Digital Twin of the laser-DED process based on a multiscale approach

Abstract

The ramp-up of new geometries, process parameters, and materials can be enormously time and cost-intensive in Additive Manufacturing. Especially for Laser-Directed Energy Deposition (DED-L), the extreme physical environment at the melt pool results in the need for multiple trial-and-error tests to quantify the process behavior. These tests significantly raise manufacturing expenses. A Digital Twin (DT) of the DED-L process can therefore be of substantial value if the amount of experimental testing is hereby reduced. In the present study, a multiscale DT based on coupling a global and local model has been investigated. The global model simulates the heating of the entire part, whereas the local model represents only a specific region of this global geometry. Using a high-density mesh for the local model enables the simulation of the specific laser-powder interactions and fast-cooling rates typical in DED-L. The results of the global model are used to integrate context awareness about the changing process conditions during the print job into the local model. This process evolvement is impossible to obtain with models of smaller dimensions and is of elemental necessity for accurately simulating multi-clad depositions. The DT was validated on an industrial-grade DED-L machine with in-situ process monitoring capabilities. In all cases, the DT shows a high resemblance with the experimental data and metallographic inspections at a reasonable computational cost.