There's a lot of buzz right now about employing additively made parts in high-performance applications and about material characterization for additive manufacturing Austin TX. Confidence levels in such parts are low due to a lack of publicly available high-fidelity additive manufacturing (AM) material characteristics data, posing a technological hurdle to the broad usage of this technique. A large number of AM machine manufacturers, a large number of process variables, the evolution of machine control software/hardware versions, and the lack of standard measurement methods and test protocols for AM materials make developing consensus materials property data with a good pedigree difficult and extremely expensive for private industry. Individual companies are now using case-by-case homemade methodologies or existing material standards that are neither AM-specific nor necessarily AM-appropriate. To qualify and quantify the unique attribute, we are developing novel characterization methods to supplement or replace established material characterization methods.
Objective: Deliver new standardized feedstock and AM-built material characterization methodologies, exemplar data, and databases to help designers and users of additive manufacturing parts in high-performance applications create and use parts faster (e.g., critical parts in high-stress applications such as turbine blades or engine components).
Technical Concept: To enable widespread use of AM technology for high-performance applications, new measuring methods, protocols, exemplar data, and AM material databases are required. There are already standardized methods for characterizing metal powders (from the powder metallurgy sector) and mechanical properties of metal pieces. These approaches, however, are limited in their applicability to AM components and powders. These existing methods can be used to build new, AM-specific characterization methods and protocols that will supplement or replace traditional material characterization methods to define and quantify the unique properties of AM materials. Data on exemplar AM materials will be made publicly available to assist technology developers and end-users in improving their process models and optimizing process parameters, resulting in increased confidence in AM processes and materials.
To qualify and quantify the unique feature of AM materials, we plan to create new characterization methods that augment or replace established feedstock and material characterization methods. The limits of traditional approaches in AM applications will be assessed first. The new approaches will be developed and applied to feedstock used in additive manufacturing processes as well as AM-built materials, with a focus on high-priority materials of particular importance to the aerospace sector. The mechanical properties of AM-built materials will be investigated using the characteristics of feedstock materials (metal powders). The influence of AM process parameters on the mechanical characteristics of AM-built materials will also be studied.
The above-mentioned empirical investigations, as well as well-designed round-robin studies with diverse high-priority materials, will provide exemplary data. This information will be utilized to look at the links between process factors and material performance in greater depth. The influence of process factors, machinery, and construction conditions on variations in material properties will be investigated. All traceable measurements of the process and the produced components will be curated in a high-fidelity AM material property database that will be publically accessible for future study and use, along with all other relevant information. Material Characterisation Facilities Austin TX can aid during the process.
