Oak Ridge National Laboratory (ORNL) researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.
The software, named Peregrine, supports the advanced manufacturing “digital thread” being developed at ORNL that collects and analyzes data through every step of the manufacturing process, from design to feedstock selection to the print build to material testing.
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.
To devise a control method for surface-visible defects that would work on multiple printer models, ORNL researchers created a novel convolutional neural network — a computer vision technique that mimics the human brain in quickly analyzing images captured from cameras installed on the printers. The Peregrine software uses a custom algorithm that processes pixel values of images, taking into account the composition of edges, lines, corners and textures. If Peregrine 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. 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. The systems print layer by layer, guided by the CAD blueprint, and are popular for the production of metal parts.
However, during the printing process, problems such as uneven distribution of the powder or binding agent, spatters, insufficient heat, and some porosities can result in defects at the surface of each layer. Some of those issues may happen in such a very short timeframe that they may go undetected by conventional techniques.
Peregrine 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.
ORNL researchers stress that by making the Peregrine software machine-agnostic — able to be installed on any powder bed system — printer manufacturers can save development time while offering an improved product to industry. Peregrine produces a common image database that can be transferred to each new machine to train new neural networks quickly, and it runs on a single high-powered laptop or desktop. Standard cameras were used in the research, ranging in most cases from 4 to 20 megapixels and installed so they produce images of the print bed at each layer. The 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.
News Source: ORNL
