Innovative modelling strategies for additive manufacturing processes

A major challenge in robust AM production is the ability to predict the physical behaviour of components during manufacturing. In the project, predictability, or "predictive capability," of manufacturing-induced defects and deviations is achieved by developing numerical models. The numerical models and methods are verified and validated experimentally. The project also evaluates the application of Physics-Informed Machine Learning (PIML), which potentially strengthens the predictive capability further. The ultimate goal is to enable the manufacturing of components that are free from construction defects.

The industry's need to efficiently design for AM according to the "first time right" principle forms the basis for the project's research activities on Powder Bed Fusion-Laser Beam (PBF-LB). By combining high-resolution models at a detailed level with full-scale models at a component level, sufficient computational accuracy can be achieved for manufacturing simulation while keeping engineering and computing time at acceptable levels.

The project places great emphasis on generating validating data, from melt pool monitoring for instance. Activities connected to Physics-Informed Machine Learning (PIML) show great potential.

Industrial demonstrators where damage mechanisms occur have been identified. Based on them, common challenges for research cases at both the lab scale and component level are studied.

The innovations from the project are transferred to the industry through the embedded knowledge in the models, industrial evaluation work, research communication, and the project's meeting structure.

The project involves leading industries in additive manufacturing, researchers, simulation software providers, and machine suppliers. The project's spirit is inclusive with a range of knowledge-sharing activities through the Application Center for Additive Manufacturing (AM Center), the Swedish Arena for Additive Manufacturing of Metals (AM-Arena), international scientific conferences, and contributions to university courses at master's and doctoral levels.