Smart Technologies for Improved Performance of Manufacturing Systems and Services (Advances in Intelligent Decision-Making, Systems Engineering, and Project Management)

✍ Scribed by Bikash Chandra Behera (editor), Bikash Ranjan Moharana (editor), Kamalakanta Muduli (editor), Islam (editor)

• Publisher: CRC Press
• Year: 2023
• Tongue: English
• Leaves: 211
• Edition: 1
• Category: Library

✦ Synopsis

This book discusses smart technologies and their influence in the field of manufacturing and industrial systems engineering, in the context of performability enhancement, and explores the development of the workforce for the execution of such smart and advanced technologies.

Smart Technologies for Improved Performance of Manufacturing Systems and Services discusses the integration of smart technology into the production process and supply chain to enhance the overall performance of manufacturing industries. As well as emphasizing the fundamentals of smart technologies, such as artificial intelligence, big data, and cyber-physical systems, it highlights the role that machine learning plays along with other smart technologies. Real-time case studies highlight the applications of smart digital technologies, and research insights into the area of performability and overall sustainable development round out the great range of discussions this reference book has to offer.

Managers and stakeholders seeking coverage on techniques and methods for integration into their organizations, as well as students and researchers in the field will find this book very useful.

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Editors
Contributors
Abbreviations
Chapter 1: Enhancement of Manufacturing Sector Performance with the Application of Industrial Internet of Things (IIoT)
1.1 Introduction
1.2 IIoT and It’s Need in Manufacturing
1.3 The Defining Characteristics of the IIoT in the Manufacturing Domain
1.4 Manufacturing IIoT Features
1.5 Major Applications of IIoT in Manufacturing Industries
1.6 Limitations
1.7 Future Scope
1.8 Conclusions
References
Chapter 2: Reliability Prediction Using Machine Learning Approach
2.1 Introduction
2.2 Problem Statement and Objectives
2.3 Literature Review
2.4 Methodology
2.5 Reliability Prediction Using ML
2.5.1 Algorithms Employed
2.5.2 Advantages of Employing ML in Reliability Prediction
2.5.3 Challenges Encountered by PNG Organizations in Implementing ML Based Maintenance Solutions
2.6 Implications of the Research
2.7 Recommendations
2.8 Conclusion
2.9 Limitations and Scope of Future Work
References
Chapter 3: Quality Control in the Era of IoT and Automation in the Context of Developing Nations
3.1 Introduction
3.1.1 Background
3.1.2 Problem Statement
3.2 Objectives
3.3 Proposed Solution Methodology
3.4 Literature Review
3.5 Methodology
3.6 Data Analysis
3.7 Findings and Observations
3.8 Discussion
3.9 Advantages and Disadvantages of IoT and Automation in Manufacturing
3.10 Importance of Adopting QC Processes in This Era of IoT and Automation
3.11 Implications
3.12 Recommendation
3.13 Conclusion
3.14 Limitation and Scope of Future Work
References
Chapter 4: Precision Positioning of Robotic Manipulators in Manufacturing Processes through PID Controller to Contribute towards Sustainability
4.1 Introduction
4.2 Sustainable Solutions for Industrial Robots
4.3 Mathematical Model of PID Controller
4.4 Experimental Results and Discussions
4.5 Conclusions and Future Scope of the Work
References
Chapter 5: Role of Additive Manufacturing in Industry 4.0
5.1 Introduction
5.1.1 First Industrial Revolution
5.1.2 Second Industrial Revolution
5.1.3 Third Industrial Revolution
5.1.4 Fourth Industrial Revolution (Industry 4.0)
5.2 Additive Manufacturing Role in Industry 4.0
5.3 Additive Manufacturing
5.4 Benefits of Additive Manufacturing in Industry 4.0
5.4.1 Produces Less Waste and Scraps
5.4.2 Decreases Prototyping Times and Costs
5.4.3 Business Digitalization
