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.
1. Chapter 1 : Introduction to cloud technology and Industry 4.0 - p. Page ix 2. Chapter 2 : Expected trends in production networks for mass personalization in the cloud technology era - p. Page 11 3. Chapter 3 : Latest advances in cloud manufacturing and global production networks enabling the shift to the mass personalization paradigm - p. Page 31 4. Chapter 4 : The mass personalization of global networks - p. Page 73 5. Chapter 5 : Production management guided by industrial internet of things and adaptive scheduling in smart factories - p. Page 110 6. Chapter 6 : Digital technologies as a solution to complexity caused by mass personalization - p. Page 147 7. Chapter 7 : Innovative smart scheduling and predictive maintenance techniques - p. Page 175 8. Chapter 8 : Review of commercial and open technologies available for Industrial Internet of Things - p. Page 202 9. Chapter 9 : The role of big data analytics in the context of modeling design and operation of manufacturing systems - p. Page 239 10. Chapter 10 : Digital twins in industry 4.0 - p. Page 270 11. Chapter 11 : Review of machine learning technologies and artificial intelligence in modern manufacturing systems - p. Page 309 12. Chapter 12 : Blockchain-enabled product lifecycle management - p. Page 345 13. Index - p. Page 377
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.
1. Chapter 1 : Introduction to cloud technology and Industry 4.0 - p. Page ix 2. Chapter 2 : Expected trends in production networks for mass personalization in the cloud technology era - p. Page 11 3. Chapter 3 : Latest advances in cloud manufacturing and global production networks enabling the shift to the mass personalization paradigm - p. Page 31 4. Chapter 4 : The mass personalization of global networks - p. Page 73 5. Chapter 5 : Production management guided by industrial internet of things and adaptive scheduling in smart factories - p. Page 110 6. Chapter 6 : Digital technologies as a solution to complexity caused by mass personalization - p. Page 147 7. Chapter 7 : Innovative smart scheduling and predictive maintenance techniques - p. Page 175 8. Chapter 8 : Review of commercial and open technologies available for Industrial Internet of Things - p. Page 202 9. Chapter 9 : The role of big data analytics in the context of modeling design and operation of manufacturing systems - p. Page 239 10. Chapter 10 : Digital twins in industry 4.0 - p. Page 270 11. Chapter 11 : Review of machine learning technologies and artificial intelligence in modern manufacturing systems - p. Page 309 12. Chapter 12 : Blockchain-enabled product lifecycle management - p. Page 345 13. Index - p. Page 377
