Additive manufacturing (AM) technologies have seen rapid advancement in the space sector, evolving from tools for rapid prototyping to enabling the production of innovative products and functional components. A notable trend in this evolution is the increasing capability to fabricate large-format parts, driven by the development of new AM solutions and expanded build volumes. In recent years, growing attention has been focused not only on using large-format AM capabilities on Earth to manufacture space systems, but also on deploying them directly in space to address the challenges of emerging space economy scenarios. In both cases, large-scale AM shall guarantee high structural and functional properties, ensuring repeatability and process stability. This is even more relevant for in-space manufacturing applications, where the system shall operate autonomously, and quality inspections are severely limited by space environment constraints. To address these issues, smart AM systems with first-time-right production capabilities are emerging as a promising solution. In this context, we present a new perspective on the integration of in-situ and in-line sensing methods combined with big data modelling and monitoring specifically design for large-scale AM processes that utilize robotic extrusion of composite materials. Continuous, real-time monitoring of material deposition at each layer enables the automatic detection of deviations from the intended deposition patterns, such as over-extrusion and surface irregularities, paving the way toward zero-defect manufacturing. The study presents preliminary results achieved on Earth. It also outlines a roadmap for adapting and developing smart in-situ monitoring and control solutions for adoption in space, targeting a fully autonomous in-space AM robotic cell to support space utilization and exploration missions.

In-situ monitoring of Large Scale Additive Manufacturing for on-Earth and in-Space applications

Fabio Caltanissetta;Marco Grasso;Giovanni Avallone;Bianca Maria Colosimo
2025-01-01

Abstract

Additive manufacturing (AM) technologies have seen rapid advancement in the space sector, evolving from tools for rapid prototyping to enabling the production of innovative products and functional components. A notable trend in this evolution is the increasing capability to fabricate large-format parts, driven by the development of new AM solutions and expanded build volumes. In recent years, growing attention has been focused not only on using large-format AM capabilities on Earth to manufacture space systems, but also on deploying them directly in space to address the challenges of emerging space economy scenarios. In both cases, large-scale AM shall guarantee high structural and functional properties, ensuring repeatability and process stability. This is even more relevant for in-space manufacturing applications, where the system shall operate autonomously, and quality inspections are severely limited by space environment constraints. To address these issues, smart AM systems with first-time-right production capabilities are emerging as a promising solution. In this context, we present a new perspective on the integration of in-situ and in-line sensing methods combined with big data modelling and monitoring specifically design for large-scale AM processes that utilize robotic extrusion of composite materials. Continuous, real-time monitoring of material deposition at each layer enables the automatic detection of deviations from the intended deposition patterns, such as over-extrusion and surface irregularities, paving the way toward zero-defect manufacturing. The study presents preliminary results achieved on Earth. It also outlines a roadmap for adapting and developing smart in-situ monitoring and control solutions for adoption in space, targeting a fully autonomous in-space AM robotic cell to support space utilization and exploration missions.
2025
large-format, additive manufacturing, in-situ monitoring, space, in-space manufacturing
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1304568
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact