Smart Manufacturing Factory : Artificial-Intelligence-Driven Customized Manufacturing

Artificial Intelligence (AI) technologies enable manufacturing systems to sense the environment, adapt to external needs, and extract process knowledge, including business models such as intelligent production, networked collaboration, and extended service models. This book therefore focuses on the implementation of AI in customized manufacturing (CM).

The main topics include edge intelligence in manufacturing, heterogeneous networks, intelligent fault diagnosis and maintenance, dynamic resource scheduling in manufacturing, and the construction mode of the smart factory. Based on the insights of CM and AI, the authors demonstrate the implementation of AI in the smart factory for CM, including architecture, information fusion, data analysis, dynamic scheduling, flexible production line construction, and smart manufacturing services.

This book will provide important research content for scholars in artificial intelligence, smart manufacturing, machine learning, multi-agent systems, and industrial Internet of Things.

Jiafu Wan is a Professor in School of Mechanical & Automotive Engineering at South China University of Technology, China. He has directed 20 research projects, including the National Key Research and Development Program of China, and the Joint Fund of the National Natural Science Foundation of China and Guangdong Province. Thus far, he has published more than 160 scientific papers, including 120+ SCI-indexed papers, and 50+ IEEE Trans./Journal papers. According to Google Scholar Citations, his published work has been cited more than 21,000 times. He was listed as a Clarivate Analytics Highly Cited Researcher (2019-2022).

Baotong Chen received the Ph.D. degree mechanical engineering from the Department of Mechanical & Electrical Engineering, South China University of Technology (SCUT). He is currently a Lecturer with the Department of Industrial Engineering and Manufacturing, Wuhan University of Science and Technology (WUST). His research interests include equipment preventive maintenance, multi-robot collaboration, and mixed model assembly.

Shiyong Wang is an Associate Professor in the School of Mechanical & Automotive Engineering at South China University of Technology, China. He has directed 20 research projects, including the National Key Research and Development Program of China and the National Natural Science Foundation of China. Thus far, he has published more than 50 scientific papers, including 30+ SCI-indexed papers. According to Google Scholar Citations, his published work has been cited more than 5,000 times. He was listed as a Highly Cited Chinese Researcher by Elsevier (2020 and 2022).