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| 1 | Digital twin-based sustainable intelligent manufacturing: a review显示文摘As the next-generation manufacturing system,intelligent manufacturing enables better quality,higher productivity,lower cost,and increased manufacturing flexibility.The concept of sustainability is receiving increasing attention,and sustainable manufacturing is evolving.The digital twin is an emerging technology used in intelligent manufacturing that can grasp the state of intelligent manufacturing systems in real-time and predict system failures.Sustainable intelligent manufacturing based on a digital twin has advantages in practical applications.To fully understand the intelligent manufacturing that provides the digital twin,this study reviews both technologies and discusses the sustainability of intelligent manufacturing.Firstly,the relevant content of intelligent manufacturing,including intelligent manufacturing equipment,systems,and services,is analyzed.In addition,thesustainability of intelligent manufacturing is discussed.Subsequently,a digital twin and its application are introduced along with the development of intelligent manufacturing based on the digital twin technology.Finally,combined with the current status,the future development direction of intelligent manufacturing is presented. | Bin He Kai-Jian Bai | 2021 | Advances in Manufacturing2021，9，1： | 24 |
| 2 | Framework and case study of cognitive maintenance in Industry 4.0显示文摘We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligent decision-making tech-niques, which can be used by maintenance professionals who are working with cutting-edge equipment. The systems will provide technical solutions to real-time online maintenance tasks, avoid outages due to equipment failures, and ensure the continuous and healthy operation of equipment and manufacturing assets. The implementation framework of CM consists of four modules, i.e., cyber-physical system, Internet of Things, data mining, and Internet of Services. In the data mining module, fault diagnosis and prediction are realized by deep learning methods. In the case study, the backlash error of cutting-edge machine tools is taken as an example. We use a deep belief network to predict the backlash of the machine tool, so as to predict the possible failure of the machine tool, and realize the strategy of CM. Through the case study, we discuss the significance of implementing CM for cutting-edge equipment, and the framework of CM implementation has been verified. Some CM system applications in manufacturing enterprises are summarized. | Bao-rui LI Yi WANG Guo-hong DAI Ke-sheng WANG | 2019 | Frontiers of Information Technology & Electronic Engineering2019，20，11： | 1 |
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