Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology draws on the latest industry advances to provide everything needed for the effective implementation of this powerful tool. Shorter product lifecycles have increased pressure on manufacturers through the increasing variety and complexity of production, challenging their workforce to remain competitive and profitable. This has led to innovation in production network methodologies, which together with opportunities provided by new digital technologies has fed a rapid evolution of production engineering that has opened new solutions to the challenges of mass personalization and market uncertainty.
In addition to the latest developments in cloud technology, reference is made to key enabling technologies, including artificial intelligence, the digital twin, big data analytics, and the internet of things (IoT) to help users integrate the cloud approach with a fully digitalized production system.
- Presents diverse cases that show how cloud-based technologies can be used in different ways as part of the standard operation of global production networks
- Provides detailed reviews of new technologies like the digital twin, big data analytics, and blockchain to provide context on the role of cloud technologies in a fully digitalized system
- Explores future trends for cloud technology and production engineering
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, Istvįn 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
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.
