不确定条件下RF-MEMS开关的概率失效物理可靠性分析

Mohammad Pourgolmohamad, Minoo Mobasher Moghaddam, Morteza Soleimani, Robab Aaghazadeh-chakherlou
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引用次数: 4

摘要

MEMS可靠性分析是一个具有挑战性的研究领域,包括各种失效物理和各种失效机制。可靠性问题在MEMS器件的设计和制造阶段都是至关重要的,因为这些问题仍然延迟了它们的商业化。在本研究中,提出了一种用于MEMS器件可靠性评估的混合方法。其第一步是通过FMEA识别主要失效模式,评估失效机制,并通过贝叶斯方法进行更新的寿命估计。利用失效概率物理(PPoF)对MEMS器件的可靠性进行了研究,确定了主要失效机制。因此,选择确定性模型对主要失效机制的寿命和可靠性进行分析。为了将确定性模型转化为概率模型,确定了影响介质寿命的不确定性源。利用蒙特卡罗方法对该模型进行了仿真。最后,利用贝叶斯方法对寿命估计结果进行更新。考虑到射频MEMS电容开关的广泛应用和优点,本文选择射频MEMS电容开关作为案例进行研究。提出了一种基于粘滞机制的开关故障可靠性评估框架。结果包括FMEA表,不同电压下的寿命估计,占空比数,最后更新了使用贝叶斯方法的寿命估计结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic Physics of Failure (PPOF) Reliability Analysis of RF-MEMS Switches under Uncertainty
MEMS reliability analysis is a challenging area of research which comprises various physics of failure and diverse failure mechanisms. Reliability issues are critical in both design and fabrication phases of MEMS devices as their commercialization is still delayed by these problems. In this research, a hybrid methodology is developed for the reliability evaluation of MEMS devices. Its first step is the identification of dominant failure modes by FMEA, evaluation of failure mechanisms and an updated lifetime estimation by the Bayesian method. The reliability of MEMS devices is studied using probabilistic physics of failure (PPoF) by determining the dominant failure mechanism. Accordingly, a deterministic model is selected for the analysis of the life and reliability of the dominant failure mechanisms. To convert the deterministic model to a probabilistic model, the uncertainty sources affecting the dielectric lifetime are determined. This model is simulated by the utilization of the Monte Carlo method. In the final stage, the results of life estimation are updated using the Bayesian method. Considering wide application and advantages of RF MEMS capacitive switches, it has been selected as a case study. A framework is developed for reliability evaluation of these switches failures due to stiction mechanism. The results contain FMEA table, lifetime estimation in different voltages, number of duty cycles and at the end, updated results of life estimation using the Bayesian method.
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