论文标题
通过近似贝叶斯推断进行加速生命测试的顺序选择
Sequential Selection for Accelerated Life Testing via Approximate Bayesian Inference
论文作者
论文摘要
加速的生命测试（ALT）通常用于评估所需应力水平下材料寿命的可靠性。材料工程的最新进展使各种材料替代方案很容易获得。为了通过有效的实验设计确定最可靠的材料设置，首选顺序测试计划策略。为了确保信息收集和更新的可访问统计机制，我们通过近似贝叶斯推断开发明确的模型参数更新公式。理论表明，我们的显式更新公式给出了一致的参数估计。仿真研究和案例研究表明，所提出的顺序选择方法可以显着提高与其他设计方法相比，具有最佳可靠性性能的材料替代方案的可能性。
Accelerated life testing (ALT) is typically used to assess the reliability of material's lifetime under desired stress levels. Recent advances in material engineering have made a variety of material alternatives readily available. To identify the most reliable material setting with efficient experimental design, a sequential test planning strategy is preferred. To guarantee a tractable statistical mechanism for information collection and update, we develop explicit model parameter update formulas via approximate Bayesian inference. Theories show that our explicit update formulas give consistent parameter estimates. Simulation study and a case study show that the proposed sequential selection approach can significantly improve the probability of identifying the material alternative with best reliability performance over other design approaches.
