
Measurement outputs from a nondestructive testing (NDT) inspection system usually involve different sources of variability such as operator variation, probe or transducer 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 and transducer assigned to do the inspection. The commonly-used traditional statistical techniques for estimating POD provide an estimate of the mean of the POD distribution. That is, the traditional techniques provide an estimate of the POD that one would obtain by averaging over all of the different sources of variability captured by the POD experiment. This focus on mean POD (and its associated lower confidence bound) ignores inspection variability and has the potential to provide an overly optimistic impression of POD when there is considerable variation. In this paper, the authors describe an extension to the traditional reporting of mean POD that accurately reflects NDT variability and the risk of having an inspection that will have poor performance.
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