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

Häftad, Engelska, 2021

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Beskrivning

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

Produktinformation

Utgivningsdatum:2021-11-12
Mått:152 x 229 x 21 mm
Vikt:660 g
Format:Häftad
Språk:Engelska
Antal sidor:406
Förlag:Elsevier Science
ISBN:9780128236574

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Tillverkningsteknik inom Naturvetenskap och teknik

Mer om författaren

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.

Innehållsförteckning

1. Introduction to cloud technology and Industry 4.0Dimitris Mourtzis2. Expected trends in production networks for mass personalization in the cloud technology eraAlexandre Dolgui, Dmitry Ivanov, Mirco Peron, and Fabio Sgarbossa3. Latest advances in cloud manufacturing and global production networks enabling the shift to the mass personalization paradigmGisela Lanza, Sina Peukert, and Gwen Louis Steier4. The mass personalization of global networksDimitris Mourtzis5. Production management guided by industrial internet of things and adaptive scheduling in smart factoriesDimitris Mourtzis, Nikos Panopoulos, and John Angelopoulos6. Digital technologies as a solution to complexity caused by mass personalizationNikolaos Papakostas and Aswin K. Ramasubramanian7. Innovative smart scheduling and predictive maintenance techniquesJinjiang Wang and Robert X. Gao8. Review of commercial and open technologies available for Industrial Internet of ThingsGünther Schuh, Matthias Jarke, Andreas Gützlaff, István Koren, Tim Janke, and Henning Neumann9. The role of big data analytics in the context of modeling design and operation of manufacturing systemsFoivos Psarommatis, Paul Arthur Dreyfus, and Dimitris Kiritsis10. Digital twins in industry 4.0Panagiotis Stavropoulos and Dimitris Mourtzis11. Review of machine learning technologies and artificial intelligence in modern manufacturing systemsAydin Nassehi, Ray Y. Zhong, Xingyu Li, and Bogdan I. Epureanu12. Blockchain-enabled product lifecycle managementZhi Li, Zonggui Tian, Lihui Wang, and Ray Y. Zhong