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Have you ever imagined printing metal objects, just like you do with a normal home printer? Laser Powder Bed Fusion (LPBF) technology already does this: a powerful laser melts layers of metal powder to create incredibly complex parts. It's like building a sandcastle, but with metal and with millimeter precision!

However, there's a catch: printing metal is extremely complicated. Even a tiny mistake can ruin the entire part. That's why scientists are using 'ensor fusion.' Imagine having a thousand electronic eyes watching everything that happens while the laser works. These sensors collect data on everything: from the heat of the melt pool to the formation of tiny sparks.

The real magic happens when an artificial intelligence combines all this data in real-time. Instead of just watching, the system can 'eact.' If it notices the heat is getting too high, it can tell the laser to slow down or decrease its power. It's like having a super-intelligent autopilot correcting the course while the plane is in flight. Thanks to these new control strategies, 3D printers will become increasingly precise, allowing us to create space components or advanced engines without any defects!

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Laser Powder Bed Fusion (LPBF) technology relies on the selective melting of metal powders using a high-energy laser beam. The process takes place inside a controlled chamber where a powder bed is spread layer by layer. The main challenge lies in thermal management: the extremely rapid heating and cooling cycle can generate residual stresses in the material, leading to micro-cracks or geometric distortions.

Recent research is shifting towards integrating advanced Deep Learning architectures, such as Transformers and Graph Neural Networks (GNN), to analyze sensor data. 'Sensor fusion' allows for the combination of thermographic data (infrared), optical data (high-speed cameras), and acoustic data. The goal is to move from passive monitoring to closed-loop control. In this way, artificial intelligence does not just detect anomalies but actively intervenes in process parameters (laser power, scanning speed, focal depth) to ensure the structural compliance of the component. The current challenge involves the standardization of this data and the ability to handle extremely complex geometries on commercial machines.

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Authors:
Alexandra PapatheodorouNikolaos PapadimitriouEmmanuel StathatosPanorios BenardosGeorge-Christopher Vosniakos
Date Published:
Original Article www.mdpi.com
Fact-check verified on 22/07/2026
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Creative Commons License CC BY-NC-SA 4.0

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