Abstract

Accelerated life testing (ALT) is a commonly used experiment in industries for assessing a product’s lifetime. Planning a proper test with consideration of possible constraints on randomization is important because the prediction accuracy highly depends on the test plan. In this article, an optimal ALT test plan with multiple sources of random effects is demonstrated. Specifically, we consider two types of random effects caused by subsampling and blocking, and the experimental design consists of a crossed experimental factor – supplier, as well as a nested experimental factor – test chamber. The D-optimal ALT test plan is derived via a quasi-likelihood approach. An optimization algorithm with three iterative steps is developed to determine testing stress conditions, chamber assignments, and the number of test units for each testing condition and their supplier sources. The resulting test plans assign test units to chambers such that the effect of stress factor will not confound with the effect of test chamber and a similar number of test units from different suppliers will be required for each test condition.

摘要

加速寿命测试 (ALT) 是工业中用于评估产品寿命的常用实验。考虑到随机化的可能限制来规划适当的测试很重要，因为预测准确性高度依赖于测试计划。在本文中，演示了具有多个随机效应来源的最佳 ALT 测试计划。具体来说，我们考虑了二次抽样和阻塞引起的两种随机效应，实验设计包括一个交叉的实验因素——供应商，以及一个嵌套的实验因素——测试室。D _- 最佳 ALT 测试计划是通过准似然方法得出的。开发了一种具有三个迭代步骤的优化算法，以确定测试压力条件、腔室分配以及每个测试条件及其供应商来源的测试单元数量。由此产生的测试计划将测试单元分配给腔室，这样应力因子的影响不会与测试腔室的影响相混淆，并且每个测试条件都需要来自不同供应商的相似数量的测试单元。