal was poured into the die cavity (Fig. 6.7) and time was given for solidification. After complete solidification of the alloy, the solidified part was ejected out of the die cavity. The properties of the secondary aluminium alloys (from blocky scrap and turning swarfs) were compared with that of the virgin H30 aluminium alloy cast through same process.

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6.4 Results and Discussion The efficiency of recycling is highly dependent on the shape, size (source of the scrap/swarf) and its contamination level. In order to get reliable information on the influence of different types of scraps/swarfs on the property of the recycled product, H30 aluminium alloy blocky scraps and turning swarfs (machining) were recycled. The metal oxidation loss, chemical composition, porosities and mechanical properties such as hardness and tensile strength are discussed.

6.4.1 Melt Loss The H30 blocky aluminium scraps and turning swarfs are measured for its weight before melting and after production of the ingots. The melt loss is calculated for blocky scraps and the turning swarfs and found as: Melt loss for blocky scrap: 2.7% Melt loss for turning swarf: 7% The melt loss is computed in order to study the influence of the processing condition on the fabrication of the secondary aluminium alloy with the H30 blocky scraps and turning swarfs. The melt loss for blocky scrap and turning swarfs are found very low (2.7% and 7% respectively) which shows that the GDC process can be employed for successful production of the secondary aluminium alloy. The aluminium alloy is highly susceptible to oxidation and possesses high reactivity. The low loss indicates that the GDC process has higher efficiency in recycling of the aluminium scraps and swarfs for the production of the secondary aluminium alloy. The recycled alloy has been further subjected for determination of chemical composition, mechanical strength and defects.

6.4.2 Evaluation of Chemical Composition Casting alloys are typically specified in accordance to ASTM and SAE alloy specifications. The performance of the aluminium alloy is largely determined by the chemical composition. This chemical composition will get change depending upon the addition of the alloying elements during the processing of molten metal. The evaluation of chemical composition is highly essential in order to attain the desired performance. Therefore pure H30 aluminium alloy and secondary aluminium alloy produced out of blocky scrap and turning swarf is subjected to analysis using Optical Emission Spectrometer (OES) and the determined chemical composition is displayed in Table 6.1. The standard chemical composition of the H30 aluminium alloy is taken from the ASM Handbook Vol. 2 for comparison.

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Table 6.1 Chemical composition of the virgin and secondary aluminium alloys Description

Al

Standard

95.2–98.3 0.7–1.3 0–0.5 0–0.1 0.4–1.0 0.6–1.2 0–0.25 0–0.2

Si

Fe

Cu

Mn

Mg

Cr

Zn

0–0.1

Ti

Virgin alloy

97.23

0.985

0.231 0.1

0.424

0.624

0.082 0.15

0.094

Blocky scrap alloy

97.59

0.964

0.169 0.03

0.557

0.528

0.014 0.026

0.018

Turning swarf alloy

97.99

1.065

0.189 0.058 0.568

0.015

0.013 0.015

0.019

From the chemical analysis, it is observed that the major alloying elements i.e., Si and Mn of the secondary aluminium alloy produced out of the blocky scraps and turning swarfs are found nearer to the pure H30 aluminium alloy and also the composition lies within the range of the standard H30 aluminium alloy. In case of blocky scrap, loss of copper is observed during production of secondary aluminium alloy whereas in turning swarf, there is loss of copper as well as great loss of magnesium during recycling. This is attributed to the loss of magnesium during machining and also during the melting process. This loss can be compensated by adding sufficient amount of copper and magnesium alloying element during the production of the secondary aluminium alloy. 6082 Aluminium (H30) alloy generally possess greater machinability, higher corrosion resistance and better strength. It has been widely in usage for several transport and structural applications hence investigation of its defects and mechanical properties is a basic requirement for extensive applications. The processing methods, solidification pattern greatly influences on the mechanical properties of the aluminium alloy [26, 27].

