Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control

Beginning in FY25, NAVSEA will begin permanently fielding both polymer and metal Additive Manufacturing (AM) equipment under an outfitting program to augment self-sufficiency and organic manufacturing capabilities, which are increasingly important when operating in contested logistics environments. Additionally, AM processes are being used increasingly within the Maritime Industrial Base to address part obsolescence substantial demand increases as well as other critical supply chain issues. However, there is inherent variability among AM machines, even those using the same AM processing modality. As a result, the task of ensuring quality and developing sufficient evidence to support the acceptance of an AM part, especially those addressing high-criticality applications, becomes time-consuming and expensive, which negatively affects the logistics benefits that the use of AM sought to realize. Developing the solution proposed by Senvol under this SBIR Phase II project reach-back would allow the Navy to implement a standardized procedure for assessing AM parts for quality acceptance and installation using data-driven machine learning algorithms that provide insights needed to achieve target mechanical performance requirements. The solution would enable qualified, equivalent AM parts from a more flexible and scalable AM supply base, both organic and commercial, without the need for costly and time-consuming qualification and testing. Furthermore, there are several ongoing projects to collect in-situ monitoring data, but lack of a consistent approach to analyzing that data and developing actionable guidance from it. The solution offered by the proposed work will bring the Navy closer to addressing that need and enabling the use of in-situ data for part acceptance by integrating in-situ requirements into NAVSEA policy.