Predictive Modeling Tools for Metal-Based Additive Manufacturing: A Composable Simulation Model for Metal Powder-bed Fusion Additive Manufacturing Processes

Additive manufacturing lacks efficient, composable physics-based computational frameworks to predict quality and performance for arbitrary geometry, orientation, location and process parameter combinations. A new set of composable computational tools capable of accurately predicting the geometrical accuracy, residual stress and microstructure of the parts made using metal based AM has been developed. The tool(s) demonstrate scaling and composability of models to support geometry-independent reusability while providing a range of parameter values (e.g. user-defined build orientation, laser power, scan speed, hatch pattern, recoat time, material properties, powder layer thickness, choice of mesh motifs, and more) supporting reliability and accuracy.