I. Cozmuta, S. Alistar, R. Osan, E. Mak and M. Dieken
G-SPACE Inc, California, United States
Keywords: Microgravity Manufacturing, AI/ML Analytics, Scalable Experimentation, In-Space Production, Data-Driven Design
This presentation focuses on how the G-SPACE platform is transforming microgravity experiments from isolated scientific efforts into repeatable, scalable, and commercially viable manufacturing processes. Microgravity offers unique conditions for producing high-performance materials and biological systems, yet much of its use remains locked in single-flight, manually interpreted experiments. To unlock the full potential of space manufacturing, we need tools that can standardize, scale, and automate microgravity-based science. G-SPACE is pioneering a software first approach powered by ML trained on and tailored to microgravity data that provides analytics, algorithm libraries, and visual tools to accelerate product design, optimization and real-time decision-making. This approach moves beyond trial-and-error, supporting the creation of scalable in-space manufacturing pipelines based on predictive modeling and data-driven control. It bridges microgravity science with industrial applicability by transforming fragmented R&D efforts into standardized processes that are accessible to commercial users. We present applications across a range of domains, including advanced materials and life science applications. Part of this work is supported through multiple NASA ROSES and SBIR awards. We invite forward-looking researchers, engineers, and companies to join us in shaping a robust ecosystem of in-space manufacturing—one driven by intelligent tools, scalable processes, and real microgravity advantage.