5.5 Industry 4.0 and AM for Maintenance and Safety: A Case Study
5.6 Obstacles to AM Integration in Manufacturing Systems in Industry 4.0
5.7 Future Prospective
5.8 Conclusions
References
Chapter 6: Challenges and Prospects of Welding 4.0 Adoption: Implication for Emerging Economics
6.1 Introduction
6.2 Welding 4.0
6.2.1 Automation
6.2.2 Big Data
6.2.3 Cloud Computing
6.2.4 Autonomous
6.2.5 Internet of Things
6.2.6 Data Analytics and Management
6.2.7 Weld Monitoring System for Quality Monitoring
6.2.8 Benefits of Weld Monitoring Techniques
6.2.9 Important Things Needed for Industry 4.0
6.3 General Issues and Limitations in Welding
6.3.1 Liquid-Phase Welding Method
6.3.1.1 Resistance Spot Welding
6.3.1.2 Arc Welding Method
6.3.1.3 Gas Metal Arc Welding
6.3.1.4 Gas Tungsten Arc Welding
6.3.1.5 Laser Welding
6.3.2 Solid State Welding Techniques
6.4 Monitoring and Controlling a Welding Process
6.5 Challenges to the Implementation of Welding 4.0
6.5.1 High Investment
6.5.2 Lack of Clarity Regarding Economic Benefit
6.5.3 Difficulties in Value-Chain Integration
6.5.4 Risk of Security Breaches
6.5.5 Poor Maturity Level of Preferred Technology
6.5.6 Inequality
6.5.7 Risk to Existing Employment
6.5.8 Lack of Proper Regulations, Standards, and Certification
6.5.9 Lack of Infrastructure
6.5.10 Lack of Digital Skills
6.5.11 Challenges in Ensuring Data Quality
6.5.12 Lack of Digital Culture and Training
6.5.13 Resistance to Change
6.5.14 Ineffective Change Management
6.5.15 Lack of Strategy and Resource Scarcity for Digitization
6.6 Summary
References
Chapter 7: An Approach to Friction Stir Additive Manufacturing of Light Weight Metal Alloys
7.1 Introduction
7.2 Origin of Friction Stir Additive Manufacturing (FSAM)
7.2.1 Parameters Affecting FSAM
7.2.2 Types of FSAM Process
7.2.3 Different Zones in a FSAM Process
7.3 Material Compatibility with FSAM Process
7.3.1 Magnesium Alloys
7.3.2 Aluminum Alloys
7.4 Microstructural Analysis of Magnesium Alloys Produced by FSAM
7.5 Mechanical Properties of Magnesium Alloys Produced by FSAM
7.5.1 Hardness Analysis
7.5.2 Tensile Strength Analysis
7.6 Conclusions
References
Chapter 8: Analysis and Improvement Performance of Manufacturing in Friction Stir Welding
8.1 Introduction
8.2 Materials and Method
8.2.1 Procedure of Specimen
8.3 Tensile and Charpy Strength Comparison
8.4 ANOVA Analysis
8.5 Microstructure Analysis
8.6 Optimization of Fuzzy TOPSIS Method
8.7 Conclusion
References
Chapter 9: Multi-Response Optimization of Process Parameters in Friction Stir Additive Manufacturing of Magnesium Alloy
9.1 Introduction
9.2 Experimental Details
9.3 Taguchi Grey Relational Analysis Process
9.4 Result and Discussion
9.4.1 Calculation with Taguchi Gray Relational Analysis (GRA)
9.4.2 Getting Optimal Parameters with the Help of Taguchi GRA
9.5 Conclusion
References
Chapter 10: Ultrasonic Welding for Light-Weight Structural Applications: An Industry Perspective
10.1 Introduction
10.2 Ultrasonic Welding Process
10.3 Disruptive Technologies
10.4 Industry Challenges
10.5 Results and Discussion
10.5.1 Mechanical Performance
10.5.1.1 Tensile Shear Strength
10.5.1.2 Micro-Hardness
10.5.1.3 Fracture Surface Morphology
10.5.2 Microstructural Analysis
10.5.2.1 SEM and EDS Analysis
10.5.2.2 XRD and TEM Analysis
10.6 Conclusions
References
Chapter 11: Supervised Machine Learning Algorithms for Machinability Assessment of Graphene Reinforced Aluminium Metal Matrix Composites
11.1 Introduction
11.2 Methodology and Results
11.3 Implementation of ML
11.4 Discussion of the Results
11.5 Conclusion
References
Chapter 12: Focused Ion Beam Machining as a Technology for Long Term Sustainability
12.1 Introduction
12.2 Basic FIB Equipment
12.2.1 Principle
12.2.2 Process Parameters in FIB Process
12.3 Multi-process Capability of FIB
12.3.1 FIB Etching
12.3.2 Gas Assisted FIB Deposition
12.3.3 For Transfer of Sensitive Samples
12.3.4 FIB Tomography
12.4 Applications of FIB System
12.5 Summary
References
Index