Improved AM quality using analytics on low-cost, COTS, in situ sensor data

Premature field-failures of Additive Manufacturing (AM) produced parts, intended for use in a variety of mission-critical industrial, military and aerospace applications, could lead to catastrophic consequences. Detecting emerging out-of-tolerance conditions using a multitude of low-cost, in situ process sensors, and applying mathematical algorithms to provide real-time operator feedback could significantly improve the AM process quality and hence better Qual & Cert of AM parts. This SBIR project will develop an innovative, open-architecture, extensible, computer-based technology product called SDC-SPMR. With this objective, a Phase I project is proposed with a goal of developing a proof-of-concept product, as the basis for an innovative solution. The Phase I effort will also include the feasibility study of significantly improve AM process and the resulting AM part quality by using low-cost sensors and proven analytical approaches. SDC-SPMR product (that can be embedded in any COTS AM machine) will enable AM machine operators to make fine-grained process adjustments to ensure defect free and highly reliable AM part production. The R&D team consists of firms’ technologists with decades of machine automation, control systems and Six-sigma quality improvement expertise, and technologists from EWI, who is a well-known organization with expertise in the advanced AM machines and AM processes.