Researchers from Oak Ridge National Laboratory, the largest U.S. Department of Energy (DOE) open science laboratory, have developed Peregrine artificial intelligence (AI) software for powder-bed fusion 3D printers that will enable real-time 3D printing quality assessment, without the need for expensive characterization equipment.
The AI software named Peregrine, probably after the Peregrine falcon, is always on the lookout for flaws in 3D printing in real-time.
PEREGRINE AI SOFTWARE
Peregrine AI software supports the advanced manufacturing “digital thread” being developed at 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.
Vincent Paquit, who leads advanced manufacturing data analytics research as part of ORNL’s Imaging, Signals, and Machine Learning group explained, “Capturing that information creates a digital ‘clone’ for each part, providing a trove of data from the raw material to the operational component. 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. 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.
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ORNL researchers have created a novel convolutional neural network as a control method for surface-visible defects that would work on multiple printer models. If Peregrine AI software detects an anomaly that may affect the quality of the part, it automatically alerts operators so adjustments can be made.
The software is well suited to powder bed printers that are popularly used for metal 3D printing.
However, during the printing process, problems such as the uneven distribution of the powder or binding agent, spatters, insufficient heat, and some porosities can result in defects at the surface of each layer.
According to ORNL’s Luke Scime, principal investigator for Peregrine, “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. 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.”
PEREGRINE AI SOFTWARE TESTING
Peregrine AI Software is being tested on multiple printers at ORNL, including as part of the Transformational Challenge Reactor, or TCR, Demonstration Program that is pursuing the world’s first additively manufactured nuclear reactor.
The Peregrine AI software has been tested successfully on seven powder bed printers at ORNL so far, including electron beam melting, laser powder bed, and binder jetting, as detailed in the journal Additive Manufacturing.
ORNL researchers stress that by making the Peregrine software machine-agnostic printer manufacturers can save development time while offering an improved product to industry.
Scime added, “Anything we can do to help operators and designers know what works and what doesn’t helps with the confidence that the part will be okay for use. When you have a 3D map of every pixel where the network thinks there is an anomaly and what it thinks the problem is, it opens up a whole world of understanding of the build process.”
The Peregrine AI software was developed at the Manufacturing Demonstration Facility at ORNL, a U.S. Department of Energy user facility that works closely with industry to develop, test, and refine nearly every type of modern advanced manufacturing technology.
The work was sponsored by DOE’s Office of Energy Efficiency and Renewable Energy’s Advanced Manufacturing Office and the DOE Office of Nuclear Energy, which funds the TCR program.
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