6.4.3 Porosity Inspection Porosity occurs in the form of the void or hole in the cast component. Understanding the various porosity-type defects also helps in casting design. While some defects can be fixed by the manufacturing process, others can be fixed through design changes or a combination of both. By knowing the casting factors that are likely to contribute to the different defects, potential problems can be avoided by relocate porosityprone areas to non-structural sections of the part and establish mutually acceptable levels of porosity present. The shape, size and location of the porosity determine the properties of the cast component and its performance. The pure H30 aluminium alloy and secondary aluminium alloys produced out of the blocky scraps and turning swarfs have been cut and observed under microscope to analyze the presence of the porosities (Fig. 6.8) and the measured sizes of the porosities are displayed in Table 6.2.

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Fig. 6.8 Size of the porosities. a Virgin alloy, b secondary alloy (blocky scrap) and c secondary alloy (turning swarf) Table 6.2 Porosity size of the virgin and secondary aluminium alloys

Property

Virgin alloy

Secondary alloy (blocky scrap)

Secondary alloy (turning swarf)

Porosity size (µm)

8–120

14–600

20–1300

From the microstructures, it is observed that size and the density of porosity is higher for the secondary aluminium alloy produced out of H30 turning swarfs compared to that of the blocky scrap alloy and virgin alloy. The presence of larger porosity may deteriorate the properties of turning swarf H30 aluminium alloy compared to the blocky scrap and the virgin H30 aluminium alloy.

6.4.4 Evaluation of Mechanical Properties Mechanical testing gives an evaluation of the metal and the casting to determine whether the properties are in compliance with the specified mechanical requirements.

6 Recycling of H30 Aluminium Alloy Swarfs … Table 6.3 Mechanical properties of the virgin and secondary aluminium alloys

93

S. no.

Properties

Virgin alloy

Secondary Secondary (blocky alloy scrap) (turning swarf)

1

Hardness (BHN)

94

86

62

2

Tensile strength (MPa)

297

272

119

The mechanical properties of the secondary aluminium alloys are evaluated and compared with the virgin aluminium alloy to ensure the achievement of desired strength. Properties such as hardness and tensile strength of the alloy are evaluated as per the ASTM standards. Hardness values generally relate to an alloy’s machinability and wear resistance. The specimens are taken from the cast component and are machined. The machined specimens are polished using emery sheets for the attainment of good surface finish. The specimen hardness is evaluated using the Brinell Hardness Tester setup which is incorporated with 10 mm carbide ball. Load of 500 kgf has been applied for producing the indentation on the specimen surface. The tests are repeated and the average value has been taken for evaluating the hardness of the particular surface. The samples are taken from the cast component and prepared as per the ASTM standard. The prepared specimens are tested in Universal Testing Machine (UTM) for the determination of Ultimate Tensile Strength (UTS). The tests are repeated and the average value is taken for the average tensile strength of the specimen which is shown in Table 6.3. The obtained values of secondary aluminium alloy (hardness and tensile strength) are compared with the properties of the virgin aluminium alloy. The hardness and tensile strength of the secondary aluminium alloy produced out of turning swarfs are found lower when compared to the properties of other two alloys. The presence of larger porosity deteriorates the properties of turning swarf H30 aluminium alloy compared to the blocky scrap and the virgin H30 aluminium alloy. The major reason for this decrease in the mechanical properties is the loss of magnesium as evident from the results of the chemical composition. Although, the slag was not accounted for this study, the quantity of slag produced for turning swarfs were higher than the virgin and blocky scraps of aluminium alloy. This is attributed to the higher surface to volume ratio of the turning swarfs and greater amount of oxide layer presence on the surface of the turning swarfs. This resulted in the higher release of oxides in the turning scrap which got agglomerated in the slag.

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S. no.

