Understanding of the risk and reliability of systems can be enhanced by modeling the grayscale degradation of the performance of components and determining the grayscale impact on the system performance. Rather than producing an estimate of the probability of the system being in either the working or the failed state, as more traditional risk and reliability modeling does, this approach produces estimates of the probability of the system being in any of a continuous range of states between fully working and completely failed. In this paper, earlier work is extended by exploring the cause of major differences between this new approach and traditional reliability analysis, as well as by developing sensitivity analysis for grayscale reliability. Because the coupling effect can cause significant differences between this approach and the traditional approach, the coupling effect of component degradation is explored through the examples of coupled and decoupled mass-spring-damper systems. Also, a new sensitivity measure for grayscale reliability is developed to determine how designers can trade changes in reliability with other design criteria such as cost.

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