In recent years, more attention has been paid prominently to accelerated degradation testing in order to characterize accurate estimation of reliability properties for systems that are designed to work properly for years of even decades. %In this regard, degradation data from particular testing levels of the stress variable(s) are extrapolated with an appropriate statistical model to obtain estimates of lifetime quantiles at normal use levels. In this paper we propose optimal experimental designs for repeated measures accelerated degradation tests with competing failure modes that correspond to multiple response components. The observation time points are assumed to be fixed and known in advance. The marginal degradation paths are expressed using linear mixed effects models. The optimal design is obtained by minimizing the asymptotic variance of the estimator of some quantile of the failure time distribution at the normal use conditions. Numerical examples are introduced to ensure the robustness of the proposed optimal designs and compare their efficiency with standard experimental designs.
翻译:近年来,对加速降解测试给予了更多的重视,以便准确估计那些设计为在甚至几十年内正常运行的系统的可靠性特性。% 在这方面,对压力变量特定测试水平的降解数据进行外推,并采用适当的统计模型,以获得正常使用水平的终身孔数估计数。在本文件中,我们建议对重复措施的加速降解测试进行最佳实验设计,采用与多种反应成分相对应的相互竞争的失败模式;假设观测时间点是固定的,并事先知晓。边际降解路径使用线性混合效应模型表示。最佳设计是通过尽可能减少正常使用条件下某些故障时间分布点的估测器的不相称差异而获得的。引入了数字实例,以确保拟议的最佳设计具有稳健性,并将其效率与标准实验设计进行比较。