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

  • Book

  • November 2021
  • Elsevier Science and Technology
  • ID: 5342381

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


Dimitris Mourtzis Laboratory Director & Full Professor, Laboratory for Manufacturing Systems and Automation (LMS), Department of Mechanical Engineering and Aeronautics, University of Patras, Rio Patras, Greece. Prof. Dimitris Mourtzis is the Director of the Laboratory for Manufacturing Systems and Automation (LMS), the Deputy Head of the Mechanical Engineering and Aeronautics Department of the University of Patras and was the Director of the Design and Manufacturing Division from 2015 to 2017. He has published more than 300 scientific papers throughout his career and his main research interests focus on manufacturing systems, robot automation and virtual reality in manufacturing, and manufacturing processes modeling and energy efficiency. He is also actively involved in digital transformation and implementation of industry 4.0 practices, both at a national and international level. [Full bio: Mourtzis Dimitris - MEAD (upatras.gr)]