Industry 4.0 in Small and Medium-Sized Enterprises (SMEs): Opportunities, Challenges, and Solutions

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
Chapter 1 Industry 4.0: An Introduction in the Context of SMEs
1.1 Introduction
1.2 Digital Manufacturing
1.3 Components of Industry 4.0
1.3.1 Connectivity of Sensors
1.3.2 Data Storage and Cloud
1.3.3 Augmented Reality
1.3.4 Artificial Intelligence for Departments
1.3.5 Cybersecurity
1.3.6 Digital Twin in Smart Factories
1.4 IIoT in Industry 4.0
1.5 Smart Factories
1.5.1 Deep Learning
1.5.2 Radio-frequency Identification
1.5.3 Data Mining
1.5.4 Cloud Computing
1.6 Challenges and Opportunities
1.6.1 Implementation Challenges
1.6.1.1 Need for Technology Maturity
1.6.1.2 Insufficient Technology to Integrate with Manufacturing Systems
1.6.1.3 Difficulty in the Reconfiguration of Production Systems
1.6.2 Challenges for Data
1.6.2.1 Unstructured Format of Data
1.6.2.2 Management of Huge Data for Storage and Processing
1.6.2.3 Quality of Data
1.6.3 Skilled Workforce
1.6.4 Security Challenges
1.6.4.1 Sharing Data with Stockholders
1.6.4.2 Connectivity Protocols
1.6.5 Difficulty in Altering the Manufacturing Set-Up
1.6.6 Standardising the Process
1.6.7 Financial Challenges
1.6.8 Implementation Difficulties at Managerial Level
1.6.9 Environmental Challenges
1.7 Opportunities in Implementation of Industry 4.0
1.8 Conclusion
References
Chapter 2 Indian SMEs – Opportunities and Challenges: Assessing Industry 4.0 Readiness
2.1 Introduction
2.2 Challenges Faced by SMEs
2.3 Industry 4.0
2.4 Research Instrument and Survey
2.4.1 Research Instrument
2.4.2 Conduct of Survey
2.5 Analysis
2.5.1 CV: Coefficient of Variation
2.5.2 Technology Index
2.5.3 Causality
2.6 Results, Discussions, and Managerial Implications
2.7 Conclusions
References
Chapter 3 Paradigm Shift in Construction Processes with Industry 4.0
3.1 Introduction
3.1.1 Rationale
3.1.2 State-of-the-Art Industry 4.0 in Construction Safety
3.2 Representatives of Industry 4.0 in Construction Safety
3.3 Conventional Safety Practices in Construction
3.3.1 General Safety Management Framework
3.4 Data-Driven Safety Management: A Conceptual Framework
3.4.1 Proposed Framework for Proactive Safety Management
3.4.2 Interaction of Cyber-Physical System Elements in Proactive Safety Management Framework
3.4.2.1 Cyber-Physical System Interaction in Pre-Construction Stage
3.4.2.2 Cyber-Physical System Interaction in Construction Stage
3.5 Discussion
References
Chapter 4 Machinery Fault Detection using Artificial Intelligence in Industry 4.0
4.1 The Era of Industry 4.0
4.1.1 Sustainable Smart Manufacturing under Industry 4.0
4.1.2 Introduction and Evolution of Predictive Maintenance
4.2 Artificial Intelligence–Empowered Predictive Maintenance
4.2.1 Predictive Maintenance Framework
4.2.2 Literature Survey: Fault Detection and Diagnosis
4.3 Case Study on Fault Detection in Bearing Machinery
4.3.1 Data Set Description
4.3.2 Algorithm Description
4.3.3 Methodology
4.3.4 Results and Analysis
4.3.4.1 Data Visualisation
4.3.4.2 Model Application
4.3.4.3 Performance Evaluation
4.4 Future Directions
4.5 Conclusions
Acknowledgement
References
Chapter 5 A Multi-Agent Reinforcement Learning Approach for Spatiotemporal Sensing Application in Precision Agriculture
5.1 Introduction: Background and Driving Forces
5.2 System Model
5.2.1 Markov Decision Process and Reinforcement Learning
5.2.2 Multi-Agent Reinforcement Learning
5.3 A MARL-Based Area Coverage Method
5.3.1 Problem Description
5.4 A MARL-Based Area Coverage Approach with Inter-Agent Negotiation
