• Design & Manufacturing
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• 제14권1호
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• pp.63-68
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• 2020

Ultra-high brightness and thin displays need to optical micro-patterns which can uniformly diffuse the lights and low loss. The micro random patterns have characteristics to rise the optical efficiency such as light extraction, uniform diffusion. For this reason, various fabrication processes are studied for random patterns. In this study, the micro random patterns were machined by diamond turning which used a controlled cutting tool path with random cutting depth. The machined patterns had random shape and directionality along the circumferential direction. The average width and length of machined random pattern according to rotation radius were 40.13㎛~55.51㎛ and 37.25㎛~59.49㎛, and these results were compared with the designed result. Also, the machining error according to rotation radius in diamond turning using randomly controlled cutting depth was discussed.

• Journal of Welding and Joining
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• 제28권4호
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• pp.61-66
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• 2010

Silicon nitride is widely used as an engineering ceramics because it has high strength, abrasion resistance and corrosion resistance even at high temperature. However, machining of silicon nitride is difficult due to its high hardness and brittleness. Laser assisted machining(LAM) allows effective cutting using CBN tool by locally heating the cutting part to the softening temperature of YSiAlON using the laser beam. The effect of preheating depending on process parameters were studied to find out the oxidation mechanism. If silicon nitride is sufficiently preheated, the surface is oxidized and $N_2$ gas is formed and escapes from the material, thereby making the cutting process more advantageous. During laser preheating process before machining, high temperature results in strong oxidation which makes the bloating, silicate layers and micro cracks. Using the results of these experiments, preheating characteristics and oxidation behavior were found out.

• 한국기계가공학회지
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• 제20권12호
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• 대한기계학회논문집A
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• 제36권10호
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• pp.1189-1193
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• 2012

본 연구는 초소형 광학 시스템을 구현할 수 있는 설계 및 제작의 방법론을 제시하고자 한다. 초소형 광학계에서는 조명 및 결상 광학소자의 성능과 소형화가 조광면의 균질도와 결상 된 이미지의 선명도에 중요한 영향을 미치게 된다. 본 연구에서는 얇은 두께로 실효 광도를 배가시키기 위한 초박형의 LED 빔조형 렌즈를 설계 제작하였다. 상기 렌즈는 중앙부의 비구면렌즈와 외각의 전반사 프레넬 가장자리 부로 구성되어 있다. 설계된 LED 빔조형 렌즈(직경 4.7 mm, 두께 0.6 mm)는 다이아몬드 선삭으로 중앙 비구면부의 전반사(TIR) 가장자리가 정밀하게 가공되었으며, LED 의 빔각을 150 도에서 17.5 도로 축소 시켰다. 다른 광학소자들 마이크로 프리즘, 결상광학용 프레넬 렌즈, 광가이드는 다양한 마이크로 나노 크기의 제조공정으로 일체형으로 성형되었다. 시작품으로 제작된 초소형 광학계($6.8{\times}2.2{\times}2.5mm$)는 마이크로 패턴을 결상의 가능성을 보여주었고, 지문인식용 초소형광학계로서의 성능을 검증하였다.