• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.125-130
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• 2021

Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.

• 반도체디스플레이기술학회지
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• 제21권2호
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• pp.68-73
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• 2022

In this study, we produced the surface defect detection model to automatically detect defect bone plates using a deep learning algorithm. Bone plates with a width and a length of 50 mm are most used for fracture treatment. Normal bone plates and defective bone plates were printed on the 3d printer. Normal bone plates and defective bone plates were photographed with 1,080 pixels using the webcam. The total quantity of collected images was 500. 300 images were used to learn the defect detection model. 200 images were used to test the defect detection model. The mAP(Mean Average Precision) method was used to evaluate the performance of the surface defect detection model. As the result of confirming the performance of the surface defect detection model, the detection accuracy was 96.3 %.

• 대한안전경영과학회지
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• 제25권2호
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• pp.153-158
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• 2023

This research was conducted to reduce the defect rate caused by nozzle clogging of printing heads used in binder jet 3D printers. The binder jet 3D printing technology may adhere to the printing head nozzle by dispersing powder due to mechanical operation such as transferring the printing head and supplying powder, and may cause nozzle clogging by natural curing at the nozzle end depending on the type of binder used. To solve this problem, this study created a cleaning module exclusively for printing heads to check whether the durability of printing heads is improved through analysis of printing results before and after using the cleaning module. To this end, this research used a thermal bubble jet printing head, and the used powder was studied using gypsum powder.

• Journal of International Society for Simulation Surgery
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• 제1권1호
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• pp.13-15
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• 2014

Nowadays, with advanced 3D printing techniques, the custom-made implant can be manufactured for the patient. Especially in skull reconstruction, it is difficult to design the implant due to complicated geometry. In large defect, an autograft is inappropriate to cover the defect due to donor morbidity. We present the process of manufacturing the 3D custom-made implant for skull reconstruction. There was one patient with skull defect repaired using custom-made 3D titanium implant in the plastic and reconstructive surgery department. The patient had defect of the left parieto-temporal area after craniectomy due to traumatic subdural hematoma. Custom-made 3D titanium implants were manufactured by Medyssey Co., Ltd. using 3D CT data, Mimics software and an EBM (Electron Beam Melting) machine. The engineer and surgeon reviewed several different designs and simulated a mock surgery on 3D skull model. During the operation, the custom-made implant was fit to the defect properly without dead space. The operative site healed without any specific complications. In skull reconstruction, autograft has been the treatment of choice. However, it is not always available and depends on the size of defect and donor morbidity. As 3D printing technique has been advanced, it is useful to manufacture custom-made implant for skull reconstruction.

• 구강회복응용과학지
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• 제35권3호
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• pp.191-198
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• 2019

본 증례는 상악골 결손이 있는 무치악 환자에서 3D printing을 이용해 closed hollow bulb obturator로 수복한 증례이다. Magic $denture^{TM}$ 시스템(Cozahn, Seoul, Korea)에서 제공하는 트레이와 인상법을 이용하여 구내 인상을 채득하였고, 시적의치상에서 수직고경과 안모, 유지력 등을 확인하였다. 환자가 요구하는 바와 오차를 시적의치에서 수정한 후 이를 반영하였다. 의치의 무게를 줄이고 균일한 두께를 부여하기 위해 상악골 결손부위를 closed hollow bulb로 디자인하여 최종의치상을 프린팅하였다. 치료 후 심미적 및 기능적으로 만족스러운 결과를 얻었기에 이를 보고하는 바이다.

• 한국분말재료학회지
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• 제31권2호
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• pp.137-145
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• 2024

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2017년도 제48회 춘계학술대회논문집
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• pp.872-876
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• 2017

금속 소재부품의 제조 형태가 복잡해지고 소비자의 요구가 다양함에 따라 금속 3D 프린팅 연구가 활발히 진행되고 있다. 본 연구에서는 우주 발사체의 엔진 연소 노즐 부품에 적용 가능한 스테인레스 316L계 금속을 3D 프린팅 방식으로 제조하고 이에 대한 기계적, 화학적 특성 상관 연구를 진행하였다. 금속 3D 프린팅 기술은 레이저원을 이용하여 분말을 급속 용융과 응고를 반복됨에 따라 기존의 주조 응고와는 다른 미세 조직 형태를 나타내고, 이에 따라 기계적 물성이 변화함을 관찰하였다. 특히 개재물의 존재에 따라 기계적 특성이 변화하고 공정 조건의 변화에 따라 기공의 형태 및 위치등이 변화하는 것을 확인하였다.

• 반도체디스플레이기술학회지
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• 제19권3호
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• pp.77-81
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• 2020

In this paper, we create scaffold defect classification models using machine learning based data. We extract the characteristic from collected scaffold external images using USB camera. SVM, KNN, MLP algorithm of machine learning was using extracted features. Classification models of three type learned using train dataset. We created scaffold defect classification models using test dataset. We quantified the performance of defect classification models. We have confirmed that the SVM accuracy is 95%. So the best performance model is using SVM.

• 한국콘텐츠학회논문지
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• 제18권7호
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• pp.628-634
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• 2018

턱관절 디스크 검사 시 MRI는 유용한 검사법으로 디스크의 정확한 위치변화를 관찰하고자 개구상태에서 오랜 시간 검사가 필요하다. 이에 3D프린팅 기술을 이용하여 개구상태를 유지시켜 줄 고정 장치(TMJ device)를 제작하고 이를 기존 고정 장치와 비교하여 유용성을 평가하고자 하였다. 기존 TMJ device를 사용한 영상에 비해 3D 프린터로 자체 제작한 TMJ device를 사용한 영상에서 SNR이 다소 낮은 결과를 보였지만 임상적으로 사용하는데 큰 결함이 없고 환자 개인별 특화된 맞춤형 제작이 가능하고 더불어 3D 프린팅 기술을 활용하여 유사도구 제작에 기여함으로서 비용대비 편익이 상승될 것이라 사료된다.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.903-914
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• 2020

In this paper, we present a novel algorithm to generate a 3D model of patient-specific orbital implant, which is finally produced by the 3D printer. Given CT (computed tomography) scan data of the defective orbital wall or floor, we compose the depth image of the defect site by using the depth buffering, which is a computer graphics technology. From the depth image, we compute the 3D surface which fills the broken part by interpolating the points around the broken part. By thickening the 3D surface, we get the 3D volume mesh of the orbital implant. Our algorithm generates the patient-specific orbital implant whose shape is accurately coincident to the broken part of the orbit. It provides the significant time efficiency for manufacturing the implant with supporting high user convenience.