Reliability and covariance estimation of weighted k-out-of-n multi-state systems

详细信息	查看全文 | 推荐本文 |

• 作者：Yong Wang^a ; Lin Li^a ; ^{linli@uic.edu} ; Shuhong Huang^b ; Qing Chang^c
• 关键词：Reliability estimation ; Uncertainty ; Weighted k-out-of-n system ; Multi-state system ; Universal generating function
• 刊名：European Journal of Operational Research
• 出版年：2012
• 期刊代码：58_03772217
• 类别：et
• 出版时间：16 August, 2012
• 卷：221
• 期：1
• 页码：138-147
• 文件大小：540 K

摘要

In the literature of reliability engineering, reliability of the weighted k-out-of-n system can be calculated using component reliability based on the structure function. The calculation usually assumes that the true component reliability is completely known. However, this is not the case in practical applications. Instead, component reliability has to be estimated using empirical sample data. Uncertainty arises during this estimation process and propagates to the system level. This paper studies the propagation mechanism of estimation uncertainty through the universal generating function method. Equations of the complete solution including the unbiased system reliability estimator and the corresponding unbiased covariance estimator are derived. This is a unified approach. It can be applied to weighted k-out-of-n systems with multi-state components, to weighted k-out-of-n systems with binary components, and to simple series and parallel systems. It may also serve as building blocks to derive estimators of system reliability and uncertainty measures for more complicated systems.