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English
Elsevier Science Publishing Co Inc
12 November 2021
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.
Edited by:  
Imprint:   Elsevier Science Publishing Co Inc
Country of Publication:   United States
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   660g
ISBN:   9780128236574
ISBN 10:   0128236574
Pages:   406
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
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

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.

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