Researchers Develop AI Software That Assess 3D Printing Quality in Real Time

Researchers Develop AI Software That Assess 3D Printing Quality in Real Time
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A team of US researchers has developed artificial intelligence (AI) software for 3D printers that assesses the quality of parts in real time, without the need for expensive characterisation equipment.

The software, named Peregrine, supports the advanced manufacturing "digital thread" being developed at Oak Ridge National Laboratory (ORNL) that collects and analyses data through every step of the manufacturing process, from design to feedstock selection to the print build to material testing.

"Capturing that information creates a digital 'clone' for each part, providing a trove of data from the raw material to the operational component," said Vincent Paquit from ORNL's Imaging, Signals and Machine Learning group.

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"We then use that data to qualify the part and to inform future builds across multiple part geometries and with multiple materials, achieving new levels of automation and manufacturing quality assurance."

The "digital thread" supports the factory of the future in which custom parts are conceived using computer-aided design, or CAD, and then produced by self-correcting 3D printers via an advanced communications network, with less cost, time, energy and materials compared with conventional production.

These printers distribute a fine layer of powder over a build plate, with the material then melted and fused using a laser or electron beam. (Representational Image). Unsplash

The concept requires a process control method to ensure that every part rolling off printers is ready to install in essential applications like cars, airplanes, and energy facilities. The software is well suited to powder bed printers.

These printers distribute a fine layer of powder over a build plate, with the material then melted and fused using a laser or electron beam. Binder jetting systems rely on a liquid binding agent rather than heat to fuse powdered materials.

"One of the fundamental challenges for additive manufacturing is that you're caring about things that occur on length-scales of tens of microns and happening in microseconds, and caring about that for days or even weeks of build time," said ORNL's Luke Scime, principal investigator for "Peregrine".

"Because a flaw can form at any one of those points at any one of those times, it becomes a challenge to understand the process and to qualify a part."

The AI software was developed at the Manufacturing Demonstration Facility at ORNL, a US Department of Energy user facility that works closely with industry to develop, test and refine nearly every type of modern advanced manufacturing technology. (IANS)

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