| Abstract Scope |
Powder bed fusion laser-based (PBF-LB) additive manufacturing (AM) technology demonstrates its strength in building near-net-shape products. Still, this voxel-to-voxel process requires an extended processing time, which increases the cost of mass production. An in-process indicator to evaluate the product properties can assist in identifying the defective AM process and stopping the remaining AM processing steps. To create the linkages of processing-microstructure-properties relations, we design a digital twin (DT) development process in three stages: (1) data preparation and data quality evaluation, (2) model development and integration, and (3) credibility assessment. The intersection of these three areas is the standard data management procedure. A practical application of physics, a simulation library that connects the metadata store of AM Bench 2022, will be introduced. The presentation will demonstrate the critical concepts and tools for developing this DT example. I will also emphasize the importance of standard data models to future developments. |