Tab Article

Preface
Authors

Chapter 1 : Fundamentals of Industry 4.0

• 1.1 Introduction
• 1.2 Industry 4.0
• 1.3 RAMI 4.0 (Reference Architecture Model Industry 4.0)
• 1.4 Servitization
• 1.5 Product Service-System (PSS)
• References

Chapter 2 : SMARTness and Pervasive Computing

• 2.1 Pervasive Computing
• 2.2 Problems of Pervasive Computing
• 2.3 Proposed Infrastructure for Pervasive (Ubiquitous) Computing: UbiCloud
• 2.4 Applications of Pervasive Computing
• 2.5 Healthcare
• 2.6. Two Stages of Pervasive Computing Development
• 2.7. Impact of Pervasive Computing
• 2.8. Differences between Traditional Networking and Pervasive Computing
• 2.9. Typical Sensors needed in Pervasive Computing
• 2.10. Defining Smart Spaces
• 2.11. Attributes of Smart Spaces in Pervasive Computing
• 2.12. Pervasive Computing and Internet of Things (IoT)
• References

Chapter 3 : The Industry 4.0 Architecture and Cyber Physical Systems

• 3.1 Cyber-Physical Systems (CPS)
• 3.2 CPS 5C Level Architecture
• 3.3 Implementation of 5C CPS Architecture for Factories
• 3.4 Adaptive Clustering for Self-Aware Machine Analytics
• 3.5 Classic Applications of CPS
• 3.6 Classification of CPS in Context of "Industry 4.0"
• 3.7 Operational Technology (OT) and Information Technology (IT)
• 3.8 IT and OT Convergence – Two Worlds Converging in Industrial IoT
• 3.9 Data and Optimization Across the Value Chain: Benefits and IT, OT and Cyber-Physical Systems in "Smart Anything"
• 3.10 Industry 4.0 Principles: Horizontal and Vertical Integration
• 3.11 Basic Functions and Uses of CPS
• 3.12 Practical Example of a Cyber Physical Systems: The Self-Modifying Machine
• 3.13 Digital Platforms
• References

Chapter 4 : Cloud Computing, Data Sources and Data Centers

• 4.1 IT vs OT
• 4.2 CMMS, ERP, MES, EMS, PLM and other actors
• 4.3 Cloud Computing Taxonomies
• 4.4 Cloud Services
• 4.5.Data Repositories and Data Centers
• References

Chapter 5 : Big Data Analytics as Service Provider

• 5.1 Connection: Sensors and Networks
• 5.2 Content or Context
• 5.3 Data Sharing and Collaboration
• 5.4 Big Data Analytics
• 5.5 Descriptive Analytics
• 5.6 Diagnostic Analytics
• 5.7 Prescriptive Analytics
• 5.8 What Types of Data Analytics Do Companies Choose

Chapter 6 : IoT and the Need for Data Rationalization

• 6.1 Internet of Things (IoT)
• 6.2 Internet of Things Vision
• 6.3 Internet of Things (IoT) Frameworks
• 6.4 Architecture of Internet of Things (IoT)
• 6.5 Visualizing the Internet of Things (IoT)
• 6.6 Essential Technologies of the Internet of Things (IoT)
• 6.7 Key Technologies Involved in Internet of Things
• 6.8 Enablers of IoT
• 6.9 Why the Internet of Things is Important?
• 6.10 The IoT Is Transforming Industry and Society
• 6.11 Types of Services of IoT
• 6.12 Internet of Things (IoT) Applications
• 6.13 The Internet of Things Today
• 6.14 The Internet of Things Tomorrow
• 6.15 Internet of Things (IoT) Ecosystem
• References

Chapter 7 : OPERATOR 4.0

• 7.1 Augmented Reality for O&M
• 7.2 Wearable Devices
• 7.3 Wearables and Localization Devices
• 7.4 Intelligent Health and Safety Devices for Operators
• 7.5 Sensors used in Wearable Devices
• 7.6 Collaborative Robotics in Industry 4.0
• 7.7 Human Factors in Industry 4.0: Ergonomic and Psychological Issues and Challenges
• References

Chapter 8 : Cybersecurity and Risk

• 8.1 Cybersecurity in OT level
• 8.2 Cybersecurity in IT level
• 8.3 IT-OT Cybersecurity Convergence
• 8.4 Risks and threats of sharing data
• 8.5 Blockchains in cybersecurity

Chapter 9 : Industry 4.0 Across the Sectors

• 9.1 Introduction
• 9.2 Transportation 4.0: Multimodal Transportation Systems
• 9.3 Rail 4.0
• 9.4 Digital Transformation of Railways
• 9.5 Logistics 4.0 (Implications)
• References

Index