EAGER: Exploration of Data-Driven Methods for Cyber Manufacturing

This EArly-concept Grant for Exploratory Research (EAGER) project will investigate the knowledge and data-driven and cyber-enabled tools needed to link design and manufacturing, thereby enabling a cyber manufacturing marketplace that identifies the on-demand manufacturing capabilities necessary for rapid realization of product designs. Such a marketplace can democratize access to “know-how” and means of production on a massive scale, by seamlessly connecting designers with manufacturers in a broad platform of regional and global supply chains and democratizing access to manufacturing capabilities without compromising manufacturers’ “know-how” and trade secrets.

To realize this impact, it is necessary to (1) create data-driven methods to harvest knowledge of manufacturing capabilities that can transform a computer-aided design (CAD) into the desired physical product, and (2) create methods to efficiently search for this knowledge through the cyber infrastructure. The project hypothesizes that: (i) computing machines can learn the manufacturing capabilities required to transform a CAD model into the desired physical part from available design and manufacturing data, and (ii) efficient cyber-enabled search of the required manufacturing capabilities for a part design can be realized through statistical similarity-based search methods.

The hypothesis will be tested through innovative and convergent data-driven approaches that utilize expertise in computer-aided design, manufacturing science and technology, and machine learning.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.