Modified secondary aluminium alloy

Hardness (BHN)

Tensile strength (MPa)

1

Cu added blocky scrap

89

288

2

Cu and Mg added turning swarf

86

284

6.4.5 Effect of Alloying Elements The mechanical properties of the secondary aluminium alloys are found lower than virgin aluminium alloy which is due to the loss of strengthening elements before and during melting of the scraps. In case of blocky scrap, loss of copper is observed during production of secondary aluminium alloy whereas in turning swarf, there is loss of copper as well as loss of magnesium during recycling (Table 6.1). Thus, Cu is added to the blocky scrap and Cu and Mg are added to the turning swarf during recycling of the scraps to compensate the element loss which inturn may increase the mechanical properties of the secondary aluminium alloy. The modified secondary aluminium alloy with alloy additives and obtained mechanical properties are shown in Table 6.4. Hardness and tensile strength are taken as the function with respect to the addition of alloying elements. The hardness and tensile strength of the Cu added blocky scrap alloy gets enhanced nearer to the properties of the virgin aluminium alloy. This is attributed to the extent of aluminium strengthening takes place upon Cu addition. From the Table 6.4, it is observed that there is drastic increase in mechanical properties in the turning swarf secondary alloy due to combined strengthening effect of Cu and Mg. The strengthening can also be attributed to the formation and dispersion of Mg2 Si compound in the H30 aluminium alloy, as reported elsewhere [28, 29]. In H30 aluminium alloy, there is also possibilities for formation of other compounds such as Al6 Mn, Al6 (Mn, Fe), Al10 Mn2 Si which also might be reason for strengthening of the secondary aluminium alloy. Thus the modified secondary aluminium alloy with better performance can be utilized for the automotive components and other applications wherever high strength is essential.

6.5 Conclusion The virgin H30 aluminium alloy, blocky scrap and turning swarfs are melted and cast successfully through the gravity die casting process. The loss of molten metal during the melting process resulted very low which indicates the higher efficiency of

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the process employed for recycling of the aluminium scraps/swarfs. The secondary aluminium alloys has the composition of Si and Mn elements closer to the virgin alloy whereas the Mg loss has been resulted in case of turning swarfs secondary alloy. The porosity size is found higher (20–1300 µm) in case of the secondary aluminium alloy (turning swarfs) compared to virgin and secondary alloy (blocky scrap). The hardness and tensile strength of the secondary aluminium alloy produced out of turning swarfs are found lower when compared to the properties of other two alloys which are attributed to the presence of larger porosity and the loss of magnesium element. Thus, the alloy is modified through addition of alloying elements and the mechanical properties are found improved which is attributed to the formation of strengthening compounds. Therefore, it is suggested to utilize the modified secondary aluminium alloy with better performance for the automotive components and other applications wherever high strength is necessary. Acknowledgements This research work was funded by the Department of Science of Technology (DST).

References 1. Miller, W.S., Zhuang, L., Bottema, J., Wittebrood, A.J., De Smet, P., Haszler, A., Vieregge, A.: Recent development in aluminium alloys for the automotive industry. Mater. Sci. Eng. A 280(1), 37–49 (2000) 2. Brungs, D.: Light weight design with light metal castings. Mater. Des. 18(4–6), 285–291 (1997) 3. Cui, J., Roven, H.J.: Recycling of automotive aluminium. Trans. Non-ferr. Metals Soc. China 20, 2057–2063 (2010) 4. Gutowski, T.G., Allwood, J.M., Herrmann. C.S., Sahni, A.: Global assessment of manufacturing: economic development, energy use, carbon emissions, and the potential for energy efficiency and materials recycling. Ann. Rev. Environ. Resour. 38, 81–106 (2013) 5. Liu, G., Bangs, C.E., Muller, D.B.: Stock dynamics and emission pathways of the global aluminium cycle. Nat. Climate Change 3, 338–342 (2013) 6. Ozer, G., Burgucu, S., Marsoglu, M.: A study on the recycling of aluminium alloy 7075 scrap. Mater. Test. 54(3), 175–178 (2012) 7. David, E., Kopac, J.: Use of separation and impurity removal methods to improve aluminium waste recycling process. Mater. Today Proc. 2, 5071–5079 (2015) 8. Logozar, K., Radonjic, G., Bastic, M.: Incorporation of reverse logistics model into in-plant recycling process: a case of aluminium industry. J. Resour. Conserv. Recycl. 49, 49–67 (2006) 9. Zhou, B., Yang, Y., Reuter, M.A., Boin, U.M.J.: Modelling of aluminium scrap melting in a rotary furnace. Miner. Eng. 19, 299–308 (2006) 10. Green, J.A.S.: Aluminum Recycling and Processing for Energy Conservation and Sustainability. Materials Park-ASM International (2007) 11. Ozer, G., Yuksel, C., Comert, Z.Y., Guler, K.A.: The effects of process parameters on the recycling efficiency of used aluminium beverage cans. Mater. Test. Recycl. Technol. 55(5), 396–400 (2013) 12. Das, K.S., Gren, J.A.S.: Aluminum industry and climate change—assessment and responses. J. Mater. 62(2), 27–31 (2010) 13. Tillova, E., Chalupova, M., Hurtalova, L.: Evolution of phases in a recycled Al-Si cast alloy during solution treatment. InTech 411 (2011) 14. Gronostajski, J., Marciniak, H., Matuszak, A.: New methods of aluminium and aluminiumalloy chips recycling. J. Mater. Process. Technol. 106, 34–39 (2000)

