Abstract Scope |
Recent efforts to extend additive process monitoring and improve part quality have focused on the creation and verification of digital twins. The implementation of digital twins in additive manufacturing is complex, because many process variables of interest, such as internal part temperatures, are not directly observable. The first step in the creation of a comprehensive digital twin for metal inert gas additive manufacturing is the tuning and certification of thermal and geometric models using measured print data. The presented 4D data processing approach (x,y,z, and time) allows collected process data from temperature, geometry, energy input, energy output, and material deposition sensors to be applied to any unknown model without the need to rerun experiments. Example data was collected and processed, and unexpected benefits and challenges for the data collection methods are discussed. |