How to embed anti-counterfeiting features in metal products
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2021-03-29
Additive manufacturing (AM) offers inherent flexibility and advantages over traditional manufacturing methods, enabling the production of complex, high-performance products. By 2020, the global potential annual market value of additive manufacturing technologies was projected to reach $21 billion, with 48.4% of this revenue expected to come from high-value-added manufacturing applications in industries such as aerospace, automotive, and healthcare. Many of these applications in the aforementioned sectors involve critical components related to functionality and safety—such as turbine blades used in jet engines and bone implants for medical applications.
The rapid adoption of additive manufacturing technologies has made it even harder to combat counterfeit products, as counterfeiters now have access to affordable 3D printers and can easily obtain 3D models—either by downloading them online or acquiring them through reverse engineering—enabling them to swiftly replicate and distribute fake items. According to a database report from the U.S. Federal Aviation Administration (FAA), between 2010 and 2017, there were 20 reported incidents of aircraft crashes caused by counterfeit components. Meanwhile, the U.S. National Transportation Safety Board (NTSB) documented 135 cases of substandard aviation parts discovered in aircraft between 2011 and 2016. In the automotive industry, the problem of counterfeiting is even more severe: the World Customs Organization, in collaboration with Interpol, estimates that the global market for counterfeit auto parts is worth an alarming $12 billion annually. Meanwhile, the U.S. auto parts industry loses as much as $3 billion in sales each year due to these fraudulent products.
Due to the technical limitations of existing metal additive manufacturing techniques—such as powder bed fusion and directed energy deposition—which make it challenging to embed high-resolution security features, developing a high-resolution, multi-metal material additive manufacturing technology capable of incorporating tracking codes as a novel anti-counterfeiting measure is crucial.
In this experiment, the primary materials used were spherical 316L stainless steel powder with a diameter of 10–45 micrometers, provided by LPW Technology Ltd. in the UK (Figure 1a), and Cu10Sn powder with a diameter of 10–45 μm (Makin Metal Powders Ltd., UK, Figure 1b), which served as the security marking material. Both Cu10Sn and 316L exhibit distinct thermal properties and densities, making it expected that they will produce markedly different infrared spectra, X-ray fluorescence signatures, and X-ray imaging characteristics. Notably, since 316L contains no copper or tin elements in its chemical composition, the embedded features should be more easily detectable via X-ray fluorescence analysis.
Figure 1. SEM images of the powder materials used: a) 316 L powder, b) Cu10Sn powder
Experiments were conducted using a multi-material SLM system designed by the University of Manchester (as shown in Figure 2).
Figure 2. Schematic Diagram of the Experimental Setup
The process flow is illustrated in Figure 3. First, the primary material—316L—is spread into a thin layer. Next, a laser beam selectively melts the powder in the designed areas. Afterward, the unmelted powder surrounding the QR code positions is carefully removed by a miniature vacuum cleaner, creating flat cavities with the desired pattern. The marking material—Cu10Sn—is then deposited into these QR code-shaped cavities and subsequently melted using the laser beam. To prevent any contamination of the primary material by the powdered material, the laser-melted QR code area is once again cleaned using the micro-vacuum system. Finally, the worktable lowers by a predefined single-layer distance. These steps are repeated until the 3D component is fully fabricated.
Figure 3. Schematic diagram of the multi-material SLM process used to embed security features into metal parts.
The embedded QR code printing process for recording CCD images—each step from (a) to (g)—is illustrated in Figure 3.
As shown in Figure 5a, a special QR code has been designed, with the QR code itself (in red) and its surrounding components (in blue) made from Cu10Sn and 316L, respectively. The information encoded in this code is "LPRC, University of Manchester." In sample A (Figure 5a), the code is fully exposed on the top surface. In sample B, two-thirds of the code is covered by a 1-mm-thick layer of 316L (Figure 5b). Meanwhile, in sample C, the entire embedded QR code (see Figure 5c) is concealed beneath a 2-mm-thick 316L layer. Notably, all three samples feature a QR code thickness of exactly 0.5 mm.
Figure 5. (a) through (c) show schematic diagrams of QR code samples A, B, and C, respectively, while (d) illustrates a schematic of the label ring adhered to a 304 stainless steel substrate, with X-rays emanating from the bottom of the substrate.
The heating of the sample surface is based on radiative heat transfer. Heat transfer between the QR code area (316L) and the substrate occurs via conduction. During the heating process, the initial sample temperature was 15°C, while the furnace temperature was set to 120°C. In the cooling phase, the sample cools primarily through convection and radiation. Since the sample is allowed to cool in a typical indoor environment, the ambient temperature remains at 15°C.
As the heating time increases, the temperature distributions of both the exposed and partially covered QR codes are shown in Figures 7a and b. For the QR code exposed on the surface, the 316L component reached a maximum temperature of 51°C, while the Cu10Sn QR code registered 35°C after 10 minutes of heating, allowing for clear identification of the QR code. In contrast, for the other samples, no significant temperature difference was observed between the Cu10Sn QR code and the surrounding 316L material until the samples were heated for an hour, as illustrated in Figure 7b.
Figure 6 shows, (a) the simulated temperature distribution of the exposed QR code over time, and (b) the simulated temperature distribution for the partially covered QR code.
Over time, the temperature difference between the Cu10Sn and 316L sections decreases, leading to reduced image contrast. Figure 9b shows the temperature distribution of the partially covered QR code over a 20-minute interval. The temperature difference caused by the QR code buried beneath the surface becomes undetectable.
Figure 8. Simulated temperature distribution of the QR code samples as cooling time increases: (a) exposed QR code, (b) partially covered QR code.
Under fixed material composition and X-ray incidence intensity, the resolution of X-ray imaging is expected to be influenced by the total thickness of the X-ray inspection area containing the marker features. Specifically, the resolution will decrease exponentially as the depth of the covering layer increases along with the material thickness. Therefore, selecting heavier metals for the marker material and increasing the marker thickness can help enhance the contrast in X-ray imaging.
The X-ray image (Figure 9b) clearly reveals the QR code on the top surface of Sample A. The lower the material density (i.e., the atomic weight of the material), the more transparent it becomes to X-rays, resulting in a brighter image. Since the densities of 316L and 10Sn are 8.00 g/cm³ and 8.78 g/cm³, respectively, the 316L material appears lighter in color compared to Cu10Sn, as shown in Figure 9b.
Figure 9. (a) and (c) show the optical images of samples A and C, while (b) and (d) present the top-view digital X-ray images of samples A and C.
To further investigate the impact of embedding depth on QR code recognition, samples A and C were examined from top to bottom with a QR code cover layer set at 15.0 mm. Due to the penetration depth limitations of the digital X-ray system, we employed the conventional radiographic film method, which offers significantly greater photon penetration but results in lower image resolution compared to digital X-ray images. From an overhead view, clear QR code outlines were still visible on both samples A and C, as shown in Figure 10. Notably, however, the X-ray images taken from the top versus bottom views revealed a noticeable difference: the sample with the 15 mm cover layer exhibited reduced contrast. Despite this, the overall QR code imaging resolution remained unaffected.
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