This research contributes to the ongoing effort toward predicting and improving reliability in early engineering design, specifically during conceptual design. Increasing the rigor of predicting reliability during early design allows the designer to improve the decision-making process. Current reliability prediction methods cannot accurately capture uncertainty during conceptual design. The uncertainty of reliability predictions in early design can be significant, and, as a result, must be utilized in decision-making. To address these limitations, this paper presents the early design reliability prediction method (EDRPM) to calculate function and component failure rate distributions, which capture the parameter uncertainty. If required, these distributions can be converted into reliability values. A new technique, Frequency Weighting, is developed and applied to a Hierarchical Bayesian model to account for the number of times that a component has historically solved a function. This addition is necessary to accurately model the structure of the function-to-component relationship for capturing uncertainty. A case study using the advanced diagnostics and prognostic testbed electrical power system is presented to show the usefulness of EDRPM in facilitating decision-making during conceptual design.

中文翻译：

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早期设计可靠性预测方法

这项研究有助于在早期工程设计中预测和提高可靠性的持续努力，特别是在概念设计期间。在早期设计中提高预测可靠性的严谨性，使设计人员能够改进决策过程。当前的可靠性预测方法无法准确捕捉概念设计过程中的不确定性。早期设计中可靠性预测的不确定性可能很大，因此必须在决策中加以利用。为了解决这些限制，本文提出了早期设计可靠性预测方法 (EDRPM) 来计算功能和组件故障率分布，从而捕获参数不确定性。如果需要，可以将这些分布转换为可靠性值。一种新技术，频率加权，开发并应用于分层贝叶斯模型，以说明组件历史上求解函数的次数。此添加对于准确建模函数与组件关系的结构以捕获不确定性是必要的。介绍了使用高级诊断和预测试验台电力系统的案例研究，以展示 EDRPM 在促进概念设计期间的决策制定方面的有用性。