Automation in the Welding Industry: Incorporating Artificial Intelligence, Machine Learning and Other Technologies (Industry 5.0 Transformation Applications)

Cover Title Page Copyright Page Dedication Page Contents Preface Acknowledgments Chapter 1 Introduction to Industry 5.0 1.1 Introduction 1.2 Industry 4.0 1.3 Industry 5.0 References Chapter 2 Advancements in Welding Technologies 2.1 Introduction 2.2 Quality of Weld Joint 2.3 Pulsed Current GMAW 2.4 P-GMAW Process Stability Factors 2.5 Suitable Pulse Parameters of Selection 2.6 Effect of Pulse Parameters 2.6.1 Weld Bead Geometry 2.6.2 Weld Dilution 2.6.3 Weld Microstructure 2.7 Pulsed Current GMAW Advances 2.8 Double-Pulsed GMAW 2.9 Synergic Control 2.10 Self-Regulating Control 2.11 Microcomputer Control 2.12 GMAW Shielding Gas Flow 2.13 Particle Image Velocimetry (PIV) 2.14 The Measurement of Oxygen (O2) Concentration 2.15 Spectroscopic Measurements of Plasma Temperature 2.16 P-GMAW Numeric Simulation 2.16.1 Approach-1 2.16.2 Approach-II References Chapter 3 Automation in Welding Industries 3.1 Introduction 3.1.1 Types of Automatic Welding 3.1.2 Challenges of Automatic Welding 3.1.3 Benefits of Automatic Welding 3.2 Automation Trends 3.2.1 Production Monitoring 3.2.2 Adaptive Welding Advancements 3.2.3 Upstream Practices 3.2.4 Collaborative Technology 3.2.5 Easier Programming of Automation Systems 3.3 Plasma Welding 3.4 Laser Welding 3.5 Arc Welding 3.6 MIG Welding 3.7 Resistance Welding 3.8 Conclusions References Chapter 4 Digitalization of Welding Processes 4.1 Introduction 4.2 Techniques for Process Monitoring 4.2.1 Electrical Process Tests: Voltage and Current for Welding 4.2.2 Thermal Measurement 4.2.3 Optical Measurement 4.2.4 Acoustic Measurement 4.2.5 Measurement of Displacement and Velocity 4.2.6 Measurement of Force 4.3 Process Monitoring Applications 4.3.1 Measurement of Current and Voltage 4.3.2 Thermal Measurement 4.3.3 Optical Measurement 4.3.4 Acoustic Measurement 4.3.5 Displacement and Velocity Measurement 4.3.6 Measurement of Force 4.3.7 EMF Measurement 4.4 Future Directions References Chapter 5 AI and ML in Welding Technologies Nomenclature 5.1 Introduction 5.2 Enhancing the Welding Industry 5.3 Machine Learning Algorithm Types 5.4 Background of AI and ML 5.5 Weld Defects 5.6 Level of Weld Quality 5.6.1 Mining Industry 5.6.2 Challenges in ML Practice 5.7 Case Studies 5.7.1 Use of AI Programs to Obtain CCT Welding Diagrams 5.7.2 Use of Algorithms to Predict the Penetration Depth in Friction Stir Spot Welding 5.8 Feasibility of Online Inspection of Ultrasonic Weld Quality 5.9 Conclusions References Chapter 6 Digital Twin in Welding 6.1 Introduction 6.2 Friction Stir Welding 6.2.1 FSW Parameters 6.3 Defects in Friction Stir Welding 6.3.1 DT for FSW 6.4 Laser Welding 6.4.1 Heat Conduction Welding 6.4.2 Deep Penetration or Keyhole Welding 6.4.3 Weld Process Parameters 6.4.3 DT for Laser Welding 6.5 Summary References Chapter 7 IoT in Welding Industries 7.1 Introduction 7.2 Sensing and Analyzing Welding Data via the Internet of Things (IoT) 7.2.1 Electrical Information 7.2.2 Optical Information 7.3 Welding Manufacture Based on IoT 7.3.1 Example 1: Arc Quality Management with IoT 7.3.2 Example 2: Case Study on IoT-Enabled Molten Metal Temperature Sensing System for Welding 7.3.3 Example 3: IoT-Based Safety Monitoring System During Welding Operations 7.3.4 Example 4: IoT-Based Monitoring of Submerged Arc Welding Process 7.4 Conclusion References Chapter 8 VR and AR in Welding Technologies 8.1 Introduction 8.1.1 Virtual Reality (VR) 8.1.2 Augmented Reality (AR) 8.1.3 Artificial Intelligence (AI) 8.1.4 Machine Learning (ML) 8.2 How Intelligent is AI When Coupled with VR/AR? 8.3 VR/AR Architecture 8.4 Welding Processes 8.5 Intelligent Welding Technology 8.6 Types of Intelligent Welding Processes 8.6.1 Types of Welding Positions 8.7 Automated Welding