Paper Info
Title
Dynamic Reliability Assessment for Multi-State Systems Utilizing System-Level Inspection Data
Abstract
Traditional time-based reliability assessment methods evaluate the reliability of a multi-state system (MSS) from a population or a statistical perspective that the reliability of a system is computed purely based upon historical time-to-failure data collected from a large population of identical components or systems. These methods, however, fail to characterize the stochastic behaviors of a specific individual system. In this paper, by utilizing system-level observation history, a dynamic reliability assessment method for MSSs is put forth. The proposed recursive Bayesian formula is able to dynamically update the reliability function of a specific MSS over time by incorporating system-level inspection data. The dynamic reliability function, state probabilities, and remaining useful life distribution of an MSS in residual lifetime are derived for two common cases: the degradation of components follows a homogeneous continuous time Markov process, and a non-homogeneous continuous time Markov process. The effectiveness and accuracy of the proposed method are demonstrated via two numerical examples.
Year
DOI
Venue
2015
10.1109/TR.2015.2418294
Reliability, IEEE Transactions  
Keywords
Field
DocType
dynamic reliability assessment,multi-state system,remaining useful life,system-level inspection data,history,computational modeling,reliability,degradation,inspection,markov processes
Population,Residual,Markov process,Homogeneous,Dynamic reliability,Statistics,Mathematics,Recursion,Reliability engineering,System level,Bayes' theorem
Journal
Volume
Issue
ISSN
PP
99
0018-9529
Citations 
PageRank 
References 
11
0.53
21
Authors
4
Name
Order
Citations
PageRank
Yu Liu119019.09
Ming J. Zuo293176.20
Yanfeng Li313510.93
Hong-Zhong Huang458358.24