INVESTIGATING THE EFFECT OF CRYO TREATED TOOL AND WORK MATERIAL IN ULTRASONIC MACHINING OF TITANIUM ALLOYS. A THESIS Submitted in fulfillment of the requirements for the award of the degree of DOCTOR OF PHILOSOPHY in MECHANICAL ENGINEERING By GAURAV KUMAR DHURIA Registration. No. 950808008 THAPAR INSTITUTE OF ENGINEERING & TECHNOLOGY (Deemed to be University) PATIALA-147004, INDIA i PREFACE This research work was carried out by the author under the guidance of Dr. Ajay Batish, Professor, Department of Mechanical Engineering, Thapar University, Patiala and Dr. Rupinder Singh, Professor, Department of Production Engineering, Guru Nanak Dev Engineering College, Ludhiana. The experimentation for the presented work was carried out on Ti-6Al-4V titanium alloy to explore the effect of six process parameters on machining response variables such as material removal rate, tool wear rate, surface roughness and dimensional accuracy. Sonic Mill 500W Ultrasonic Machine Tool available in the Mechanical Engineering Department at Thapar University, Patiala was used for experimentation. Following articles have been published from the presented work: 1. Gaurav Kumar Dhuria, Rupinder Singh, Ajay Batish (2016) Predictive modeling of surface roughness in ultrasonic machining of cryogenic treated Ti-6Al-4V. Engineering Computations, 33 (8) 2377 – 2394 (SCIE - Impact Factor 0.691). 2. Gaurav Kumar Dhuria, Rupinder Singh, Ajay Batish,(2016) Application of a hybrid Taguchi-entropy weight-based GRA method to optimize and neural network approach to predict the machining responses in ultrasonic machining of Ti–6Al–4V. J Braz. Soc. Mech. Sci. Eng., 39 (7) 2619-2634 (SCIE – Impact Factor 0.963). 3. Rupinder Singh, Gaurav Kumar Dhuria, Ajay Batish (2017) Effect of Cryogenic Treatment on Ultrasonic Machining of Titanium and Its Alloys: A Review, Reference Module in Materials Science and Materials Engineering, http://dx.doi.org/10.1016/B978-0-12-803581-8.04157-6. 4. Gaurav Kumar Dhuria, Rupinder Singh, Ajay Batish (2016) Process capability study in ultrasonic drilling of Ti-6Al-4. Proc. of Internatonal Conference on Production and Industrial Engineering, Dec 19-21, 2016 NIT Jalandhar. 5. Gaurav Kumar Dhuria, Rupinder Singh, Ajay Batish (2011) Ultrasonic machining of titanium and its alloys: a state of art review and future prospective. Int. J. of Machining and Machinability of Materials, 10 (4) 326 – 355. ii iii ACKNOWLEDGEMENT I take this opportunity to express my sincere, heartfelt gratitude and adulation to my supervisors Dr. Ajay Batish, Professor, Department of Mechanical Engineering and Dean, Partnerships and Accreditation, Thapar University, Patiala and Dr. Rupinder Singh, Professor, Department of Production Engineering and Dean, Academics, Guru Nanak Dev Engineering College, Ludhiana for their invaluable guidance, persistent inspiration and immense cooperation in accomplishing the present work. The work would not have been possible without their constant motivation, constructive suggestions and thought provoking discussions. In the times of adversities they were always there to uplift the morale and ensured my focus on the target. It has been a blessing to work under their mentoring and I thank the Almighty for providing me the opportunity for the same. No work is possible without the blessings of parents and I am lucky to have such affectionate and caring revered parents who motivated and showered their unconditional love and blessings that were instrumental in completion of the work. I express my sincere gratitude to Prof. Prakash Gopalan, Director, Thapar University, Patiala, for providing the required institutional and infrastructure facilities and supporting the work. I am extremely thankful to Dr. O. P. Pandey, Dean, Research and Sponsored Projects, Thapar University, Patiala, Dr. S. K. Mohapatra, Head, Mechanical Engineering Department, Dr. Vinod Kumar, Associate Prof., Mechanical Engineering Department and Dr. Tarun Nanda, Ph. D. Coordinator for their continuous encouragement, invaluable suggestions and kind support during the course of the work. I am highly indebted to Dr. Manoj Kumar, Principal, DAVIET, Jalandhar for his continuous support at the work place. I am extremely grateful to Prof. C. L. Kochher, former Director, DAVIET, Jalandhar for inspiring and supporting me to complete the work. I express my sincere gratitude to Sh. Narinder Singh and Sh. Sukhbir Singh, Mechanical Engineering Department, Thapar University for their cooperation and assistance during the work. I am also thankful to Sh. Trilok Singh, Retd. Lab Superintendent, Thapar University Patiala, for his technical inputs. I take this opportunity to express my profound gratitude to Sh. Riyaz Amin, Proprietor, Cryonet, Surat, Mr. Nitin Joshi, Bhukhanwala Industries