System-reliability confidence-intervals for complex-systems with estimated component-reliability
System-reliability confidence-intervals for complex-systems with estimated component-reliability
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DOI：
10.1109/24.693781
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发表时间：
1997-12-01
影响因子：
5.9
通讯作者：
Coit, DW
中科院分区：
文献类型：
--
作者：
Coit, DW
一个灵活的过程中描述和证明，以确定系统可靠性的近似置信区间时，有不确定性的组件可靠性信息。该方法是强大的，并适用于许多系统的设计配置和组件的故障时间分布，从而在使用这些置信区间的限制很少。该方法不需要任何参数假设的组件的可靠性或故障时间，并允许I型或II型删失数据记录。置信区间基于组件和系统可靠性估计的方差以及系统可靠性估计的对数正态分布假设。这种方法适用于任何可以分解为组件之间的串联和/或并联连接的系统设计。为了评估置信限的有效性，对具有不同数据样本量和置信水平的两个假设系统进行了大量模拟。测试案例和实证结果表明，这种新的方法估计置信区间提供了良好的覆盖面，可以很容易地应用，只需要最小的计算工作量，并适用于更大范围的设计配置和数据类型相比，其他方法。对于许多设计问题，这些置信区间是优选的，因为不需要指数失效时间分布，部件数据也不限于二项数据。
A flexible procedure is described and demonstrated to determine approximate confidence intervals for system reliability when there is uncertainty regarding component reliability information. The approach is robust, and applies to many system-design configurations and component time-to-failure distributions, resulting in few restrictions for the use of these confidence intervals. The methods do not require any parametric assumptions for component reliability or time-to-failure, and allows type-I or -II censored data records. The confidence intervals are based on the variance of the component & system reliability estimates and a lognormal distribution assumption for the system reliability estimate. This approach applies to any system design which can be decomposed into series and/or parallel connections between the components. To evaluate the validity of the confidence limits, numerous simulations were performed for two hypothetical systems with different data sample-sizes and confidence levels. The test cases and empirical results demonstrate that this new method for estimating confidence intervals provides good coverage, can be readily applied, requires only minimal computational effort, and applies for a much greater range of design configurations and data types compared to other methods. For many design problems, these confidence intervals are preferable because there is no requirement for an exponential time-to-failure distribution nor are component data limited to binomial data.