Simulation-based Uncertainty Correlation Modeling in Reliability Analysis

Khosravi F, Müller M, Glaß M, Teich J (2018)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2018

Journal

Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability Professional Engineering Publishing Ltd.

Book Volume: 232

Pages Range: 725-737

Journal Issue: 6

URI: https://journals.sagepub.com/doi/abs/10.1177/1748006X18758720

DOI: 10.1177/1748006X18758720

Abstract

Due to destructive effects like temperature and radiation, today’s embedded systems have to deal with unreliable components. The intensity of these effects depends on uncertain aspects like environmental or usage conditions such that highly safety-critical systems are pessimistically designed for worst-case mission profiles. These uncertain aspects may affect several components simultaneously, implying correlation across uncertainties in their reliability. This paper enables a state-of-the-art uncertainty-aware reliability analysis technique to consider multiple arbitrary correlations, i. e. components’ reliability is affected by several uncertain aspects to different degrees. This analysis technique combines reliability models such as binary decision diagrams with a Monte Carlo simulation, and derives the uncertainty distribution of the system’s reliability with insights on mean, quantile intervals, etc. The proposed correlation
method aims at generating correlated samples from the uncertainty distribution of components’ reliability such that the shape and statistical properties of each individual distribution remain unchanged. Experimental results confirm that the proposed correlation model enables the employed uncertainty-aware analysis to accurately calculate uncertainty at system level.

Authors with CRIS profile

Faramarz Khosravi Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design) Jürgen Teich Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)

Involved external institutions

Universität Ulm DE Germany (DE)

How to cite

APA:

Khosravi, F., Müller, M., Glaß, M., & Teich, J. (2018). Simulation-based Uncertainty Correlation Modeling in Reliability Analysis. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 232(6), 725-737. https://doi.org/10.1177/1748006X18758720

MLA:

Khosravi, Faramarz, et al. "Simulation-based Uncertainty Correlation Modeling in Reliability Analysis." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 232.6 (2018): 725-737.

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