Intelligent Predictive Maintenance

Min Liu received the B.Sc. degree from China University of Geosciences, Wuhan, China, in 1993, and the M.Sc. and Ph.D. degrees from Zhejiang University, Hangzhou, China, in 1996 and 1999, respectively. He is a full professor at the College of Electronic and Information Engineering, Tongji University, Shanghai, China. He was a Post-Doctoral Fellow at the Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China, from 1999 to 2001. From 2001 to 2004, he was a product architecture engineer at Asia-Bridge Software Company Ltd, where he developed an enterprise resource management system. He has authored or co-authored over 100 papers in scientific journals and international conferences in related fields. He has been involved in research on artificial intelligence technologies for collaborative intelligent manufacturing and MRO services over 20 years. Ling Li received her bachelor's and master's degrees from Hubei University, Wuhan, China, in 2004 and 2007, respectively, and her Ph.D. in Control Science and Engineering from Tongji University, Shanghai, China, in 2018. Now she is a full professor at the School of Statistics and Mathematics, Shanghai Lixin University of Accounting and Finance, Shanghai, China. Her research interests include service-oriented computing, supply chain management, intelligent maintenance and reliability theory. Feng Yan received his B.S., M.S. and Ph.D. degrees from Central South University, Changsha, China in 2003, 2007 and 2015, respectively. He is a senior engineer with the rank of a professor from CINF Engineering Co., Ltd. and serves as deputy director of the Science & Technology Management Dept. and R&D Centre of CINF. He has been honoured as an outstanding young engineer by the Nonferrous Metals Society of China and an outstanding automation engineer by the Chinese Association of Automation. He has been involved in the research and engineering application of automation and intelligent technology in the process industry over 15 years.

• Chapter 1 Introduction.- Chapter 2 Methods of Fault Diagnosis and Prediction.- Chapter 3 Intelligent Predictive Maintenance System and Framework.- Chapter 4 IoT-based Perception Resource Management Framework and Model.- Chapter 5 Wireless Routing Model and Algorithm for Complex Manufacturing Environment.- Chapter 6 Protocol Integration and Design Case of Data Collection.- Chapter 7 Data-driven Fault Diagnosis Methods.- Chapter 8 Data-driven Fault Prediction Model and Methods.- Chapter 9 Maintenance Optimization Scheduling and Decision Making in Intelligent Factories.- Chapter 10 Large-scale Maintenance Service Forecasting and Optimization Configuration.- Chapter 11 Operation Process Control based on Cyber-Physical Systems.