Digital Transformation in Industrial Production Management Techniques and Systems
Perspectives from Industry 4.0 and Beyond
- 1st Edition - January 1, 2027
- Latest edition
- Editors: Ajay Kumar, Parveen Kumar, J. Paulo Davim
- Language: English
Intelligent industrial production management techniques enhance industrial services, products, and quality, contributing to societal improvements. This complex system involves… Read more
Description
Description
Intelligent industrial production management techniques enhance industrial services, products, and quality, contributing to societal improvements. This complex system involves resources, capital, people, machines, and information, all of which rapidly evolve with technological advancements. To meet market demands and global competitiveness, production management must integrate global resources and achieve resource efficiency, transitioning from traditional to digital methods. Digital transformation utilises technologies such as artificial intelligence (AI), machine learning (ML), digital twins (DT), the Industrial Internet of Things (IIoT), big data analytics, and augmented/virtual reality (AR/VR). These advancements optimise industrial systems and promote green production, reducing carbon emissions and improving quality of life. Digital Transformation in Industrial Production Management Techniques and Systems: Perspectives from Industry 4.0 and Beyond explores how Industry 4.0 facilitates digital transformation in production management, emphasising human-machine collaboration for resource efficiency and resilience. It is organised into three sections: fundamental strategies, Industry 4.0 trends, and applications in new product development and smart manufacturing, addressing challenges and opportunities in data-driven production management.
Key features
Key features
- Comprehensive overview of Industry 4.0 approaches in production management, emphasising intelligent tools and algorithms for sustainable practices across various sectors
- Explores fundamental concepts, opportunities, challenges, and frameworks in intelligent industrial production management, supported by experimental and numerical data
- Focuses on contemporary methodologies for sustainable and green production models applicable to diverse industries
Readership
Readership
Researchers, academicians, upper under graduate, post graduate, Ph.D. scholars in production engineering, mechanical, industrial engineering, supply chain management and operations management etc.
Table of contents
Table of contents
Section I: Intelligent Industrial Production Management Techniques and Systems: Fundamental Strategies
1. Major Technologies of Industry 4.0 in Industrial Production Management Techniques
2. Bibliometric analysis of Industry 4.0 enabled Intelligent Production Management Systems
3. Transformation of Production Management Systems from 1.0 to 4.0
4. Elements of Production Management Techniques
5. Intelligent design of Production Management Facilities
6. Intelligent Industrial Production Planning Control and Scheduling
7. Optimization of Production Management Methods by numerical/experimental and Computational/Simulation Approaches
Section II: Industry 4.0 Technologies Enabling Intelligence in Production Management Techniques
8. Developing a framework for Artificial Intelligence implementation In Intelligent Production Management
9. Digital Twin Technology Driven Production Management Methods
10. Human-Machine Interaction in Sustainable Production Management Systems
11. Augmented/Virtual/Mixed Reality in Production Engineering and Management
12. Cyber-Physical Systems in Production Management
13. Big Data Analytics in Production Management
14. Role of Blockchain Technologies in Production Management Techniques
15. Machine Learning (ML) approaches in production management
16. Industrial Internet of Things (IIoT) in Production Management Strategies
17. Role of cloud computing in intelligent production management techniques
18. Integration of 3D Printing Technologies with Intelligent Production Management Techniques
19. Information and Communication Technologies (ICT) Production Management Services
Section III: Applications of Data Driven Industrial Production Management Techniques
20. Role of Intelligent Production Management in New Product Development
21. Application of Intelligence of Production Management Techniques in Smart Manufacturing
22. Applications of Intelligent Production Management Techniques in Operational Departments of Manufacturing Industries
23. Current Challenges and Future Direction in implementation of Intelligent Production Methods
1. Major Technologies of Industry 4.0 in Industrial Production Management Techniques
2. Bibliometric analysis of Industry 4.0 enabled Intelligent Production Management Systems
3. Transformation of Production Management Systems from 1.0 to 4.0
4. Elements of Production Management Techniques
5. Intelligent design of Production Management Facilities
6. Intelligent Industrial Production Planning Control and Scheduling
7. Optimization of Production Management Methods by numerical/experimental and Computational/Simulation Approaches
Section II: Industry 4.0 Technologies Enabling Intelligence in Production Management Techniques
8. Developing a framework for Artificial Intelligence implementation In Intelligent Production Management
9. Digital Twin Technology Driven Production Management Methods
10. Human-Machine Interaction in Sustainable Production Management Systems
11. Augmented/Virtual/Mixed Reality in Production Engineering and Management
12. Cyber-Physical Systems in Production Management
13. Big Data Analytics in Production Management
14. Role of Blockchain Technologies in Production Management Techniques
15. Machine Learning (ML) approaches in production management
16. Industrial Internet of Things (IIoT) in Production Management Strategies
17. Role of cloud computing in intelligent production management techniques
18. Integration of 3D Printing Technologies with Intelligent Production Management Techniques
19. Information and Communication Technologies (ICT) Production Management Services
Section III: Applications of Data Driven Industrial Production Management Techniques
20. Role of Intelligent Production Management in New Product Development
21. Application of Intelligence of Production Management Techniques in Smart Manufacturing
22. Applications of Intelligent Production Management Techniques in Operational Departments of Manufacturing Industries
23. Current Challenges and Future Direction in implementation of Intelligent Production Methods
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 1, 2027
- Language: English
About the editors
About the editors
AK
Ajay Kumar
Ajay Kumar is a Professor (Research Track), Department of Mechanical Engineering, School of Core Engineering, Faculty of Science, Technology & Architecture, Manipal University Jaipur.
Affiliations and expertise
Professor (Research Track), Department of Mechanical Engineering, School of Core Engineering, Faculty of Science, Technology & Architecture, Manipal University Jaipur, IndiaPK
Parveen Kumar
Parveen Kumar is an Assistant Professor in the Department of Mechanical Engineering, at Rawal Institute of Engineering and Technology, Faridabad, Haryana, India. His areas of research include advanced materials, die-less forming, additive manufacturing, CAD/CAM, and optimization techniques.
Affiliations and expertise
Assistant Professor, Department of Mechanical Engineering, Rawal Institute of Engineering and Technology, Faridabad, Haryana, IndiaJD
J. Paulo Davim
Prof. (Dr.) J. Paulo Davim is a Full Professor at the University of Aveiro, Portugal, with over 35 years of experience in Mechanical, Materials, and Industrial Engineering. He holds multiple distinguished academic titles, including a PhD in Mechanical Engineering and a DSc from London Metropolitan University. He has published over 300 books and 600 articles, with more than 36,500 citations. He is ranked among the world's top 2% scientists by Stanford University and holds leadership positions in numerous international journals, conferences, and research projects.
Affiliations and expertise
Full Professor, Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal