In the aerospace sector, the adoption of additive manufacturing (AM) technologies has rapidly evolved, moving from rapid prototyping to the production of innovative products and functional parts. One relevant trend regards the growth of build volumes as well as the emergence of new AM solutions to produce large format parts. However, large format AM also entails a variety of new challenges that motivate continuous research and industrial developments. A key aspect regards the capability to improve repeatability, process stability and quality requirements, especially when new conditions (new materials, new shapes, new environmental conditions) need to be meet. In this framework, smart AM systems with first-time-right production capabilities represent a promising solution to overcome many barriers. We present a novel approach for in-situ and in-line sensing and big data modelling and monitoring of large-scale AM processes performed via robotic extrusion of composite components. The in-line and continuous monitoring of the material deposition in every layer allows the automatic detection of deviations from a regular deposition pattern, including over-extrusion and surface irregularities issues. This data-assisted large-scale printing can be usefully considered for process tuning and optimization in a closed-loop framework to achieve zero-defect manufacturing for on- and off-Earth applications.

New solutions for Smart Large Scale Additive Manufacturing for on-Earth and off-Earth applications

Marco Grasso;Fabio Caltanissetta;Giovanni Avallone;Bianca Maria Colosimo
2024-01-01

Abstract

In the aerospace sector, the adoption of additive manufacturing (AM) technologies has rapidly evolved, moving from rapid prototyping to the production of innovative products and functional parts. One relevant trend regards the growth of build volumes as well as the emergence of new AM solutions to produce large format parts. However, large format AM also entails a variety of new challenges that motivate continuous research and industrial developments. A key aspect regards the capability to improve repeatability, process stability and quality requirements, especially when new conditions (new materials, new shapes, new environmental conditions) need to be meet. In this framework, smart AM systems with first-time-right production capabilities represent a promising solution to overcome many barriers. We present a novel approach for in-situ and in-line sensing and big data modelling and monitoring of large-scale AM processes performed via robotic extrusion of composite components. The in-line and continuous monitoring of the material deposition in every layer allows the automatic detection of deviations from a regular deposition pattern, including over-extrusion and surface irregularities issues. This data-assisted large-scale printing can be usefully considered for process tuning and optimization in a closed-loop framework to achieve zero-defect manufacturing for on- and off-Earth applications.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1286866
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