Researchers have developed artificial intelligence (AI) 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” that collects and analyzes data through every step of the manufacturing process, from design and feedstock selection, to print build and material testing.

Capturing that information creates a digital “clone” for each part, providing data from the raw material to the operational component. That data is then used 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 (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, 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, which 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. During the printing process, however, 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.

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 including electron beam melting, laser powder bed, and binder jetting.

Researchers can combine image data with data from other sources — such as the printer's log files, the laser systems, and operator notes — allowing parts to be uniquely identified and statistics from all parts tracked and evaluated.

For more information, contact Stephanie G. Seay at This email address is being protected from spambots. You need JavaScript enabled to view it.; 865-576-9894.


Tech Briefs Magazine

This article first appeared in the October, 2020 issue of Tech Briefs Magazine.

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