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Frontiers of Information Technology & Electronic Engineering

2019, Volume 20,  Issue 11, Pages 1493-1504
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    Framework and case study of cognitive maintenance in Industry 4.0

    Affiliation(s): Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200444, China; School of Business, University of Plymouth, Plymouth Devon PL4 8AA, UK; School of Mechanical Engineering, Changzhou University, Changzhou 213164, China; Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim N-7491, Norway; less

    Received： 2019-12-10 08:00:00 Accepted：2019-04-14 08:00:00 Available online：2019-12-10
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    10.1631/FITEE.1900193
    Cite this article
    Bao-rui Li,, Yi Wang,, Guo-hong Dai,, Ke-sheng Wang,kesheng.wang@ntnu.no.Framework and case study of cognitive maintenance in Industry 4.0[J].Frontiers of Information Technology & Electronic Engineering,2019,20(11):1493-1504.

    Abstract

    We present a new framework for (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent approaches and intelligent decision-making techniques, which can be used by maintenance professionals who are working with . 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 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.

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