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15. Lazzaro, G., Atzori, C.: Recycling of aluminium trimmings by conform process. Light Metals 3, 1379–1384 (1992) 16. Gronostajski, J., Matuszak, A.: The recycling of metals by plastic deformation: an example of recycling of aluminium and its alloys chips. J. Mater. Process. Technol. 92–93, 35–41 (1999) 17. Samuel, M.: A new technique for recycling aluminium scrap. J. Mater. Process. Technol. 135, 117–124 (2003) 18. Fogagnolo, J.B., Ruiz-Navas, E.M., Simón, M.A., Martinez, M.A.: Recycling of aluminium alloy and aluminium matrix composite chips by pressing and hot extrusion. J. Mater. Process. Technol. 143–144, 792–795 (2003) 19. Shamsudina, S., Lajisb, M.A., Zhong, Z.W.: Evolutionary in solid state recycling techniques of aluminium: a review. Procedia CIRP 40, 256–261 (2016) 20. Wan, B., Chen, W., Lu, T., Liu, F., Jiang, Z., Mao, M.: Review of solid state recycling of aluminum chips. Resour. Conserv. Recycl. 125, 37–47 (2017) 21. Amini Mashhadi, H., Moloodi, A., Golestanipour, M., Karimi, E.Z.V.: Recycling of aluminium alloy turning scrap via cold pressing and melting with salt flux. J. Mater. Process. Technol. 209, 3138–3142 (2009) 22. Haase, M., Erman Tekkaya, A.: Recycling of aluminum chips by hot extrusion with subsequent cold extrusion. Procedia Eng. 81, 652–657 (2014) 23. Chiba, R., Yoshimura, M.: Solid-state recycling of aluminium alloy swarf into c-channel by hot extrusion. J. Manuf. Process. 17, 1–8 (2015) 24. Khamis, S.S., Lajis, M.A., Albert, R.A.O.: Sustainable direct recycling of aluminum chip (AA6061) in hot press forging employing response surface methodology. Procedia CIRP. 26, 477–481 (2015) 25. Zhao, L., Pan, Y., Liao, H., Wang, Q.: Degassing of aluminum alloys during re-melting. Mater. Lett. 66, 328–331 (2012) 26. Srivatsan, T.S., Guruprasad, G., Vesudevan, K.: The quasi static deformation and fracture behaviour of aluminum alloy 7150. Mater. Des. 29, 742–751 (2008) 27. Michna, S.: Aluminium materials and technologies from A to Z (2007) 28. Fayomi, O.S.I.., Popoola, A.P.I., Udoye, N.E.: Effect of alloying element on the integrity and functionality of aluminium-based alloy. InTech (2017) 29. Zvinys, J., Kandrotaite Janutiene, R., Meskys, J., Juzenas, K.: Investigation of thermo mechanical effect on structure and properties of aluminium alloy 6082. In: Scientific Proceedings IX International Congress on Machines, Technologies, Materials, vol. 2, pp. 13–16 (2012)

