Flexible Automation and Intelligent Manufacturing: Manufacturing Innovation and Preparedness for the Changing World Order - Proceedings of FAIM 2024, June 23-26, 2024, Taichung, Taiwan, Volume 1

This book reports on cutting-edge research and developments in manufacturing, giving a special emphasis to solutions for the Changing World Order. It covers applications of machine learning in manufacturing and advances in cyber-physical systems, human-robot collaboration, and machine tools and assembly systems.  It also reports on advances in logistics and supply chain, and lean manufacturing.  Based on the proceedings of the 33rd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2024), held on June 23-26, 2024, in Taichung, Taiwan, this first volume of a 2-volume set provides academics and professionals with extensive, technical information on trends and technologies in manufacturing, yet it also discusses challenges and practice-oriented experience in all the above-mentioned areas.

Produktdetails

• Mitarbeit: Siu Hang Chan (Herausgeber), Siu Hang Chan (Herausgeber), Yi-Chi Wang (Herausgeber), Zih-Huei Wang (Herausgeber)
• Verlag: Springer, Berlin
• Sprache: Englisch
• Produktform: Taschenbuch
• Erschienen: 01.12.2024
• EAN: 9783031744815
• ISBN: 978-3-0-3174481-5
• Seiten: 483
• Abmessung: 155 mm x 26 mm x 235 mm
• Gewicht: 751 g
• Illustration: XVI, 483 p. 192 illus., 162 illus. in color.
• Serie: Lecture Notes in Mechanical Engineering
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Technik > Elektronik, Elektrotechnik, Nachrichtentechnik; Regelungstechnik, Konstruktion, Entwurf, Predictive Maintenance, Engineering Design, Machines, Tools, Processes, Control, Robotics, Automation, Intelligent Control Systems, Digital Twin for Manufacturing, Automated Maintenance, Cyber Physical Production Systems, human-robot collaboration, Lean and Green Manufacturing, Adaptive/Dynamic Control in Manufacturing, Cyber-Security Threats, Collaborative Robots in Manufacturing, Machine Learning Models in Manufacturing