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Manufacturing from Industry 4.0 to Industry 5.0 : advances and applications /

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Manufacturing from Industry 4.0 to Industry 5.0: Advances and Applications unfolds establishing three main pillars: (i) it investigates the theoretical background of the current industrial practice within the framework of industry 4.0 by presenting its key definitions and backbone technologies; (ii)...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Mourtzis, Dimitris
Format: eBook
Language:English
Published: Amsterdam : Elsevier, 2024.
Subjects:
Industry 4.0.
Manufacturing processes > Technological innovations.
Industrie 4.0.
Fabrication > Innovations.
TECHNOLOGY & ENGINEERING / Manufacturing.
TECHNOLOGY & ENGINEERING / Robotics.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • Manufacturing from Industry 4.0 to Industry 5.0
  • Copyright Page
  • Contents
  • List of contributors
  • Preface
  • I. From Industry 4.0 to Industry 5.0: definition, technological enablers, and comparison
  • 1 Introduction
  • 1.1 Comparison with Industry 4.0
  • 1.2 Challenges
  • 1.3 Structure of the book
  • 1.3.1 Part I: From Industry 4.0 to Industry 5.0: definition, technological enablers, and comparison
  • 1.3.2 Part II: Industry 5.0: human-centric, resilient, and sustainable manufacturing
  • 1.3.3 Part III: Integration of Industry 4.0 technologies in modern production and manufacturing networks toward Industry 5.0
  • 1.3.4 Part IV: Outlook, trends, and future directions toward Industry 5.0
  • References
  • 2 Industry 4.0 and smart manufacturing
  • 2.1 Introduction
  • 2.1.1 Evolution of manufacturing paradigms
  • 2.1.2 Market needs and challenges
  • 2.2 Industry 4.0
  • 2.2.1 Technological pillars of Industry 4.0
  • 2.2.2 RAMI 4.0 reference architecture
  • 2.2.3 Industrial Internet Reference Architecture
  • 2.2.4 The Open Group Architecture Framework
  • 2.2.5 ISO/IEC/IEEE 42010:2011
  • 2.2.6 IEC 62443
  • 2.2.7 NIST Cloud Computing Reference Architecture
  • 2.2.8 IBM Industry 4.0 reference architecture
  • 2.2.9 Draft ISO IoT reference architecture
  • 2.2.10 Maturity stages of Industry 4.0
  • 2.2.11 Automation pyramid for cyber-physical systems
  • 2.3 Smart manufacturing principles
  • 2.3.1 Smart factory
  • 2.3.2 Communication protocols
  • 2.3.3 Cloud manufacturing
  • 2.3.3.1 Software as a service
  • 2.3.3.2 Platform as a service
  • 2.3.3.3 Infrastructure as a service
  • 2.4 Digital manufacturing
  • 2.4.1 Big Data
  • 2.4.1.1 The 7V's of Big Data
  • 2.4.1.1.1 Volume
  • 2.4.1.1.2 Velocity
  • 2.4.1.1.3 Variety
  • 2.4.1.1.4 Veracity
  • 2.4.1.1.5 Value
  • 2.4.1.1.6 Value (content of data).
