This proceeding is a compilation of selected papers from the 8th International Workshop of Advanced Manufacturing and Automation (IWAMA 2018), held in Changzhou, China on September 25 - 26, 2018. Most of the topics are focusing on novel techniques for manufacturing and automation in Industry 4.0 and smart factory. These contributions are vital for maintaining and improving economic development and quality of life. The proceeding will assist academic researchers and industrial engineers to implement the concepts and theories of Industry 4.0 in industrial practice, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factory.

Autorentext

**Professor Kesheng Wang **has been a Professor and director of the Knowledge Discovery Laboratory at the Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology (NTNU), Norway. He became an elected member of the Norwegian Academy of Technological Sciences in 2006. Prof. Wang has published 22 books, 10 book chapters and over 270 technical peer-reviewed papers in international journals and conferences. He also has extensive experience with coordinating cooperation projects with many industrial companies and national, international and EU projects. Professor Wang's current areas of interest are intelligent manufacturing systems, data mining and knowledge discovery, radio-frequency identification (RFID), predictive maintenance and Industry 4.0/Logistics 4.0.

Dr. Yi Wang obtained his PhD from the Manufacturing Engineering Center, Cardiff University, UK in 2008. He is currently a Lecturer at the School of Business, Plymouth University, UK. He holds various visiting professorships in several universities worldwide. Dr. Wang's research interests include supply chain management, logistics, operation management, culture management, information systems, game theory, data analysis, semantics and ontology analysis, and neuromarketing. He has published over 70 technical peer-reviewed papers in international journals and conferences. He has co-authored two monographs: Operations Management for Business in 2008 and Data Mining for Zero-defect Manufacturing in 2012. He will publish a new book in 2018: Intelligent fashion supply chain, Taylor and Francis. (in progress)

Professor Jan Ola Strandhagen is a Professor at the Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology (NTNU), Norway. He was previously director of the research center SFI Norman in SINTEF. He holds a PhD in Production Engineering from NTNU (1994). His research has focused on production management and control, logistics, manufacturing economics and strategies. He has managed and executed R&D projects in close collaboration with a wide variety of Norwegian companies and participated as researcher and project manager in several European projects.

**Professor Tao Yu **is the President of Shanghai Polytechnic University, Shanghai, China and Professor at Shanghai University. He is a committee member of the International Federation for Information Processing (IFIP)/TC5. Prof. Yu has published more than one hundred academic papers. His research interests include mechatronics, computer integrated manufacturing systems and grid manufacturing.

Inhalt

Robotics and Automation.- Chemical Process Equipment.- Parallel Mechanism and Manipulator.- Computational Intelligence.- Design and Optimization.- Product Life-cycle Management.- Integration of CAD/CAPP/CAM/CIMS.- Advanced Manufacturing Systems.- Manufacturing Operations Management.- Knowledge-based Manufacturing.- Manufacturing Quality Control and Management.- Sustainable Production.- Diagnosis and Prognosis of Machines.- Industry 4.0.- Lean and Agile Manufacturing.- Virtual and Grid Manufacturing.- Resource and Asset Management.- Logistics and Supply Chain Management.- EEG and Eye Tracking for Cognitive Applications.- RFID Applications.- Predictive Maintenance.- Reliability and Maintainability in Manufacturing.- Project Management.- Renewable Energy Development.- Knowledge Management and Decision Making.- Intelligent Inspection.