Name
Title | ||
|---|---|---|
Efficient Treatment of Uncertainty in System Reliability Analysis using Importance Measures |
Abstract | ||
|---|---|---|
The reliability of today's electronic products suffers from a growing variability of failure and ageing effects. In this paper, we investigate a technique for the efficient derivation of uncertainty distributions of system reliability. We assume that a system is composed of unreliable components whose reliabilities are modeled as probability distributions. Existing Monte Carlo (MC) simulation-based techniques, which iteratively select a sample from the probability distributions of the components, often suffer from high execution time and/or poor coverage of the sample space. To avoid the costly re-evaluation of a system reliability during MC simulation, we propose to employ the Taylor expansion of the system reliability function. Moreover, we propose a stratified sampling technique which is based on the fact that the contribution (or importance) of the components on the uncertainty of their system may not be equivalent. This technique finely/coarsely stratifies the probability distribution of the components with high/low contribution. The experimental results show that the proposed technique is more efficient and provides more accurate results compared to previously proposed techniques. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/DSN.2019.00022 | 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) |
Keywords | DocType | ISSN |
Reliability, Uncertainty Analysis, Sampling, Importance Measure, System Design, Stratified Sampling | Conference | 1530-0889 |
ISBN | Citations | PageRank |
978-1-7281-0058-6 | 0 | 0.34 |
References | Authors | |
19 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hananeh Aliee | 1 | 0 | 0.34 |
| Faramarz Khosravi | 2 | 22 | 4.87 |
| Juergen Teich | 3 | 90 | 18.01 |