  • 2.4.1.2 Big Data analytics-as-a-service intelligence platform
  • 2.4.2 5G technology and maintenance 4.0
  • 2.4.3 Artificial intelligence
  • 2.5 Discussion and outlook
  • 2.6 Conclusions
  • References
  • 3 Industry 5.0: perspectives, concepts, and technologies
  • 3.1 Introduction
  • 3.2 Related work
  • 3.2.1 What is Industry 5.0
  • 3.2.2 Core values of Industry 5.0
  • 3.2.2.1 Human-centricity
  • 3.2.2.2 Sustainability
  • 3.2.2.3 Resiliency
  • 3.2.3 Composition of Industry 5.0
  • 3.2.3.1 Collaborative intelligence
  • 3.2.3.2 Business model transformation
  • 3.2.3.3 Multisector symbiosis
  • 3.2.3.4 Multisystem heterogeneity
  • 3.3 Key enabling technologies and Industry 5.0 architecture
  • 3.3.1 Technological pillars of Industry 5.0 and areas of application
  • 3.3.2 Multicognitive human-robot collaboration
  • 3.3.3 Architecture for Industry 5.0 implementation
  • 3.4 Identification of challenges and outlook toward Industry 5.0
  • 3.4.1 Extended reality and holographic computing
  • 3.4.2 Cognitive Digital Twins and Metaverse
  • 3.4.2.1 Digital Twin evolution
  • 3.4.2.2 Cognitive Digital Twin
  • 3.4.3 Ontology-based approaches to big data analytics
  • 3.4.4 Human-centric platforms for value creation and blockchain
  • 3.4.5 Implementation steps of Industry 5.0
  • 3.4.6 Proposed framework for the realization of Industry 5.0 and Society 5.0
  • 3.5 Challenges, opportunities, and limitations
  • 3.5.1 Challenges and opportunities
  • 3.5.1.1 Human cyber-physical systems
  • 3.5.1.2 Human Digital Twin
  • 3.5.1.3 Future operators and workforce
  • 3.5.1.4 Greentelligent manufacturing
  • 3.5.2 Social barriers and limitations
  • 3.6 Outlook and conclusion
  • References
  • 4 Challenges and opportunities of the transition from Industry 4.0 to Industry 5.0
  • 4.1 Introduction
  • 4.2 Related work
  • 4.2.1 Industrial revolutions toward Industry 5.0.
  • 4.2.2 Societal revolutions toward Society 5.0
  • 4.2.3 Industry 5.0
  • 4.2.3.1 Definitions
  • 4.2.3.2 Key enabling technologies
  • 4.2.3.3 Industry 5.0 areas of application
  • 4.2.3.3.1 Manufacturing industry
  • 4.2.3.3.2 Supply chain management
  • 4.2.3.3.3 Smart healthcare
  • 4.2.3.3.4 Smart cities and disaster management
  • 4.2.4 Society 5.0
  • 4.2.4.1 Definition
  • 4.2.4.2 The nature of Society 5.0
  • 4.2.4.3 Sustainable concept of Society 5.0
  • 4.3 Comparison between Industry 4.0 and Industry 5.0
  • 4.3.1 Comparison framework for Industry 4.0 and Industry 5.0
  • 4.3.2 Industry 4.0 vs. Industry 5.0
  • 4.3.3 Digital twin as a common building block of I4.0 and I5.0
  • 4.3.3.1 Decoding digital twins
  • 4.4 Discussion
  • 4.4.1 Industry in the Society 5.0 era
  • 4.4.2 Skills for the realization of Operator 5.0
  • 4.4.3 Human-centric manufacturing based on human digital twin in Industry 5.0
  • 4.4.4 Challenges and opportunities
  • 4.5 Conclusions and outlook
  • References
  • 5 Society 5.0: social implications, technoethics, and social acceptance
  • 5.1 Introduction
  • 5.2 Fundamentals of Society 5.0 and Industry 5.0
  • 5.2.1 Concept of Society 5.0
  • 5.2.2 Characteristics of Society 5.0
  • 5.2.2.1 Human-centered
  • 5.2.2.2 Integrated cyberspace and physical space
  • 5.2.2.3 Sustainable
  • 5.2.3 Comparison between Society 5.0 and Industry 5.0
  • 5.2.3.1 Goal dimension
  • 5.2.3.2 Value dimension
  • 5.2.3.3 Organization dimension
  • 5.3 Social implications
  • 5.3.1 Sustainable Development Goals and Society 5.0
  • 5.3.2 Digital transformation
  • 5.3.3 Social value
  • 5.3.3.1 Healthcare
  • 5.3.3.2 Education
  • 5.3.3.3 Manufacturing
  • 5.3.3.4 Transportation
  • 5.3.3.5 Energy
  • 5.3.3.6 Disaster management
  • 5.3.3.7 Agriculture and food
  • 5.3.3.8 Finance
  • 5.3.3.9 Public services
  • 5.4 Technoethics
  • 5.4.1 Human-centric technologies.
