• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.92-96
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• 1997

Recently, the life cycle of products is rapidly shortened and then the disposal of the used mold applied in development of the product is a difficult thing. In this study, we proposed the feasibility of new 3plate type mold base for recycling by analyzing of the existing standard mold base. And in order to apply new 3plate mold base in mold design and making, we constructed the specifications for parts such as runner stripper plate, cavity plate, core plate and slide core unit. Also, we confirmed the possibility of recycling mold base by testing a used 3plate mold for a Audio front pannel.

• 한국정밀공학회지
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• 제20권6호
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• pp.123-129
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• 2003

Recently, the life cycle of products is rapidly shortened and then the disposal of the used mold applied in development of the product is a difficult thing. In this study, we proposed the feasibility of new three plate type mold structure for recycling by analyzing of the existing standard mold base. And in order to apply new three plate mold structure in mold design and making. we constructed the specifications for mold parts such as runner stripper plate, cavity plate, core plate and slide core unit. Also, we confirmed the possibility of recycling mold base by testing a used three plate mold for audio front panel.

• Design & Manufacturing
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• 제15권3호
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• pp.45-49
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• 2021

In this study, during the injection molding process, a device was manufactured and evaluated that calculates a cooling time by measuring a vibration signal generated from a mold using an acceleration. The last two parts, one of which has a large magnitude change in the measured vibration signal of a mold, were divided into a cooling start section (paking end section) and a mold opening section, and the time difference at the relevant points was calculated as the cooling time. The cooling time was monitored on a 5-inch light guide plate mold by applying the method. The manufactured device was attached to a fixed base of mold to measure the cooling time, and data was obtained remotely using Bluetooth technology. Then, the measured cooling time was compared with the cooling time set in the injection molding machine to evaluate the accuracy. As a result of the experiment, the cooling times measured by the devices were 15.675±0.024 sec, 20.637±0.014 sec and 25.623±0.079 sec of each conditions. Also, the measurement results were shown with errors of 0.655±0.044 sec, 0.637±0.014 sec, and 0.662±0.013 sec, respectively.

• 대한치과기공학회지
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• 제9권1호
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• pp.67-72
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• 1987

This experimental study presented the study on the dimensional changes of occuring for the denture curing methods. The method is as follows: 1. The master die was made of wax. 2. The Silicon Rubber Mold was made into the same 80 casts. 3. The 80 Wax Plate were made of using the Base Plate Wax. 4. Flasking, Wax-wash, & Resin-packing were performed by the general procedures. 5. The curing method is performed through the four curing methods. (A, B, C, D). Table 2 shows the dimensional change after a day. Table 3 shows the dimensional change after soaking for 30 days in water of the degree of 36 Centigrade. As a result, the A curing method is the most denture curing.

• 한국산학기술학회논문지
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• 제7권3호
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• pp.471-475
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• 2006

랩온어칩(Lab-on-a-chip) 등 미세구조를 갖는 다양한 장치들의 대량 생산이 가능한 사출성형공정 내에서의 미세 흐름 거동의 이해는 매우 중요하다. 본 논문에서는 마이크로 채널 구조 내에서의 사출성형 흐름에 관하여 연구하였다. 흐름 현상을 관찰하기 위하여 투명한 PMMA를 사용하여 가시화 금형(visual mold)을 제작하였다. 실험 대상 물질로는 고분자 용액인 PEO (poly (ethylene oxide)) 와 PA (polyacrylamide) 용액을 선정하였는데, 이는 고분자 용융체의 특징인 높은 점성과 탄성을 갖도록 설계한 것이다. 시간에 따른 흐름현상과 주 채널과 마이크로 채널과의 경쟁적인 흐름 현상을 관찰하였다. 이로부터 마이크로 사출성형 흐름에서 나타나는 마이크로 채널 내의 충전길이에 대한 해석이 가능하였다.

• Design & Manufacturing
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• 제15권3호
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• pp.1-6
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• 2021

An artificial neural network model based on a deep learning algorithm is known to be more accurate than humans in image classification, but there is still a limit in the sense that there needs to be a lot of training data that can be called big data. Therefore, various techniques are being studied to build an artificial neural network model with high precision, even with small data. The transfer learning technique is assessed as an excellent alternative. As a result, the purpose of this study is to develop an artificial neural network system that can classify burr images of light guide plate products with 99% accuracy using transfer learning technique. Specifically, for the light guide plate product, 150 images of the normal product and the burr were taken at various angles, heights, positions, etc., respectively. Then, after the preprocessing of images such as thresholding and image augmentation, for a total of 3,300 images were generated. 2,970 images were separated for training, while the remaining 330 images were separated for model accuracy testing. For the transfer learning, a base model was developed using the NASNet-Large model that pre-trained 14 million ImageNet data. According to the final model accuracy test, the 99% accuracy in the image classification for training and test images was confirmed. Consequently, based on the results of this study, it is expected to help develop an integrated AI production management system by training not only the burr but also various defective images.

• Design & Manufacturing
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• 제14권3호
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• pp.8-16
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• 2020

In this study, the vibration signal of the mold was measured and analyzed to monitoring the process time and characteristics during injection molding. A 5 inch light guide plate mold was used to injection molding and the vibration signal was measured by MPU6050 acceleration sensor module attached the surface of fixed mold base. Conditions except for injection speed and packing pressure were set to the same value and the change of the vibration signal of the mold according to injection speed and packing pressure was analyzed. As a result, the vibration signal had a large change at three points: "Injection start", "V/P switchover", and "Packing end". The time difference between "injection start" and "V/P switchover" means the injection time in the injection molding process, and the time difference between "V/P switchover" and "Packing end" means the packing time. When the injection time and packing time obtained from the vibration signal of the mold are compared with the time recorded in the injection molding machine, the error of the injection time was 2.19±0.69% and the error of the packing time was 1.39±0.83%, which was the same level as the actual value. Additionally, the amplitude at the time of "injection start" increased as the injection speed increased. In "V/P switchover", the amplitude tended to be proportional to the pressure difference between the maximum injection pressure and the packing pressure and the amplitude at the "packing end" tended to the pressure difference between the packing pressure and the back pressure. Therefore, based on the result of this study, the injection time and packing time of each cycle can be monitored by measuring the vibration signal of the mold. Also, it was confirmed that the level and trend of process variables such as the injection speed, maximum injection pressure, and packing pressure can be evaluated as the change of the mold vibration during injection molding.