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Machine health management in smart factory: A review

期刊

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
卷 32, 期 3, 页码 987-1009

出版社

KOREAN SOC MECHANICAL ENGINEERS
DOI: 10.1007/s12206-018-0201-1

关键词

Smart factory; Machine health management; Virtual factory; Cloud manufacturing

资金

  1. SNU-Hojeon Garment Smart Factory Research Center - Hojeon Ltd.
  2. Next Generation Hybrid Manufacturing Consortium of Institute of Advanced Machines and Design at Seoul National University
  3. Korea Basic Science Institute (KBSI) Creative Convergence Research Project - National Research Council of Science and Technology (NST) [CAP-PN2017003]
  4. International S&T Cooperation Program through the National Research Foundation of Korea (NRF) - Ministry of Science, ICT & Future Planning (MSIP) [NRF-2017K1A3A9A04013801]
  5. SNU-Boeing collaborative research project - Boeing Research & Technology (BRT), Boeing, USA

向作者/读者索取更多资源

In this paper, we present a review of machine health managements for the smart factory. As the Industry 4.0 leads current factory automation and intelligent machines, the machine health management for diagnostic and prognostic purposes are essential, and their importance is getting more significant for the realization of the smart factory in the Industry 4.0. After brief introductions to important concepts and definitions composing smart factory and Industry 4.0, the developments in maintenance strategies towards Prognostics and health management (PHM) of machines are summarized. The review of machine health managements is followed, classifying the references by the monitoring components, types of measurements, as well as PHM tools and algorithms. 94 existing articles are reviewed and summarized in this regard. The implementations of machine health managements within the smart factory are discussed in terms of data connectivity, communications, Cyber-physical system (CPS) and virtual factory, relating them to Internet of things (IoT), cloud computing, and big data management.

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