This book presents selected papers from the 10th International Workshop of Advanced Manufacturing and Automation (IWAMA 2020), held in Zhanjiang, Guangdong province, China, on October 12-13, 2020. Discussing topics such as novel techniques for manufacturing and automation in Industry 4.0 and smart factories, which are vital for maintaining and improving economic development and quality of life, it offers researchers and industrial engineers insights into implementing the concepts and theories of Industry 4.0, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.
About the Author: Dr. Yi Wang obtained his PhD from Manufacturing Engineering Center, Cardiff University in 2008. Hu is a lecturer in Business School, Plymouth University, UK. Previously he worked in the department of Computer Science, Southampton University and at the Business School, Nottingham Trent University. He holds various visiting lectureship in several universities worldwide. Dr. Wang has special research interests in supply chain management, logistics, operation management, culture management, Big data and data analytics, Neuromarketing, and Industry 4.0/5.0. Dr. Wang has published over 100 technical peer-reviewed papers in international journals, book chapters and conferences. He has authored 3 books, for example, 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, Kristian Martinsen took his PhD at the Norwegian University for Science and Technology (NTNU) in 1995, with the topic "Vectorial Tolerancing in Manufacturing". He has 15 years' experience from manufacturing industry. He is a Professor at faculty of Engineering and Department for Manufacturing and Civil Engineering, the Norwegian University for Science and Technology (NTNU), and is the manager of the Manufacturing Engineering research group in this department. He is a corporate member of the International academy for Production Engineering and a member of the High-Level Group of the EU Technology Platform for manufacturing; MANUFUTURE. He is the manager of the Norwegian national infrastructure for manufacturing research laboratories; MANULAB, and is the international coordinator for the Norwegian Centre for Research-based Innovation SFI MANUFACTURING. He has published many papers in international journals and conference. His major research area is within the field of measurement systems, variation/quality management and toleranceing. Towards Industry 5.0: Research Challenges in Human-Machine Systems
Dr. Tao Yu is the president of Shanghai Second Polytechnic University (SSPU), China and professor of Shanghai University (SHU). He received his PhD from SHU in 1997. Professor 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 an executive vice president of Shanghai Science Volunteer Association, and executive director of Shanghai Science and Art Institute of Execution. He managed and perform about 20 national, Shanghai, 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) and Grid Manufacturing.
Dr. Kesheng Wang holds a PhD 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.
