Distinguishing between uncertainty and variability in nondestructive evaluation

Abstract

In nondestructive evaluation (NDE), measurement outputs usually involve different sources of variability such as operator variation, flaw-morphology variation, setup and calibration variation, environmental related variations, and measurement error. If an appropriate experiment is conducted, it is possible to estimate the separate effects of different sources of variability. These sources of variability imply that the Probability of Detection (POD) itself is random depending, for example, on the operator assigned to do the inspection. Traditional POD analysis has focused on the estimation of the mean of the POD distribution (i.e., estimating a POD averaged over the different sources of variability reflected in the data), also providing an associated 95% lower confidence bound to reflect statistical uncertainty (i.e., uncertainty due to limited data). Focusing on mean POD obscures the process variability and has the potential to provide an overly optimistic impression of POD when there is considerable variation. An alternative, commonly used in other areas of statistical analysis, such as product reliability, is to make inferences on a lower quantile of the distribution. In this paper, we emphasize the important difference between mean POD and quantile POD and provide guidance about when they should be used.