Probabilistic Physics of Failure (PPOF) Reliability Analysis of RF-MEMS Switches under Uncertainty

Document Type : Original Research Article

Authors

1 Sahand University of Technology

2 University of Bradford

3 Tehran Science and Research branch of Azad University

Abstract

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.

Keywords

Main Subjects

References

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International Journal of Reliability, Risk and Safety: Theory and Application
Volume 1, Issue 1 - Serial Number 1
December 2018
Pages 1-10

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History

  • Receive Date: 15 September 2018
  • Revise Date: 10 October 2018
  • Accept Date: 20 October 2018

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