Machine health management in smart factory: A review |
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| Authors: | Gil-Yong Lee Mincheol Kim Ying-Jun Quan Min-Sik Kim Thomas Joon Young Kim Hae-Sung Yoon Sangkee Min Dong-Hyeon Kim Jeong-Wook Mun Jin Woo Oh In Gyu Choi Chung-Soo Kim Won-Shik Chu Jinkyu Yang Binayak Bhandari Choon-Man Lee Jeong-Beom Ihn " target="_blank">Sung-Hoon Ahn |
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| Affiliation: | 1.Institute of Advanced Machines and Design (IAMD),Seoul National University,Seoul,Korea;2.Department of Mechanical and Aerospace Engineering,Seoul National University,Seoul,Korea;3.Department of Mechanical Engineering,University of Wisconsin-Madison,Madison,USA;4.BK21 Plus Transformative Training Program for Creative Mechanical and Aerospace Engineers,Seoul National University,Seoul,Korea;5.Research Laboratory of Electronics,Massachusetts Institute of Technology,Cambridge,USA;6.William E. Boeing Department of Aeronautics & Astronautics,University of Washington,Seattle,USA;7.Department of Railroad Integrated System,Woosong University,Daejeon,Korea;8.School of Mechanical Engineering,Changwon National University,Changwon,Korea;9.Boeing Research and Technology,Boeing, Seattle, Washington,USA;10.Graduate School of Engineering Practice,Seoul National University,Seoul,Korea;11.Institute of Engineering Research,Seoul National University,Seoul,Korea |
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| 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. |
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