Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology

Dimitris Mourtzis is a Professor in the Dept. of Mechanical Engineering and Aeronautics and Vice President of the Research Council of the University of Patras. He is a Founding Member of the CLEAN AVIATION Joint Undertaking Governing Body and Director of the Laboratory for Manufacturing Systems and Automation (LMS). He is a Fellow of the International Academy for Production Research (CIRP), the International Federation of Automatic Control (IFAC), the International Federation of Information Processing (IFIP), and Member of the American Society of Mechanical Engineers (ASME) and the Institute of Electrical and Electronic Engineers (IEEE). His scientific interests focus on design, planning, and control of manufacturing systems and networks, robotic systems, automation, advanced simulation including augmented, mixed, and virtual reality in manufacturing, manufacturing processes modeling and optimization, digital manufacturing, industry 4.5, industry 5.0, metaverse, and hybrid teaching factory.

1. Introduction to cloud technology and Industry 4.0

Dimitris Mourtzis

2. Expected trends in production networks for mass personalization in the cloud technology era

Alexandre Dolgui, Dmitry Ivanov, Mirco Peron, and Fabio Sgarbossa

3. Latest advances in cloud manufacturing and global production networks enabling the shift to the mass personalization paradigm

Gisela Lanza, Sina Peukert, and Gwen Louis Steier

4. The mass personalization of global networks

Dimitris Mourtzis

5. Production management guided by industrial internet of things and adaptive scheduling in smart factories

Dimitris Mourtzis, Nikos Panopoulos, and John Angelopoulos

6. Digital technologies as a solution to complexity caused by mass personalization

Nikolaos Papakostas and Aswin K. Ramasubramanian

7. Innovative smart scheduling and predictive maintenance techniques

Jinjiang Wang and Robert X. Gao

8. Review of commercial and open technologies available for Industrial Internet of Things

Günther Schuh, Matthias Jarke, Andreas Gützlaff, István Koren, Tim Janke, and Henning Neumann

9. The role of big data analytics in the context of modeling design and operation of manufacturing systems

Foivos Psarommatis, Paul Arthur Dreyfus, and Dimitris Kiritsis

10. Digital twins in industry 4.0

Panagiotis Stavropoulos and Dimitris Mourtzis

11. Review of machine learning technologies and artificial intelligence in modern manufacturing systems

Aydin Nassehi, Ray Y. Zhong, Xingyu Li, and Bogdan I. Epureanu

12. Blockchain-enabled product lifecycle management

Zhi Li, Zonggui Tian, Lihui Wang, and Ray Y. Zhong