5.4.1 Markov Game Model
5.4.2 Learning for Equilibrium Computation
5.4.3 A Numerical Simulation
5.5 Concluding Remarks
References
Chapter 6 Digital Twin of a Laboratory Gas Turbine Engine Using Deep Learning Framework
6.1 Introduction
6.1.1 Literature
6.1.2 Contributions
6.2 Deep Neural Network
6.2.1 Architecture of LSTM Network
6.3 System Description and Problem Formulation
6.4 Digital Twin of Laboratory GTE
6.4.1 Data Collection
6.4.2 Data Pre-Processing
6.4.3 Configuration of Network
6.4.4 Training Progress
6.4.5 Testing and Deployment
6.5 Results and Discussion
6.5.1 Model Validation on Testing Data Set
6.5.2 LSTM Network Validation against NARX Network
6.5.3 LSTM Model Validation against a First Principle–Based Mathematical Model
6.6 Conclusions
Appendix 6A
6A.1 NARX Neural Network Architecture
6A.2 First Principle–Based Mathematical Model of Laboratory GTE
References
Chapter 7 A Case Study of Additive Manufacturing in Prosthesis Development in Industry 4.0
7.1 Introduction
7.2 Prosthetic Legs
7.3 Treatment Timeline
7.4 General Prescription Guidelines
7.5 Literature Review
7.6 Raw Materials Used
7.7 Prosth esis by Additive Manufacturing over Conventional Methods
7.8 Fused Deposition Modelling
7.9 Case Study
7.9.1 Development of Specification for Prosthetic Limb
7.9.2 Finite Element Analysis of Pylon
7.10 Conclusions
References
Chapter 8 Technology Gap Analysis with Respect to Mysore Printing Cluster: An Attractive Opportunity in Industry 4.0 Market
8.1 Introduction
8.1.1 Mysore Printers Cluster
8.1.2 Aim
8.1.3 Objectives
8.1.4 Methodology
8.1.5 Vision
8.2 Mysore City
8.3 Printing Technologies
8.3.1 Introduction to Different Printing Technologies
8.3.1.1 Process Flow of Flexography
8.3.1.2 Pre-Press, Plate-Making, Handling, and Storage
8.4 Technology Gaps
8.5 Suggested Remedial Measures and Recommendations with a View to Creating an Attractive Opportunity in Industry 4.0 Market
8.5.1 Action Plan
8.6 Conclusion
Acknowledgement
References
Chapter 9 Intelligent Machining
9.1 Introduction
9.2 Machine Tools
9.2.1 Evolution
9.2.2 New Generation AI
9.2.3 New Generation AI-Based Intelligent Machine Tool
9.3 Cutting Tools
9.3.1 Real-Time Tool Condition Monitoring
9.4 Techniques
9.4.1 Artificial Neural Network (ANN)
9.4.2 Fuzzy Sets
9.5 Development Trends in Intelligent Machining
9.6 Summary
References
Chapter 10 Digital Market Scenario in India: A Case Study on “Unicorn” Indian Digital Start-Ups
10.1 Introduction: Understanding Digital Economy
10.2 Objectives and Methods
10.3 Digital Economy of India
10.4 Make in India Initiative (2014)
10.5 Digital India Campaign (2015)
10.6 Start-up India (2015)
10.7 Atmanirbhar Bharat (2020)
10.8 Unicorns
10.9 Conclusion and Discussion
References
Chapter 11 Skill Requirement in Industry 4.0
11.1 Introduction
11.2 Expected Changes in Industry 4.0
11.3 Factors Shaping Industry 4.0
11.4 How will Future Tasks Differ?
11.5 What Skills Are Required in Industry 4.0?
11.5.1 Technical Skills
11.5.2 Methodological Skills
11.5.3 Social Skills
11.5.4 Personal Skills
11.6 Conclusion
References
Annexure A
Other sources
Industry 4.0: Required Personnel Competences
Transformation of the Machines from Learner to Decision Maker: Industry 4.0 and Big Data
Chapter 12 The Changing Role of Academics from the Perspective of Educational Transformation in Education 4.0
12.1 Introduction: Background and Driving Forces
12.2 The Fourth Industrial Revolution and Education: Education 4.0
12.3 Higher Education and the Changing Role of Academics in Education 4.0
References
Index