The Advantage of Machine Learning to the Inspector

NDT inspectors are highly trained professionals who have taken advantage of new inspection techniques such as phased array ultrasonics and digital radiography. While these new techniques improve the inspection result as a whole, they also produce considerable amount more data than the older analog methods. In inspections, the increased data amount usually leads to more reliable result, however this also leads to a longer inspection time. The majority of the inspector’s time is usually used to look at data where there are no indications to detect, evaluate or report. Some shortcuts such as merging and adjusting can speed up the data analysis, but they inherently destroy information. Machine learning offers the opportunity to utilize modern inspection techniques to their full extent while maintaining high reliability, repeatability and efficiency. Machine learning further enables new statistical interpretation options that combine information from numerous indications, which have been infeasible with the human inspector alone. In this paper we study different opportunities machine learning has to offer in form of data-analysis for the inspectors and how they affect the inspector’s task. These include examples from radiography and ultrasonic inspection and different ways to apply machine learning and present results to the inspector.