Large batch metrology on internal features of additively manufactured parts using X-ray computed tomography

Abstract

Additive manufacturing (AM) can produce complex geometries, resulting in features that can be hidden or obscured, and the measurement of these features is important for many applications. X-ray computed tomography (CT) is the only non-destructive inspection technique capable of measuring internal features that are inaccessible to optical or tactile measurements; however, batch processing of CT data can be challenging and time consuming. There is a need to develop efficient CT measurement strategies to better understand how the accuracy of internal geometries varies across different parts, processes, and materials. This study presents an automated method for batch CT metrology using open-source software, and investigates 48 nozzle parts made using 11 polymer materials and 3 AM processes. The nozzles have features critical to performance, including internal channels whose measurement would otherwise require destructive evaluation. The parts are measured using CT and the data is automatically processed, resulting in over 1000 measurements per part. The deformations that occur during manufacturing result in highly nonuniform variability within the parts, and features have significantly different accuracies depending on whether the features are located on the interior or exterior of the part. Part-to-part variability is low within a batch of parts made from a single material, generally within 35 µm. However, part variability changes significantly between materials, even when the parts are made using the same process. The research demonstrates measurement results and insights enabled by large batch CT metrology of AM parts with internal features, as well as the need to monitor part-to-part variability.