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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Recommended by Editor Hyung Wook Park
Gil-Yong Lee received the B.S., M.S. and Ph.D. degrees from Seoul National University, Seoul, Korea in 2006, 2008, and 2013, respectively. After graduations, he conducted his research at the University of Washington, Seattle, WA from 2013 to 2016. Currently he is a Research Assistant Professor in the Institute of Advanced Machines and Design (IAMD) at the Seoul National University, Seoul, Korea. His research interests are in direct printing, nanoparticle printer, rapid prototyping, micro/nano fabrication, soft actuators and sensors, energy devices, composites, and acoustic metamaterials.
Sung-Hoon Ahn received the B.S. degree from University of Michigan, Ann Arbor, MI, USA in 1992, and M.S. and Ph.D. degrees from the Stanford University, CA, USA in 1994 and 1997, respectively. Currently, he is a Professor in the Dept. of Mechanical and Aerospace Engineering and Associate Dean in Graduate School of Engineering Practice at the Seoul National University, Seoul, Korea. His research interests include 3D Printing, Smart Soft Composite Materials, micro/ nano-scale fabrication (Laser, focused ion beam, milling drilling, and Nano Particle Deposition System), green manufacturing, energy device, and appropriate technology.
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Lee, GY., Kim, M., Quan, YJ. et al. Machine health management in smart factory: A review. J Mech Sci Technol 32, 987–1009 (2018). https://doi.org/10.1007/s12206-018-0201-1
- Smart factory
- Machine health management
- Virtual factory
- Cloud manufacturing