Active Part Filtering for Additive Manufacturing Candidate Identification

Cornerstone Research Group, Inc. (CRG) proposes to develop an additive manufacturing candidate identification (AMCI) tool which automatically processes technical data packages, applies part filtering/assessment methods to score the part against a list of additive manufacturing criteria, and categorizes parts according to their suitability for additive manufacturing. This tool will feature a continuously tuned machine learning prediction component to produce assessment metrics directly from technical data package information. As the tool is used, prediction capability will grow as expert judgments are incorporated until fully automated assessments are possible with suitable accuracy. CRG’s research institution partner, The Pennsylvania State University (PSU), will formulate the core filtering and assessment methodology for CRG’s implementation and automation via machine learning application. During Phase II, CRG and PSU will refine and optimize the scoring tools and algorithms developed in Phase I. CRG will develop a fully functional cloud-based software prototype and demonstrate usability and accuracy to the Navy.