• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.99-103
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• 2021

Warpage defect detecting of scaffold is very important in biosensor production. Because warpaged scaffold cause problem in cell culture. Currently, there is no detection equipment to warpaged scaffold. In this paper, we produced detection model for shape warpage detection using deep learning based CNN. We confirmed the shape of the scaffold that is widely used in cell culture. We produced scaffold specimens, which are widely used in biosensor fabrications. Then, the scaffold specimens were photographed to collect image data necessary for model manufacturing. We produced the detecting model of scaffold warpage defect using Densenet among CNN models. We evaluated the accuracy of the defect detection model with mAP, which evaluates the detection accuracy of deep learning. As a result of model evaluating, it was confirmed that the defect detection accuracy of the scaffold was more than 95%.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.872-876
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• 2017

Laser Based 3D Printing is an recently advance manufacturing technology for making complex shape comopnent such as automobile and aerospace. So in this article, stainless steel 316L was manufactured by Selective Laser Melting (SLM) and Laser Melting Deposition (LMD) method. SLM is an additive manufacturing process that allow for the manufacture of small and complex component by laser melting and solidification of powder in bed using a high intensity laser beam. The results showed that the laser scanning speed and laser power affects the defect, microstructure and the hardness of the components.

• Transactions on Electrical and Electronic Materials
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• v.13 no.3
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• pp.129-135
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• 2012

A number of surface mount technology (SMT) process variables including land design are considered for minimizing tombstone defect in flexible printed circuit assembly in high volume manufacturing. As SMT chip components have been reduced over the past years with their weights in milligrams, the torque that once helped self-centering of chips, gears to tombstone defects. In this paper, we have investigated the correlation of the assembly process variables with respect to the tombstone defect by employing statistically designed experiment. After the statistical analysis is performed, we have setup hypotheses for the root causes of tombstone defect and derived main effects and interactions of the process parameters affecting the hypothesis. Based on the designed experiments, statistical analysis was performed to investigate significant process variable for the purpose of process control in flexible printed circuit manufacturing area. Finally, we provide beneficial suggestions for find-pitch PCB design, screen printing process, chip-mounting process, and reflow process to minimize the tombstone defects.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.59-64
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• 2020

In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.3
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• pp.233-236
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• 2021

A mandibular continuity defect can be repaired using either a prosthetic device or autogenous bone. A titanium reconstruction plate can be used with a localized or vascularized flap over the defect of the mandible. Unfortunately, the plate may fail due to plate exposure, screw loosening, fracture, or infection, and will need to be removed. Plate exposure though the skin or mucosa is one of the main reasons for failure. In the present work, the authors introduced a lingually positioned reconstruction plate fabricated via three-dimensional printed bending support. This custom reconstruction plate can avoid plate re-exposure as well as reduce surgical errors and operation time.

• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.99-102
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• 2014

The skull defect can be made after the trauma, oncologic problems or neurosurgery. The skull reconstruction has been the challenging issue in craniofacial fields for a long time. So far the skull reconstruction with autogenous bone would be the standard. Although the autogenous bone would be the ideal one for skull reconstruction, donor site morbidity would be the inevitable problem in many cases. Meanwhile various types of allogenic and alloplastic materials have been also used. However, skull reconstruction with many alloplastic material have produced no less complications including infection, exposure, and delayed wound healing. Because the 3D printing technique evolved so fast that 3D printed titanium implant were possible recently. The aim of this trial is to try to restore the original skull anatomy as possible using the 3D printed titanium implant, based on the mirrored three dimensional CT images based on the computer simulation. Preoperative computed tomography (CT) data were processed for the patient and a rapid prototyping (RP) model was produced. At the same time, the uninjured side was mirrored and superimposed onto the traumatized side, to create a mirror-image of the RP model. And we fabricated Titanium implant to reconstruct three-dimensional orbital structure in advance, using the 3D printer. This prefabricated Titanium-implant was then inserted onto the defected skull and fixed. Three dimensional printing technique of titanium material based on the computer simulation turned out to be very successful in this patient. Individualized approach for each patient could be an ideal way to manage the traumatic patients in near future.

• Archives of Craniofacial Surgery
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• v.16 no.1
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• pp.11-16
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• 2015

Background: Source material used to fill calvarial defects includes autologous bones and synthetic alternatives. While autologous bone is preferable to synthetic material, autologous reconstruction is not always feasible due to defect size, unacceptable donor-site morbidity, and other issues. Today, advanced three-dimensional (3D) printing techniques allow for fabrication of titanium implants customized to the exact need of individual patients with calvarial defects. In this report, we present three cases of calvarial reconstructions using 3D-printed porous titanium implants. Methods: From 2013 through 2014, three calvarial defects were repaired using custom-made 3D porous titanium implants. The defects were due either to traumatic subdural hematoma or to meningioma and were located in parieto-occipital, fronto-temporo-parietal, and parieto-temporal areas. The implants were prepared using individual 3D computed tomography (CT) data, Mimics software, and an electron beam melting machine. For each patient, several designs of the implant were evaluated against 3D-printed skull models. All three cases had a custom-made 3D porous titanium implant laid on the defect and rigid fixation was done with 8 mm screws. Results: The custom-made 3D implants fit each patient's skull defect precisely without any dead space. The operative site healed without any specific complications. Postoperative CTs revealed the implants to be in correct position. Conclusion: An autologous graft is not a feasible option in the reconstruction of large calvarial defects. Ideally, synthetic materials for calvarial reconstruction should be easily applicable, durable, and strong. In these aspects, a 3D titanium implant can be an optimal source material in calvarial reconstruction.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.628-634
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• 2018

In an examination of the temporomandibular joint disc, MRI(Magnetic Resonance Imaging) is a useful method, and it is necessary to conduct an examination with one's mouth open for a long time to observe the accurate position change of the disc. Thus, this study would produce a TMJ device, using the 3-D printing technology, which would maintain the state of opening the mouth and would evaluate its usefulness as compared to the existing fixed device. As compared to the image using the existing TMJ device, the image taken with the self-produced TMJ device with a 3-D printer showed a somewhat lower SNR, but there was no defect for a clinical use. It is judged that benefits to costs would increase, since it can be customized for the individual patient and can contribute to the production of similar tools by utilizing the 3-D printing technology.

• Journal of Korea Multimedia Society
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• v.23 no.8
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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.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.419-427
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• 2023

In this study, optimal adhesion conditions to alleviate defects caused by heat shrinkage with FDM type 3D printers with machine learning are researched. Machine learning is one of the "statistical methods of extracting the law from data" and can be classified as supervised learning, unsupervised learning and reinforcement learning. Among them, a function model for adhesion between the bed and the output is presented using supervised learning specialized for optimization, which can be expected to reduce output defects with FDM type 3D printers by deriving conditions for optimum adhesion between the bed and the output. Machine learning codes prepared using Python generate a function model that predicts the effect of operating variables on adhesion using data obtained through adhesion testing. The adhesion prediction data and verification data have been shown to be very consistent, and the potential of this method is explained by conclusions.