• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.9
• /
• pp.418-424
• /
• 2017

Magnesium has a higher specific strength than other metals and is widely used industry wide due to its excellent vibration absorption ability and electromagnetic wave shielding property.For example, it is used for automobile parts such as car seat frames and cylinder heads, and is widely used in electronic products such as notebook cases and mobile phone cases. In addition, it is in the spotlight as a bone-implant material used to assist in the treatment of damaged bones when the bones are cracked or broken. Currently, Ti alloy, stainless steel and Co-Cr-Mo alloy are used as the implant material, and the Mg alloy remains in research stage. The current problem with bone implant implants is that the patients must undergo reoperation to remove the implants after joint surgery. Magnesium, however, can achieve sufficient strength compared to current materials. In addition, since it is self-decomposed after the recovery, reoperation is not necessary. In this paper, Mg alloys were designed by adding harmless Ca and Zn to the human body. In order to improve the strength and corrosion resistance, the final alloy was designed by adding a small amount of Sr as a grain refiner. The radioactive elements of Sr are harmful to the human body, but other naturally occurring Sr elements are harmless. Microstructure analysis of the alloys was performed by optical microscopy and scanning electron microscopy. The mechanical properties and corrosion characteristics were evaluated by tensile test, potentiodynamic test and immersion test.

• Tribology and Lubricants
• /
• v.30 no.5
• /
• pp.278-283
• /
• 2014

Carbon nanotubes (CNTs) are used in various composite materials to enhance electrical, thermal and mechanical properties of composite materials. In this study, we investigate the wear characteristics of polycarbonate/acrylonitrile-butadiene-styrene (PC/ABS) blends containing multi-walled carbon nanotubes (MWCNTs). PC/ABS blends are commonly used in many industrial applications such as cellular phones and display cases and MWCNTs have been added to the PC/ABS blends to improve their electromagnetic interference shielding (EMS). We performed wear tests on PC/ABS blends containing MWCNTs under reciprocating linear sliding conditions with chrome steel balls as a counterpart material. The normal loads were 10, 30, 50, 70, 100 N, the sliding speed was 10 mm/s, the stroke length was 15 mm, and the tests lasted 900 s. The MWCNTs included in the PC/ABS blends lower the wear volume and friction coefficient of the composites. We analyzed the wear debris collected from the composites during the tests in terms of the MWCNT concentration using inductively coupled plasma optical emission spectroscopy. The results show that the quantity of MWCNTs in the debris is proportional to the concentration of MWCNTs in the composite, indicating that the exposure of the MWCNTs to environments by wear could be increased with their concentration in the composite.

• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.6_2
• /
• pp.729-735
• /
• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.