In the traditional simple step-stress partial accelerated life test (SSSPALT), the items are put on normal operating conditions up to a certain time and after that the stress is increased to get the failure time information early. However, when the stress increases, an additional cost is incorporated that increases the cost of the life test. In this context, an adaptive SSSPALT is considered where the stress is increased after a certain time if the number of failures up to that point is less than a pre-specified number of failures. We consider determination of Bayesian reliability acceptance sampling plans (BSP) through adaptive SSSALT conducted under Type I censoring. The BSP under adaptive SSSPALT is called BSPAA. The Bayes decision function and Bayes risk are obtained for the general loss function. Optimal BSPAAs are obtained for the quadratic loss function by minimizing Bayes risk. An algorithm is provided for computation of optimum BSPAA. Comparisons between the proposed BSPAA and the conventional BSP through non-accelerated life test (CBSP) and conventional BSP through SSSPALT (CBSPA) are carried out.

翻译：在传统的简单步进应力部分加速寿命试验中，试件首先在正常操作条件下运行至某一特定时间，随后提高应力水平以提前获取失效时间信息。然而，应力增加会引入额外成本，从而提升寿命试验的总费用。在此背景下，本文考虑一种自适应SSSPALT方案：若在特定时间点之前观测到的失效数低于预设阈值，则在该时间点提高应力水平。我们研究了在Ⅰ型截尾条件下，通过自适应SSSPALT确定贝叶斯可靠性验收抽样方案的方法。该方案称为BSPAA。针对一般损失函数，推导了贝叶斯决策函数与贝叶斯风险。通过最小化贝叶斯风险，获得了二次损失函数下的最优BSPAA方案。本文提供了计算最优BSPAA的算法，并将所提BSPAA方案与通过非加速寿命试验的传统BSP方案以及通过SSSPALT的传统BSP方案进行了对比分析。