Utilization of tomography data for process improvement in additive manufacturing through cross-correlation with real time monitoring data
Résumé
Additive Manufacturing (AM) parts are often subject to defects which are induced from one or more undesirable variations in the process parameters. The process monitoring data are available from the machines but there is a lack of strategies about how this can be used in a meaningful way. Thanks to X-ray tomography techniques, which provides holistic volumetric information in a non-destructive way, the monitoring data could be utilized for cross-correlation and eventually for process improvement. In this work, we present a methodology to establish cross-correlation between real time process monitoring data and CT characterization data. We have developed a software module within CIVA framework, which is being validated on a number of AM applications with metallic parts (Directed Energy Deposition) as well as polymeric parts.
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