DocumentCode :
74939
Title :
A Generalized Result for Degradation Model-Based Reliability Estimation
Author :
Xiao-Sheng Si ; Donghua Zhou
Author_Institution :
Dept. of Autom., Xi´an Inst. of High-Tech, Xi´an, China
Volume :
11
Issue :
2
fYear :
2014
fDate :
Apr-14
Firstpage :
632
Lastpage :
637
Abstract :
Reliability estimation based on degradation model is a feasible and low-cost alternative used to estimate reliability for highly reliable systems when the failure-time data are rare. Based on reliability estimation by degradation modeling, preventive maintenance work orders need to be timely triggered to minimize unscheduled downtime. In Trans. Autom. Sci. Eng., vol. 9, no. 1, pp. 209-212, Jan. 2012, Sun et al., an approach to dynamically extract maintenance threshold is presented for maintenance scheduling, in which the reliability threshold for maintenance is determined by maximizing the expected availability and the reliability estimation is achieved by a modified two-stage degradation modeling approach. Although this approach is novel and useful, its reliability estimation is an asymptotic solution in long time scale. In this paper, we generalize the above result by considering a general degradation path model and provide the exact and explicit formulation for reliability estimation. Additionally, a maximum-likelihood estimation method for parameters in the presented model is proposed based on the historical degradation observations. Finally, an example is provided for illustration.
Keywords :
maximum likelihood estimation; parameter estimation; preventive maintenance; reliability; scheduling; asymptotic solution; degradation model-based reliability estimation; expected availability; general degradation path model; historical degradation observations; maintenance scheduling; maintenance threshold extraction approach; maximum likelihood estimation method; modified two-stage degradation modeling approach; parameter estimation; preventive maintenance work orders; Brownian motion; degradation; reliability;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2013.2260740
Filename :
6519286
Link To Document :
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