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

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 INDICE: 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

• ISBN: 978-0-12-823657-4
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 406
• Fecha Publicación: 12/11/2021
• Nº Volúmenes: 1
• Idioma: Inglés