The global market for 3D-printed parts is a $5 billion business with a worldwide supply chain involving the internet, the cloud, and email - creating several opportunities for counterfeiting and intellectual property theft. Defective parts printed from stolen design files could produce dreadful results: experts forecast that by 2021, 75% of new commercial and military aircraft will fly with 3D-printed airframe, engine, and other components, and the use of AM in the production of medical implants will increase by 20% annually over the next 10 years.
A research team at NYU Tandon School of Engineering has discovered a method to prove the provenance of a part by employing Quick Response (QR) codes in an advanced way for unique device identification. In the recent issue of Advanced Engineering Materials, the researchers describe a technique for converting barcodes, QR codes, and other passive tags into three-dimensional (3D) features concealed in such a way that they neither sacrifice the part’s integrity nor reveal themselves to counterfeiters who possess the means to reverse engineer the part.
Renowned materials researcher Nikhil Gupta, an associate professor of mechanical engineering at NYU Tandon; Fei Chen, a doctoral student under Gupta; and joint NYU Tandon and NYU Abu Dhabi researchers Nektarios Tsoutsos, Michail Maniatakos and Khaled Shahin, detail how they manipulated the layer-by-layer AM printing process to convert QR codes into a game of 3D chess. Gupta’s team designed a scheme that “explodes” a QR code within a computer-assisted design (CAD) file so that it shows several false faces - dummy QR tags - to a micro-CT scanner or other scanning device. Only a reliable printer or end user would know the accurate head-on orientation for the scanner to capture the genuine QR code image.
By converting a relatively simple two-dimensional tag into a complex 3D feature comprising hundreds of tiny elements dispersed within the printed component, we are able to create many ‘false faces,’ which lets us hide the correct QR code from anyone who doesn’t know where to look.
Nikhil Gupta, Associate Professor of Mechanical Engineering
The team tested various configurations - from distributing a code across only three layers of the object, to fragmenting the code into up to 500-minute elements - on photopolymers, thermoplastics, and metal alloys, with several printing technologies universally employed in the industry.
Chen, the lead author of the research, said that after embedding QR codes in such basic objects as bars, cubes, and spheres, the team stress-tested the parts, learning that the embedded characteristics had a very minor impact on structural integrity.
“To create typical QR code contrasts that are readable to a scanner you have to embed the equivalent of empty spaces,” she explained. “But by dispersing these tiny flaws over many layers we were able to keep the part’s strength well within acceptable limits.”
Tsoutsos and Maniatakos researched threat vectors to establish which AM sectors are ideally served by this security technology, a step that Gupta said was vital in the research.
“You need to be cost-efficient and match the solution to the threat level,” he explained. “Our innovation is particularly useful for sophisticated, high-risk sectors such as biomedical and aerospace, in which the quality of even the smallest part is critical.”
A 2016 article by Gupta and a team of scientists that included Maniatakos and Tsoutsos in JOM, The Journal of the Minerals, Metals & Materials Society investigated how defects caused by printing orientation and insertion of fine defects could be foci for AM cyber-attacks. Among Springer’s over 245 engineering journals, this paper was the most-read engineering research that year. In a paper last year in Materials and Design, Gupta detailed techniques of inserting undetectable errors within CAD files so that only a reliable printer could properly produce the parts.