• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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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.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.202-202
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• 2011

The research of 3-dimensional (3-D) scaffold for tissue engineering has been widely investigated as the importance of the 3-D scaffold increased. 3-D scaffold is needed to support for cells to proliferate and maintain their biological functions. Furthermore, its architecture defines the shape of the new bone and cartilage growth. Polycaprolactone (PCL) has been one of the most promising materials for fabricating 3-D scaffold owing to its excellent mechanical property and biocompatibility. However, there are practical problems for using it, in vitro and in vivo; extracellular matrix components and nutrients cannot penetrate into the inner space of scaffold, due to its hydrophobic property, and thus cell seeding and attachment onto the inner surface remain as a challenge. Thus, the surface modification strategy of 3-D PCL scaffold is prerequisite for successful tissue engineering. Herein, we utilized a mussel-inspired approach for surface modification of 3-D PCL scaffold. Modification of 3-D PCL scaffolds was carried out by simple immersion of scaffolds into the dopamine solution and stimulated body fluid, and as a result, hydroxyapatite-immobilized 3-D PCL scaffolds were obtained. After surface modification, the wettability of 3-D PCL scaffold was considerably changed, and infiltration of the pre-osteoblastic cells into the 3-D scaffold followed by the attachment onto the surface was successfully achieved.

• Journal of Industrial and Engineering Chemistry
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• v.67
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• pp.388-395
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• 2018

Significant efforts have been applied toward fabricating three-dimensional (3D) scaffolds using 3D-bioprinting tissue engineering techniques. Gelatin has been used in 3D-bioprinting to produce designed 3D scaffolds; however, gelatin has a poor printability and is not useful for fabricating desired 3D scaffolds using 3D-bioprinting. In this study, we fabricated pore size controlled 3D gelatin scaffolds with two step 3D-bioprinting approach: a low-temperature ($-10^{\circ}C$) freezing step and a crosslinking process. The scaffold was crosslinked with 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS). The pore sizes of the produced 3D gelatin scaffolds were approximately 30% smaller than the sizes of the designed pore sizes. The surface morphologies and pore sizes of the 3D gelatin scaffolds were confirmed and measured using scanning electron microscopy (SEM). Human dermal fibroblasts (HDFs) were cultured on a 3D gelatin scaffold to evaluate the effect of the 3D gelatin scaffold pore size on the cell proliferation. After 14 days of culture, HDFs proliferation throughout the 3D gelatin scaffolds prepared with more than $580{\mu}m$ pore size was approximately 14% higher than proliferation throughout the 3D gelatin scaffold prepared with a $435{\mu}m$ pore size. These results suggested that control over the 3D gelatin scaffold pore size is important for tissue engineering scaffolds.

• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1722-1729
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• 2006

Predicting the mechanical properties of the 3-D scaffold using finite element method (FEM) simulation is important to the practical application of tissue engineering. However, the porous structure of the scaffold complicates computer simulations, and calculating scaffold models at the pore level is time-consuming. In some cases, the demands of the procedure are too high for a computer to run the standard code. To address this problem, the representative volume element (RVE) theory was introduced, but studies on RVE modeling applied to the 3-D scaffold model have not been focused. In this paper, we propose an improved FEM-based RVE modeling strategy to better predict the mechanical properties of the scaffold prior to fabrication. To improve the precision of RVE modeling, we evaluated various RVE models of newly designed 3-D scaffolds using FEM simulation. The scaffolds were then constructed using microstereolithography technology, and their mechanical properties were measured for comparison.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1697-1699
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• 2008

The purpose of tissue engineering is to repair or replace damaged tissues or organs by a combination of cells, scaffold, suitable biochemical and physio-chemical factors. Among the three components, the biodegradable scaffold plays an important role in cell attachment and migration. In this study, we designed 3D porous scaffold by Rapid Prototyping (RP) system and fabricated layer-by-layer 3D structure using Polycarprolactone (PCL) - one of the most flexible biodegradable polymer. Furthermore, the physical and mechanical properties of the scaffolds were evaluated by changing the pore size and the strand diameter of the scaffold. We changed nozzle diameter (strand diameter) and strand to strand distance (pore size) to find the effect on the mechanical property of the scaffold. And the surface morphology, inner structure and storage modulus of PCL scaffold were analyzed with SEM, Micro-CT and DMA.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.1
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• pp.33-40
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• 2012

The scaffold serves as 3D substrate for the cells adhesion and mechanical support for the newly grown tissue by maintaining the 3D structure for the regeneration of tissue and organ. In this paper, we proposed integrated scaffold fabrication system using multi-axis rapid prototyping (RP) technology. It can fabricate various types of scaffolds: arbitrary sculptured shape, primitive shape, and tube shape scaffolds by layered dispensing biocompatible/ biodegradable polymer strands in designated patterns. In order to fabricate the 3D scaffold, we need to generate the plotting path way for the scaffold fabrication system. We design a data processing program - scaffold plotting software, which can convert the 3D STL file, primitive and tube model images into the NC code for the system. Finally, we fabricated the customized 3D scaffolds with high accuracy using the plotting software and the fabrication system.

• 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 %.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.12
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• pp.1229-1235
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• 2015

Scaffold fabrication technology using a 3D printer was developed for damaged bone tissue regeneration. A scaffold for bone tissue regeneration application should be biocompatible, biodegradable, and have an adequate mechanical strength. Moreover, the scaffold should have pores of satisfactory quantity and interconnection. In this study, we used the polymer deposition system (PDS) based on fused deposition modeling (FDM) to fabricate a 3D scaffold. The materials used were polycaprolactone (PCL) and alginic acid sodium salt (sodium alginate, SA). The salt-leaching method was used to fabricate dual pores on the 3D scaffold. The 3D scaffold with dual pores was observed using SEM-EDS (scanning electron microscope-energy dispersive spectroscopy) and evaluated through in-vitro tests using MG63 cells.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.25-30
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• 2019

In this paper, we have analyzed manufacturing problems of the scaffold with pores using FDM 3D printer and PLGA. We suggested the solutions using 3SC practical TRIZ. We selected the final solution used machine learning. We reduced number of experiments using most influential factor after analysis print factors. We printed the scaffold and measured pore size. We created the regression model using python tensorflow. The print condition data of measured pore size was used as training data. We predicted the pore size of printed condition using regression model. We printed the scaffold using the predicted the print condition data. We quantitatively compare the predicted scaffold pore size data and the measured scaffold pore size data. We got satisfactory result.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.46-50
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• 2019

In this paper, We used the regression model of machine learning for improve the print quantity problem when which print scaffold with 400 ㎛ pore using FDM 3d printer. We have difficult to experiment with changing all factors in the field. So we reduced print quantity by selected two factors that most impact the pore size. We printed and measured scaffold 5 times under same conditions. We created regression model using scaffold pore size and print conditions. We predicted pore size of untested print condition using the regression model. After print scaffold with 400 ㎛ pore, we printed scaffold 5 times under same conditions. We compare the predicted scaffold pore size and the measured scaffold pore size. We confirmed that error is less than 1 % and we verified the results quantitatively.