
Smart Manufacturing Factory
Artificial-Intelligence-Driven Customized Manufacturing
CRC Press
1st Edition
Published on 28. December 2023
Book
Hardback
458 pages
978-1-032-60896-9 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Postgraduate and Professional Reference
Illustrations
268 s/w Abbildungen, 100 s/w Photographien bzw. Rasterbilder, 168 s/w Zeichnungen, 77 s/w Tabellen
77 Tables, black and white; 168 Line drawings, black and white; 100 Halftones, black and white; 268 Illustrations, black and white
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 30 mm
Weight
1075 gr
ISBN-13
978-1-032-60896-9 (9781032608969)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jiafu Wan | Baotong Chen | Shiyong Wang
Smart Manufacturing Factory
Artificial-Intelligence-Driven Customized Manufacturing
Book
approx. 12/2025
1st Edition
CRC Press
€76.40
Not yet published

Jiafu Wan | Baotong Chen | Shiyong Wang
Smart Manufacturing Factory
Artificial-Intelligence-Driven Customized Manufacturing
E-Book
12/2023
1st Edition
CRC Press
€69.99
Available for download

Jiafu Wan | Baotong Chen | Shiyong Wang
Smart Manufacturing Factory
Artificial-Intelligence-Driven Customized Manufacturing
E-Book
12/2023
1st Edition
CRC Press
€69.99
Available for download
Persons
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).
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).
Content
I. Introduction to Smart Manufacturing Factory II. Edge Intelligence in Customized Manufacturing III. Heterogeneous Networks in Smart Manufacturing Factory IV. Intelligent Fault Diagnosis and Maintenance in Smart Manufacturing Factory V. Resource Dynamic Scheduling in Manufacturing VI. Implementation of Customized Manufacturing Factory