Industrial spillover effects of generative AI-enabled in-space additive manufacturing
Abstract
In-space additive manufacturing is a key enabling technology for long-duration on-orbit operations and extra terrestrial resource utilization. This study examines the industrial spillover effects of generative artificial intelligence-enabled in-space additive manufacturing on terrestrial systems. Based on publicly available engineering cases and academic literature, a framework is developed using system analysis and multi-case theoretical sampling to explain how manufacturing capabilities formed under extreme space conditions are transferred and applied in terrestrial contexts. The findings indicate that manufacturing capabilities developed under such conditions—characterized by high reliability, strong autonomy, closed-loop operation, and traceability—can exert a reverse-driving influence on terrestrial manufacturing systems, supporting their transition toward data-driven and evidence-based processes. Generative AI further enhances this process by improving the efficiency of capability reuse and cross-context transfer, particularly within distributed intelligence architectures that combine ground-based training with space-based deployment and asynchronous iteration. On this basis, an eight-dimensional structural model of industrial spillover is proposed, capturing the progression from foundational capabilities to technological expansion and application-level transformation. The model reveals the mechanisms through which extreme space environments reshape terrestrial manufacturing systems and provides a new analytical perspective for industrial intelligent transformation and science–industry integration.
