TY - JOUR
T1 - Machine health management in smart factory
T2 - A review
AU - Lee, Gil-Yong
AU - Kim, Mincheol
AU - Quan, Yin-Jun
AU - Kim, Min-Sik
AU - Kim, Thomas Joon Young
AU - Yoon, Hae-Sung
AU - Min, Sangkee
AU - Kim, Dong-Hyeon
AU - Mun, Jeong-Wook
AU - Oh, Jin Woo
AU - Choi, In Gyu
AU - Kim, Chung-Soo
AU - Chu, Won-Shik
AU - Yang, Jinkyu
AU - Bhandari, Binayak
AU - Lee, Choon-Man
AU - Ihn, Jeong-Beom
AU - Ahn, Sung-Hoon
N1 - Publisher Copyright:
© 2018, The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - 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.
AB - 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.
KW - n/a OA procedure
KW - Machine health management
KW - Smart factory
KW - Virtual factory
KW - Cloud manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85045743884&partnerID=8YFLogxK
U2 - 10.1007/s12206-018-0201-1
DO - 10.1007/s12206-018-0201-1
M3 - Review article
SN - 1738-494X
VL - 32
SP - 987
EP - 1009
JO - Journal of Mechanical Science and Technology
JF - Journal of Mechanical Science and Technology
IS - 3
ER -