  • 5.4.1.1 Human-robot collaboration
  • 5.4.1.2 Artificial intelligence
  • 5.4.1.3 5G and beyond
  • 5.4.1.4 Big Data
  • 5.4.1.5 Internet of Everything
  • 5.4.1.6 Digital twin
  • 5.4.1.7 Edge computing
  • 5.4.1.8 Extended Reality
  • 5.4.2 Ethical considerations and policy recommendations
  • 5.4.2.1 Ethical considerations of Artificial Intelligence
  • 5.4.2.2 Ethical considerations of metaverse
  • 5.4.2.3 Policy recommendations
  • 5.5 Social acceptance
  • 5.5.1 Implementation of Society 5.0
  • 5.5.1.1 Healthcare system
  • 5.5.1.2 Sustainable environment
  • 5.5.1.3 Others
  • 5.5.2 Applications of Industry 5.0
  • 5.5.2.1 Human digital twin
  • 5.5.2.2 Smart additive manufacturing
  • 5.5.2.3 Human-machine integration
  • 5.5.3 Challenges
  • 5.5.4 Value system
  • 5.6 Conclusion
  • References
  • II. Industry 5.0: human-centric, resilient, and sustainable manufacturing
  • 6 Human-centric systems in smart manufacturing
  • 6.1 Introduction
  • 6.2 Terminology and definition of human-centric systems
  • 6.2.1 Terminology of human-centric systems
  • 6.2.2 Human roles in human-centric systems
  • 6.3 Manufacturing paradigm of human-centric systems
  • 6.3.1 Human-centric cyber-physical systems
  • 6.3.2 Human-machine/robot collaborative assembly
  • 6.3.3 Human-centric manufacturing systems in assembly
  • 6.4 Conclusions and future work
  • Acknowledgments
  • References
  • 7 The configuration of workforce and equipment in assembly lines: toward Industry 5.0
  • 7.1 Introduction
  • 7.2 Design of assembly lines for Industry 5.0: current trends and challenges
  • 7.3 Workforce dimensioning and new methodology for dynamic workforce and task planning
  • 7.3.1 Model-dependent task and workers assignment (MALBP−WMd vs MALBP−WFix)
  • 7.3.2 Dynamic (planned) task and workers assignment (MALBP−WDyn1 vs MALBP−WMd vs MALBP−WFix).
  • 7.3.3 Dynamic (reactive) task and workers assignment (MALBP−WDyn2 vs MALBP−WDyn1 vs MALBP−WMd vs MALBP−WFix)
  • 7.4 Illustrative example
  • 7.4.1 MALBP−WMd
  • 7.4.2 MALBP−WDyn1
  • 7.4.3 MALBP−WDyn2
  • 7.5 Discussion and outlook
  • 7.6 Conclusion
  • References
  • 8 Responsible manufacturing toward Industry 5.0
  • 8.1 Introduction
  • 8.2 Responsible artificial intelligence
  • 8.2.1 What is responsible artificial intelligence
  • 8.2.2 Basic principles of responsible artificial intelligence
  • 8.2.2.1 Transparency
  • 8.2.2.2 Fairness
  • 8.2.2.3 Accountability
  • 8.2.2.4 Privacy
  • 8.2.2.5 Robustness
  • 8.2.2.6 Human oversight
  • 8.2.3 Applications of responsible artificial intelligence in different fields
  • 8.2.3.1 Manufacturing
  • 8.2.3.2 Electricity
  • 8.2.3.3 Aerospace
  • 8.2.3.4 Autonomous driving
  • 8.2.3.5 Oil and gas extraction
  • 8.2.3.6 Agriculture
  • 8.3 Applicability of responsible artificial intelligence to smart manufacturing
  • 8.3.1 Applications of artificial intelligence in smart manufacturing
  • 8.3.2 Applicability of responsible artificial intelligence to smart manufacturing
  • 8.3.2.1 Human-centered artificial intelligence in manufacturing
  • 8.3.2.2 Fairness, transparency, accountability, privacy, and data security
  • 8.3.2.2.1 Fairness
  • 8.3.2.2.2 Transparency
  • 8.3.2.2.3 Accountability
  • 8.3.2.2.4 Privacy and data security
  • 8.3.3 Values of responsible artificial intelligence to smart manufacturing
  • 8.3.3.1 Enhancing trust and public perception
  • 8.3.3.2 Increased efficiency and cost savings
  • 8.3.3.3 Enhanced safety and security
  • 8.4 Case study: application of responsible manufacturing in the automotive manufacturing industry
  • 8.4.1 Press shop
  • 8.4.2 Real-time defect detection
  • 8.4.3 Predictive maintenance
  • 8.4.4 Normative maintenance
  • 8.4.5 Body shop
  • 8.4.6 Paint shop
  • 8.4.7 Final assembly shop.