USING DEGRADATION MEASURES TO ESTIMATE A TIME-TO-FAILURE DISTRIBUTION
USING DEGRADATION MEASURES TO ESTIMATE A TIME-TO-FAILURE DISTRIBUTION
复制标题
DOI：
10.2307/1269661
复制
发表时间：
1993-05-01
期刊：
影响因子：
2.5
通讯作者：
MEEKER, WQ
中科院分区：
文献类型：
--
作者：
LU, CJ;MEEKER, WQ
一些寿命测试很少或根本没有失败。在这种情况下，很难通过仅记录故障时间的传统寿命测试来评估可靠性。对于某些设备，可以获得随时间推移的退化测量结果，并且这些测量结果可能包含有关产品可靠性的有用信息。即使很少或没有审查，分析退化数据也可能具有重要的实际优势。如果根据指定的退化级别来定义故障，则退化模型定义特定的故障时间分布。通常不可能获得该分布的封闭式表达式。这项工作的目的是开发统计方法，使用退化测量来估计一大类退化模型的故障时间分布。我们使用非线性混合效应模型并开发基于蒙特卡罗模拟的方法来获得可靠性评估的点估计和置信区间。
Some life tests result in few or no failures. In such cases, it is difficult to assess reliability with traditional life tests that record only time to failure. For some devices, it is possible to obtain degradation measurements over time, and these measurements may contain useful information about product reliability. Even with little or no censoring, there may be important practical advantages to analyzing degradation data. If failure is defined in terms of a specified level of degradation, a degradation model defines a particular time-to-failure distribution. Generally it is not possible to obtain a closed-form expression for this distribution. The purpose of this work is to develop statistical methods for using degradation measures to estimate a time-to-failure distribution for a broad class of degradation models. We use a nonlinear mixed-effects model and develop methods based on Monte Carlo simulation to obtain point estimates and confidence intervals for reliability assessment.