The book is a compilation of selected papers from the 13th International Workshop of Advanced Manufacturing and Automation (IWAMA 2023), held in Shanghai University of Engineering Science, China on 15 — 16 October, 2023. Topics focusing on novel techniques for manufacturing and automation in Industry 4.0 are now vital factors for the maintenance and improvement of the economy of a nation and the quality of life. It will help academic researchers and engineers to implement the concept, theory and methods in Industry 4.0 which has been a hot topic. These proceedings will make valuable contributions to academic researchers, engineers in the industry for the challenges in the 4th industry revolution and smart factories.
Содержание
Industry 4.0 and 5.0.- Robotics and Automation.- AI & Computational Intelligence.- Intelligent Manufactory.- Design and Optimization.- Product Life-cycle Management.- Advanced Manufacturing Systems.- Manufacturing Operations Management.- Smart Aquaculture Technology.- Knowledge Management and Decision Making.- Manufacturing Quality Control and Management.- Sustainable Production.- Diagnosis and Prognosis of Machines.- Lean and Agile Manufacturing.- Virtual and Grid Manufacturing.- Resource and Asset Management.- Logistics and Supply Chain Management.- Fashion Logistics and Marketing.- RFID Applications.- Predictive and Cognitive Maintenance.- 3D Printing.- Intelligent Inspection.- Chemical Process Equipment.- Parallel Mechanism and Manipulator.- Integration of CAD/CAPP/CAM/CIMS.- Smart Factory.
Об авторе
Prof. Dr. Yi Wang obtained his Ph D from Manufacturing Engineering Center, Cardiff University in 2008. He is a professor in Business School, University of Bedfordshire, Luton, UK. Previously, he worked in Southampton University, Nottingham Trent University, Manchester University and Plymouth University. He holds various visiting lectureships in several universities worldwide. Prof. Wang has special research interests in supply chain management, logistics, operation management, culture management and, Neuromarketing, big data and data analytics, and Industry 4.0/5.0. Prof Wang has published over 100 technical peer-reviewed papers in international journals, book chapters and conferences. He has authored 3 books, , Operations Management for Business, Fashion Supply Chain Management and Data Mining for Zero-defect Manufacturing. etc., edited 6 books, and made 5 book chapters.Dr. Tao Yu is the president at Shanghai University of Engineering Science (SUES), China.Previously he was the president of Shanghai Polytechnic University (SSPU), China. He is a professor at Shanghai University (SHU). He received his Ph D from SHU in 1997. Prof. Yu is a member of the Group of Shanghai manufacturing information and a committee member of the International Federation for Information Processing IFIP /TC5. He is also the vice director of Shanghai Arbitration Commission, and the vice chairman of the academic committee of Shanghai Key Laboratory of Smart Manufacturing and Robotics. He managed and performed about 20 national and Shanghai local enterprises commissioned projects. He has published hundreds of academic papers, of which about thirty were indexed by SCI, EI. His research interests are mechatronics, computer integrated manufacturing system (CIMS).
Dr. Kesheng Wang holds Ph D degree in production engineering from the Norwegian University of Science and Technology (NTNU), Norway. Since 1993, he has been appointed Professor at the Department of Mechanical and Industrial Engineering, NTNU. He was a director of the Knowledge Discovery Laboratory (KDL) at NTNU. He is also an active researcher and serves as a technical adviser in SINTEF. He was elected member of the Norwegian Academy of Technological Sciences (NTVA) in 2006. He has published 22 books, 10 book chapters and over 300 technical peer-reviewed papers in international journals, book chapters and conferences. Professor Wang’s current areas of interest are intelligent manufacturing systems, applied computational intelligence, data mining and knowledge discovery, Predictive/Cognitive Maintenance and Industry 4.0.
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