Sequential selection for accelerated life testing via approximate Bayesian inference
Sequential selection for accelerated life testing via approximate Bayesian inference
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DOI：
10.1002/nav.22009
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发表时间：
2020-01
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通讯作者：
Ye Chen;Qiong Zhang;Mingyang Li;Wenjun Cai
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文献类型：
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作者：
Ye Chen;Qiong Zhang;Mingyang Li;Wenjun Cai
加速寿命测试 (ALT) 通常用于评估材料在所需应力水平下寿命的可靠性。材料工程的最新进展使得各种材料设置变得容易使用。一个关键问题是如何有效地进行 ALT 以优化不同材料设置下的可靠性性能。我们提出了一种顺序选择方法来解决这个问题。所提出的方法包含（1）模型更新机制，在每个步骤中纳入新的实验数据，以及（2）指导新实验的设计标准，最大限度地发挥找到最佳材料设置的潜力。为了保证信息收集的易处理统计机制，我们通过近似贝叶斯推理开发了显式模型参数更新公式。理论表明，我们的显式更新公式给出了一致的参数估计。为了保证每个步骤中的设计准则都能对最佳材料设置的识别做出改进，本文采用基于预期改进的设计准则来优化目标应力因子水平下的材料设置。我们还对该设计标准给出了启发式方法，以证明近似贝叶斯估计的统计一致性。仿真研究和案例研究表明，与其他设计方法相比，所提出的顺序选择方法可以显着提高识别具有最佳可靠性性能的材料替代品的概率。
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 settings readily available. A critical question is how to efficiently conduct ALT to optimize reliability performance over different material settings. We propose a sequential selection approach to solve this problem. The proposed approach contains (1) a model updating mechanism to incorporate new experimental data in each step, and (2) a design criterion to guide new experiments that maximizes the potential to find the optimal material setting. To guarantee a tractable statistical mechanism for information collection, we develop explicit model parameter update formulas via approximate Bayesian inference. Theories show that our explicit update formulas give consistent parameter estimates. To guarantee that the design criterion in each step can make improvement on the identification of optimal material setting, this paper adopts an expected improvement‐based design criterion for optimizing the material setting under target stress factor levels. We also give a heuristic on this design criterion to justify the statistical consistency of approximate Bayesian estimates. Simulation studies 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 compared to other design approaches.