Abstract: Modern foundries are striving to find ways to use vast amounts of production data to support knowledge based systems that can provide closed-loop feedback to enhance the cast product quality through the elimination of casting defects. Detection and characterization of internal defects, such as porosity, by non-destructive evaluation (NDE) techniques will be a critical element in the process to provide rapid product quality feedback to the system. Advances in computed tomography (CT) have greatly improved the capability and efficiency of detection and reconstruction of defects in Al castings. The NDE data, along with floor operation and processing data, as well as simulation tools of the casting and solidification process, will be integral components of a data fusion framework for continuous process learning to mitigate and alleviate casting defects.
Authors: N. Sun, C. Dai, V. Alreja, and D. Apelian
Keywords: X-Ray CT, NDE, Casting Process Cognition Development