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.
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Table of Contents
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
G�nther Schuh, Matthias Jarke, Andreas G�tzlaff, Istv�n 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
