FA864921P1657

Small Business Innovation Research Program (SBIR) Phase II

Intelligent Process Control for Additive Manufacturing

Digital Engineering Pitch Day

Additive Manufacturing (AM)'s shorter production lead-times allow for parts to be made on-demand and on-site fitted to aircraft, reducing maintenance time. However, AM part reliability has more variability compared to traditionally manufactured (TM) parts, typically due to latent and residual thermal stresses. IFOS is developing an innovative integrated in-situ and real-time advanced process control (R-APC), advanced equipment control (AEP, and advanced process optimization (APO) system AM*Sense that incorporates artificial intelligence (AI), machine learning (ML, and high resolution distributed 4D (temporal/spatial) sensing (temperature, vibration, pressure) and mapping, along with thermal imaging to monitor, optimize, and control print process, equipment, and parts, minimizing variability and failures. IFOS' multifunctional sensing approach overcomes the technology gap between conventional sensors and the need for high-quality process data by incorporating AI/ML monitoring and control systems, that would complement IFOS EMI/RFI-immune, cybersecure sensors to optimize the print process across materials. AM*Sense's control system will enable real-time optimization of process parameters to ensure consistent physical properties and strength of printed parts. In Phase II, IFOS and collaborator Colorado School of Mines' Alliance for Development of Additive Processing Technologies (ADAPT) will demonstrate an engineering prototype of AM*Sense along with Air Force Materiel Command (AFMC) and practical plan for transitioning.

The goal of phase II is to continue the R&D efforts initiated in Phase I. Funding is based on the results achieved in Phase I and the scientific and technical merit and commercial potential of the project proposed in Phase II.

AF203-DCSO3

F2D-1386

X20.3

Dr. Behzad Moslehi