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System Reliability Optimization Considering Uncertain Future Operating Conditions and Usage Stresses

机译：考虑不确定的未来运行条件和使用压力的系统可靠性优化

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This paper develops a new system reliability design optimization model based on a series-parallel system, where each subsystem is composed of components that are chosen to optimize the system reliability, while considering uncertainty of future usage conditions. In previous research, component reliability is generally assumed to be known with certainty because the usage and operating stresses are either not changing or they are known with certainty. However, this paper proposes a more general perspective in analyzing the uncertainty of actual system usage and operating stresses. In industry, predictions of component reliability often have inaccuracy or uncertainty due to unplanned variation, or changing environments and operating stresses. Sensitivity of particular component reliability occurs due to a relative increase/decrease of operating forces or stresses. A risk-neutral design is considered for the system reliability optimization model with a probability associated with defined possible future usage conditions. The optimal redundancy allocation problem for each subsystem is composed of multiple choices of components with system-level constraints. The system is designed to maximize expected system reliability while considering the uncertainty of future component usage conditions and stresses. Nonlinear integer programming and a neighborhood search heuristic was used to solve this new problem formulation.
机译：本文基于串联-并联系统，开发了一个新的系统可靠性设计优化模型，该模型中的每个子系统均由选择以优化系统可靠性的组件组成，同时考虑了未来使用条件的不确定性。在以前的研究中，通常假定组件可靠性是确定的，因为使用情况和操作应力或者没有改变，或者确定性是已知的。但是，在分析实际系统使用情况和操作压力的不确定性时，本文提出了一个更一般的观点。在工业中，由于计划外的变化，变化的环境和工作压力，对组件可靠性的预测通常不准确或不确定。由于操作力或应力的相对增加/减少，因此出现了特定组件可靠性的敏感性。对于系统可靠性优化模型，考虑与风险无关的设计，其概率与已定义的将来使用条件有关。每个子系统的最佳冗余分配问题由具有系统级约束的组件的多种选择组成。该系统旨在最大程度地提高预期的系统可靠性，同时考虑未来组件使用条件和压力的不确定性。非线性整数规划和邻域搜索启发式算法用于解决这一新问题。

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