Chapter 7

Effect on Mechanical and Metallurgical Properties of Cryogenically Treated Material SS316 Jitendra Upadhyay, Anuj Bansal and Jagtar Singh

Abstract Mechanical components are subjected to wear during their functionality, which decreases the life of such components. The mechanical strength plays a major role for the same. Different heat treatments had been used to improve the mechanical strength of such components. In this paper, DCT (Deep cryogenic treatment) with post-tempering treatment was conducted on austenitic steel SS316 and its effect on mechanical as well as metallurgical properties was investigated through experimental testing’s. For post-tempering, two temperatures were selected (T1 : 350 °C and T2 : 250 °C). It was observed that the DCT samples with post-tempered treatment at T2 : 250 °C possess good tensile strength and hardness. The reason behind the same can be refinement of grains after DCT with tempered at T2 : 250 °C as seen from the microstructural analysis. Further, decrease in toughness was also observed for both the DCT samples. The conversion from austenitic grains to martensitic grains was also observed after DCT. Keywords DCT: deep cryogenic treatment · Tempering · SS316 · Austenitic

7.1 Introduction SS316 is austenitic grade of SS and widely used in many of the mechanical components. These mechanical components may be exposed to different wearing condition during their functionality like slurry erosion, dry abrasion and corrosion as observed by Patil et al. [1] which decreases the life span of such components. Liu et al. [2] have J. Upadhyay · A. Bansal (B) · J. Singh Department of Mechanical Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur 148106, India e-mail: [email protected] J. Upadhyay e-mail: [email protected] J. Singh e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 V. S. Sharma et al. (eds.), Manufacturing Engineering, Lecture Notes on Multidisciplinary Industrial Engineering, https://doi.org/10.1007/978-981-13-6287-3_7

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explained that erosion is one of the major modes of failure which cause fatal hazard to hydro-machinery component, for example, gas turbine oil and gas pipeline, and drilling platforms, etc. Touseef et al. [3] observed that main reason behind the wear is mechanical strength, i.e., tensile, toughness or hardness of SS316. Many researchers have worked on different processes like heat treatment to improve the mechanical as well as metallurgical properties of material [4]. On the other side, some researchers have used different thermal spray coatings like high velocity oxy fuel (HVOF), high velocity fuel sprayed (HVFS), etc. to improve the surface characteristics of the material and these coatings provide high wear resistance to the surface as compare to the base metal. Further some researchers have explained thermal sprayed cermet and metallic coatings are often used to resist severe wear in such diverse industrial applications as mining, mineral or pulp and paper processing, aerospace and automobile manufacturing, and power generation [5, 6]. But Molinari et al. [7] have found that deep cryogenic treatment (DCT) along with the tempering and quenching was giving better results for improving the mechanical properties like increment in hardness, toughness, tensile strength, etc. So, in the present study SS316 was taken as base material and effect of DCT on different tempering temperatures was investigated on different mechanical and metallurgical properties.

7.2 Experimental Procedure For finding out the metallurgical and mechanical characterizations of selected material test like microstructure analysis, Charpy impact, tensile and micro-hardness were performed for non-cryogenic, and cryogenic with post-tempering at two different temperatures T1 : 250 °C and T2 : 350 °C treated specimens.

7.2.1 Material Selection and Specimen Preparation As there are different types of material used in hydro-machineries, we have selected the SS316, which was purchased from Bhagyashali Metal, Mumbai. The chemical composition of the material was analyzed through spectroscopy test at Met-Lab Laboratory Service, Parsi Lane, Mumbai, to ensure the type of material. The chemical composition of the material is shown in Table 7.1.

Table 7.1 Chemical composition of the material (SS316) Elements Actual weight % Standard weight %

C

Si

Mn

P

S

Cr

Ni

Fe

0.07

0.95

1.89

0.041

0.03

17.78

11.55

Rest