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This study aims to investigate ultraviolet (UV) laser patterning QR codes on printed circuit boards (PCBs) for the inventory management of image recognition. The developed technology is a green manufacture and can replace the harmful environmental substances of brominated epoxy resin ink for the PCB process. In this study, the recognizability of the laser-patterned QR codes and the relationship between the ablated depth and the color change were investigated. The gray relational analysis (GRA) method was adopted to obtain the optimal laser patterning parameters. Furthermore, a spectrophotometer, scanning electron microscope, laser confocal microscope, and spectrometer were used to examine the light absorbance, the ablated depth, the pattern morphology, and the change in light reflectance of the laser-patterned QR codes on PCBs, respectively. The laser-patterned results revealed that QR codes produced white images with an ablation depth ranging from 5 to 10 μm as the scan speed was 300 mm/s at a laser power of 2 W and the scan speed was 900 mm/s at a laser power of 3—6 W. Moreover, the light reflectance of the white sample was close to 0.3819—0.3139, which was a parameter for successful whitening and was easy to recognize by a smartphone app. According to GRA results, the recognized QR code image could be patterned by the parameters of 2 W laser power, 300 mm/s scan speed, and 60 μm scan space. Furthermore, the scan speed was a severe impact factor for laser-patterned QR codes.

Laser-patterned small-scale QR codes have been widely used for rapid product identification in production history or inventory management. This study proposed a laser-heating oxidation mechanism to produce highly recognizable QR codes on metal surfaces that could save processing time and prevent environmental damage caused by chemical printing. Hence, maskless ultraviolet lasers with a wavelength of 355 nm were used to irradiate on the surface of alloys SS316 and Ti-64. The laser-patterned surface generated an oxide layer without ablating materials and produced the color change between oxides and raw materials. Laser power, scan speed, and scan spacing were adjusted to pattern QR codes for product identification. The tested results demonstrated that a higher laser power, slower scan speed, and lower scan spacing produced a dark oxide layer. This was due to a phenomenon of high thermal accumulation. Furthermore, the image recognition by the smartphone was more stable when the QR code was patterned with a scan speed of 60 mm/s and a scan spacing of 40 μm. The patterned QR codes for Ti-64 have significantly black colors compared to those for SS316. QR codes on surfaces SS316 and Ti-64 were found to have the ability to be recognized since the laser areal fluence was greater than 156.3 J/cm 2 . The elemental oxygen content of SS316 and Ti-64 treated with 625 J/cm 2 was greater than 3.5 and 50.8 times compared to the untreated, respectively. The grain size of SS316 and Ti-64 before and after maskless laser patterning does not have a significant change in the lattice structure. The proposed approach can be widely applied in IoTs for manufacturing components that need to use QR codes in conjunction with the barcode reader to quickly manage inventory.