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

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.