(Georgia Institute of Technology, 2016-09-09)
Brough, David
The search for optimal manufacturing process routes that results in the combination of desired properties for any application is a highly dimensional optimization problem due to the hierarchical nature of material structure. Yet, this problem is a key component to materials design. Customized materials data analytics provides a new avenue of research in the efforts to address the challenge described above, while accounting for the inherently stochastic nature of the available data. The analytics mine and curate transferable, high value, materials knowledge at multiple length and time scales. More specifically, this materials knowledge is cast in the form of Process-Structure-Property (PSP) linkages of interest to the design/manufacturing experts. The extension of the novel Materials Knowledge Systems (MKS) framework to Process-Structure linkages holds the exciting potential to development full PSP linkages that can be can be leveraged by experts in data science, manufacturing and materials science and engineering communities. PSP linkages are an essential component in the to realize a modern accelerated materials innovation ecosystem. This work describes the methodologies used to extend the MKS framework to Process-Structure linkages and demonstrates their utility.