Probability of detection of minute defects by ultrasonic automated testing equipment in view of Bayesian inference

Abstract

AbstractThe method of Bayesian analysis of confidence in the testing evidence collected during ultrasonic automated testing of high quality aluminum ingots for minute defects of sub-millimeter size is discussed. These test results are assessed in the view of true or false evidence. The analysis demonstrates the significant influence of false evidence on the confidence in the test outcome where the evidence is skewed in the direction of false positive. At the same time the influence of the false negative evidence is shown to be more muted. To minimize the risk of false rejection of ingots with “ghost” indications not representing the physical defects, the off-line ingot retesting by an A-scan with defect waveform verification is implemented. Retesting of fabricated blanks made of the ingots previously passed the ingot testing is used to minimize the risk of passing products with defects earlier undetected.