||Metallic additive manufacturing (AM) technology has achieved significant advancement toward industrial maturity in recent years; however, challenges related to certification have inhibited the widespread adoption of this manufacturing capability in key industries such as transportation. For several years now, there has been a push within government and academia to establish high fidelity physically correct process models to support certification. Much advancement has been realized in the development of models toward the simulation of the metallic AM process; however, the lack of consistent and available high temperature material property and model validation data remains a roadblock. Empirical measurements are often difficult or impossible to obtain; alone, they can often only provide proof of a processing effect but not an understanding of the cause. Ideally, simulation and measurement can be coordinated to provide a complete understanding of the AM process, and increase confidence and availability in quality part properties and performance variability predictions. Such improvements are necessary to enable the implementation of cost-effective certification paradigms for load critical AM parts.
By identifying the data needs most consequential to AM process model predictions, new measurement capabilities or techniques tailored to AM can be targeted and developed. High temperature material properties data for metals are largely unavailable in literature; and, in some cases properties are available but are inconsistent between sources. Furthermore, by identifying key model validation data gaps, resources can be prioritized to enhance measurement capabilities and collect data in quantities sufficient to characterize the high variability notorious in as-built AM parts. Ensuring that the most important high quality and consistent measurements are available in a publicly available standardized database facilitates efforts toward certification and promotes the widespread adoption of additive manufacturing.
The main objective of this symposium is to bring experts and information together to discuss potential development of a standardized government facilitated material properties and model validation database to support improved process modeling predictions toward certification of additively manufactured metallic parts for load critical applications. Topics for discussion and abstract solicitations include:
- Alloys of interest for certification efforts and current data gaps
- Identification of material properties with the largest impacts on process model predictions
- Model validation data needs
- Current measurement capabilities for material properties at temperatures of interest
- Current sources of validation data (in-situ monitoring, DXR, micrographs, etc.)
- Challenges to and roadmap for the potential development for such a standardized database (IP considerations, roles and responsibilities, database formats, etc.)