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This work was supported by National Natural Science Foundation of China (Grant Nos. 61773386, 61573366), and National Key RD Program of China (Grant No. 2018YFB1306100).
Appendixes A–C.
[1] Zhang Z X, Si X S, Hu C H. Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods. Eur J Operational Res, 2018, 271: 775-796 CrossRef Google Scholar
[2] Wang Z Q, Wang W B, Hu C H. A Prognostic-Information-Based Order-Replacement Policy for a Non-Repairable Critical System in Service. IEEE Trans Rel, 2015, 64: 721-735 CrossRef Google Scholar
[3] Nakagawa T, Osaki S. Optimum ordering policies with lead time for an operating unit. RAIRO-Oper Res, 1978, 12: 383-393 CrossRef Google Scholar
[4] Armstrong M J, Atkins D R. Joint optimization of maintenance and inventory policies for a simple system. IIE Trans, 1996, 28: 415-424 CrossRef Google Scholar
[5] Elwany A H, Gebraeel N Z. Sensor-driven prognostic models for equipment replacement and spare parts inventory. IIE Trans, 2008, 40: 629-639 CrossRef Google Scholar
[6] Louit D, Pascual R, Banjevic D. Condition-based spares ordering for critical components. Mech Syst Signal Processing, 2011, 25: 1837-1848 CrossRef ADS Google Scholar
[7] Si X S, Wang W B, Hu C H. Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process. IEEE Trans Rel, 2012, 61: 50-67 CrossRef Google Scholar
[8] Chow S M, Ferrer E, Nesselroade J R. An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models.. Multivariate Behaval Res, 2007, 42: 283-321 CrossRef PubMed Google Scholar
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