Pvt. Ltd., Mumbai, Mr. H.S.K. Alva, Manager, Snam Abrasives, Hosur, Mr. Vivek Aggarwal, Krishna Micro Abrasives for material and processing support to accomplish the work. I am extremely indebted to Mr. Charlie Wilhite, Mr. Clyde Treadwell and Mr. Bill Brenn from Sonic Mill, Albuquerque for their technical advice and support during the work. iv The work would have been very difficult without the technical support and guidance of my friend Sh. M. R. Sallan, Assistant Director, CIHT, Jalandhar. I also express my heartfelt gratitude to Sh. Bachittar Singh for technical advice and support. A special mention and admiration needs to be made of my wife Mrs. Puja Dhuria for her continuous inspiration and unconditional support that enabled me complete the work. Our new born, Vardaan, has been the best gift of the Almighty and I am thankful to the mother and the baby for their support and understanding. I am extremely grateful to my sister Mrs. Suman Girdhar and brother-in-law Dr. Akshay Girdhar for their immense support and for inspiring and motivating me to complete the work. I want to express my sincere thanks to all those who directly or indirectly helped me during the course of research work. Above all, I bow before the Almighty God, whole heartedly thanking and expressing my indebtedness for all His blessings, kindness and for not letting me down at the time of crisis. (Gaurav Kumar Dhuria) v CONTENTS DESCRIPTION PAGE No. Preface ii Certificate iii Acknowledgement iv Contents vi List of Figures ix List of Tables xiii Abbreviations xv Abstract xvi CHAPTER – 1 INTRODUCTION 1 1.1 Classification of non-traditional Processes 2 1.2 Ultrasonic Machining (USM) 4 1.3 Elements of Ultrasonic Machine Tool 8 1.3.1 Ultrasonic Power Supply (USM Generator) 8 1.3.2 Ultrasonic Transducer 9 1.3.3 Mechanical Amplifier 10 1.3.4 Tool and Abrasives 12 1.4 USM Process Parameters 12 1.5 Material Removal Mechanism in USM 13 1.6 Titanium and its alloys 16 1.7 Cryogenic Treatment and its effect 18 1.8 Objectives and issues of the present study 22 1.9 Scope of the work 23 1.10 Overall methodology of the study 24 1.11 Organization of thesis 25 vi CHAPTER – 2 LITERATURE REVIEW 28 2.1 Machining of Titanium and challenges 28 2.2 Ultrasonic Machining and its variants for machining Titanium 32 2.3 Ultrasonic Machining of other materials 37 2.4 Cryogenic Treatment 42 2.5 Summary and gaps in literature review 47 CHAPTER – 3 DESIGN OF STUDY 50 3.1 Pilot Experimentation 51 3.1.1 Results of Pilot Experimentation 54 3.2 Taguchi Method and steps in implementation 61 3.2.1 Statement of intent of study 63 3.2.2 Objectives 63 3.2.3 Selection of Orthogonal Array 65 3.2.4 Analysis and Interpretation of Results 66 3.2.5 Signal to Noise Ratio 67 3.2.6 Confirmatory Experiment 68 3.3 Selection of input process parameters for final Design of Experimentation 68 3.4 Selection of Orthogonal Array 71 CHAPTER – 4 EXPERIMENTATION, RESULTS AND DISCUSSION 73 4.1 Machine Tool, Material and Measurement 73 4.1.1 Machine Tool 73 4.1.2 Work and Tool Material 74 4.1.3 Cryogenic Treatment 75 4.1.4 Abrasive Slurry 75 4.1.5 Measurements 76 4.2 Experimentation 78 4.3 Material Removal Rate (MRR) 90 vii 4.4 Tool Wear Rate (TWR) 98 4.5 Surface Roughness (SR) 104 4.6 Dimensional Accuracy (Hole Oversize) 111 4.7 Tolerance Grades 117 CHAPTER – 5 MODELLING OF RESPONSE VARIABLES 119 5.1 Artificial Neural Network modelling 120 5.1.1 Mathematical model of a neuron 122 5.1.2 Network Architecture 123 5.1.3 Learning Paradigms 123 5.2 Modelling of response variables using ANN 123 5.2.1 Modelling for Surface Roughness 125 5.2.2 Modelling of MRR 129 5.2.3 Modelling of TWR 134 5.2.4 Modelling of HOS 138 CHAPTER – 6 OPTIMIZATION OF RESPONSE VARIABLES 143 6.1 Entropy based Grey Relational Analysis to optimize MRR and TWR 144 6.1.1 Calculation of Entropy based Grey Relational Grade 144 6.2 Use of Analytical Hierarchical Process for optimization 149 6.2.1 Application of AHP to the current problem 153 6.2.2 Sample Calculation to determine the global weight of MRR corresponding to untreated tool material: 162 6.2.3 Results of Optimization using AHP 166 CHAPTER – 7 CONCLUSIONS AND RECOMMENDATIONS 167 7.1 Conclusions 167 7.2 Scope for future work 170 REFERENCES 171 viii LIST OF FIGURES Figure 1.1 Basic elements of ultrasonic machining 6 Figure 1.2 Comparison of (a) burr type’s samples at drill exit and (b) drill skidding samples at drill entrance in conventional and ultrasonic assisted drilling of Inconel 738 7 Figure 1.3 Longitudinal wave in acoustic system 11 Figure 1.4 Amplifying tool holders, and mechanically attached tools for USM 11 Figure 1.5 USM Process Parameters related to Machine, Workpiece, Tool and Abrasive Slurry 14 Figure 1.6 Material removal Mechanism in USM 15 Figure 1.7 Cryogenic Treatment