Advanced Manufacturing and Automation XV

Prof. Dr. Yi Wang obtained his Ph.D. from Manufacturing Engineering Center, Cardiff University in 2008. He is a professor in School of Business, 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.Prof. Dr. Tao Yu is a professor and dean of Bionic Institute Robot Dreamworks for Special purpose (BIRDS) at Shanghai University (SHU). He is honorary director of Shanghai Key Laboratory of Intelligent Manufacturing and Robotics at Shanghai University. He was the president at Shanghai University of Engineering Science (SUES) and Shanghai Polytechnic University (SSPU), China. He received his PhD from SHU in 1997. Prof. Yu is a member of the Shanghai manufacturing information group 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 systems (CIMS), humanoid robotics and intelligent agriculture systems.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 as a 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 an 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.

• A Review of Intelligent Algorithms for Flexible Job Shop Scheduling Problems.- Identifying Key Genes and Functional Analysis of Interaction Networks in Alzheimer's Disease Based on Bioinformatics.- Physical feasible dynamic parameter identification of the 7-DOF robot using iterative reweighted least squares.- Operation Optimization of Combined Cooling, Heating and Power System Based on Non-dominant Sorting Whale Optimization Algorithm.- Research on flexible job shop scheduling based on intelligent algorithm.- Research on low-carbon scheduling problem of distributed multi-objective flexible job shop for automotive bearing production.- The Research Progress on Bolt Surface Micro-Defect Detection Based on Deep Learning.- Optimization study of 3D point cloud registration algorithm based on truncated least squares estimation.- Research on Industrial Part Classification Technology Based on Adversarial Networks.- Research on 3D Point Cloud Classification and Segmentation Based on Deep Learning.- Design of surface defect detection system based on YOLOv5.- Analysis of the swinging characteristics of ship ladders in a land-based marine environment with cable sway.- Fundamental Research on Growth Behavior of Dicing Blade Based on Electrochemical Additive Manufacturing.- Development Status and Trends of Photovoltaic Panel Cleaning Technology.