Examples 8.7.1 Computer Interface of Automated Welding Processes 8.8 Applications of VR and AR in Automated Welding 8.9 AI and ML for Visual Inspection of Welds 8.9.1 AI in Arc Welding 8.9.2 AI Detection of Welding Defects 8.9.3 VR/AR Welding Simulator 8.10 Limitations in the Existing State-of-the-Art Welding Techniques 8.10.1 Advantages of AR/VR 8.11 Conclusions References Chapter 9 Intelligent, Clean Cobot Arc Welding Cell 9.1 Chances for SMEs 9.1.1 Introduction and Goals 9.2 Parameters and Consumption Data 9.3 CO2 Footprint Methodology 9.4 Result Presentation 9.5 Conclusion Acknowledgments References Chapter 10 Welding-Based 3D, 4D, 5D Printing Nomenclature 10.1 Introduction 10.2 Differences Among 3DP, 4DP and 5DP 10.3 Materials Used in 3DP, 4DP and 5DP Processes 10.3.1 Additive Manufactured Metallic Components 10.4 Machinability of Welded Components 10.5 Concept of 4D and 5D Printing 10.6 FEM-Based Analysis 10.7 Applications 10.7.1 4D Printing Applications 10.7.2 3D Printing in the Aerospace Industry 10.7.3 3D Printing in Electronics 10.7.4 3D Printing in Electrochemical Industries 10.7.5 5D Printing in Dentistry 10.7.6 5D Printing in Orthopedics 10.8 Conclusions References Chapter 11 Welding and Joining of Novel Materials 11.1 Introduction 11.1.1 Concept of High Entropy Alloys (HEAs) 11.2 Core Effects 11.2.1 High Entropy Effect 11.2.2 Sluggish Diffusion Effect 11.2.3 Severe Lattice Distortion Effect 11.2.4 Cocktail Effect 11.2.5 Current Status of HEAs 11.3 Arc Welding Techniques for HEAs 11.4 Solid State Welding 11.4.1 Friction Stir Welding (FSW) 11.5 Explosive Welding 11.5.1 Soldering and Brazing 11.6 EBW and EBC of HEAs 11.7 Laser Welding of HEAs 11.8 Laser Cladding of HEAs 11.9 Conclusion and Summary References Chapter 12 Sustainability in Welding Industries 12.1 Introduction 12.2 Critical Factors for Sustainability of Welding 12.3 Adoptability of Sustainable Welding 12.4 New Welding Standards for Sustainability 12.5 Resource-Conserving Techniques 12.5.1 Sustainable Welding in Practice 12.5.2 Boosting Efficiency with Special Welding Processes 12.6 Sustainability in Welding Training 12.6.1 Sustainable Technologies for Thick Metal Plate Welding 12.7 5S Lean Strategy for a Sustainable Welding Process 12.7.1 Sustainability Assessment of Shielded Metal Arc Welding (SMAW) Process 12.8 A-TIG Welding: A Small Step Towards Sustainable Manufacturing 12.8.1 Weight Space Partitions-Based Sustainable Welding 12.8.2 Sustainability Assessment of Welding Processes 12.8.3 Sustainability in Manufacturing 12.9 Sustainability Indices 12.10 Conclusion References Chapter 13 Global Welding Market Growth 13.1 Introduction 13.1.1 Overview of Global Welding Products Market 13.2 Patrons of Global Welding Market 13.3 Welding Technologies in the Global Welding Market 13.4 Fluxes, Wires, Electrodes, and Fillers 13.5 Welding Market Dynamics 13.6 Manpower and Labor Challenges in Global Market 13.7 COVID-19’s Impact on Global Welding Materials Market 13.8 New Opportunity in the Welding Market and Advanced Applications 13.9 Conclusions References Chapter 14 Quality Assurance and Control in Welding and Additive Manufacturing 14.1 Introduction 14.2 Quality Issues in Welding 14.3 Quality Issues in 3D Printing 14.4 Conclusion References Chapter 15 Welding Practices in Industry 5.0: Opportunities, Challenges, and Applications 15.1 Introduction 15.2 Manufacturing Trends 15.3 Welding Technology 15.3.1 Classification of Welding 15.4 Variety of Materials Used by Welding for Industry 5.0 15.4.1 Advantages of Welding 15.4.2 Applications 15.4.3 Automation 15.4.4 Welding-Based AM 15.4.5 Welding Trends in Aeronautic Industry 15.4.6 Robotic and Automated Welding 15.5 Virtual Reality (VR) for Welders 15.6 Challenges and Opportunities in Nuclear Reactor 15.7 Challenges of AM-Based Functionally Graded Materials Through LDED 15.8 Conclusion References Index EULA