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- Title
Machine health management in smart factory: A review.
- Authors
Lee, Gil-Yong; Kim, Mincheol; Quan, Ying-Jun; Kim, Min-Sik; Kim, Thomas Joon Young; Yoon, Hae-Sung; Min, Sangkee; Kim, Dong-Hyeon; Mun, Jeong-Wook; Oh, Jin Woo; Choi, In Gyu; Kim, Chung-Soo; Chu, Won-Shik; Yang, Jinkyu; Bhandari, Binayak; Lee, Choon-Man; Ihn, Jeong-Beom; Ahn, Sung-Hoon
- Abstract
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.
- Subjects
MACHINERY maintenance &; repair; AUTOMATION; ARTIFICIAL intelligence; INDUSTRY 4.0; INTERNET of things; CLOUD computing
- Publication
Journal of Mechanical Science & Technology, 2018, Vol 32, Issue 3, p987
- ISSN
1738-494X
- Publication type
Article
- DOI
10.1007/s12206-018-0201-1