• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.138-147
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• 2013

The liquefaction process system is regarded as primary among all topside systems in LNG FPSO. This liquefaction process system is composed of many types of equipment. LNG equipment on offshore plants has quite different demands on the equipment compared to traditional onshore LNG plants, so the reliability analysis of this process system needs to be performed. This study investigates how DEVS formalism for discrete event simulation can be used to reliability analysis of the liquefaction cycle for LNG FPSO. The reliability analysis method based on DEVS formalism could be better model for reflecting the system configuration than the conventional reliability analysis methods, such as fault tree analysis and event tree analysis.

• Journal of Microbiology and Biotechnology
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• v.10 no.1
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• pp.21-26
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• 2000

A microarrayer system was developed mainly for manufacturing DNA chips. The 3-axis robot was designed to automatically collect samples from 96-or 384-well microtiter plates using up to 16 simultaneously moving pens and to deposit them on a surface-modified slide glass. This is followed by a wash/dry operation in a clean station. The cycle is repeated with a new set of samples, This system can deposit cDNA or oligonucleotides with spot intervals of $150{\;}\mu\textrm{m}$ and the spot size of $80\mu\textrm{m}$, thus allowing a high density DNA chip containing about 5,000 spots per $\textrm{cm}^2$. The entire procedure is controlled by the Visual C++ program that was written in our laboratory by using a personal computer with Pentium 100 CPU.

• Metals and materials international
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• v.24 no.6
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• pp.1303-1308
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• 2018

A new sintering technique for enhancing a densification and hardness of sintered titanium body by supplying hydrogen was developed (Hydrogen Sintering Process, HSP). The HSP was developed by only injecting hydrogen into an argon atmosphere during the core time. As a result, sound titanium sintered bodies with high density and hardness were obtained by the HSP. In addition, a pore size and number of the HSP specimens were smaller than those of the argon atmosphere specimen. It was found that the injecting hydrogen into the argon atmosphere by HSP can prevent the formation of oxide layers, resulting in enhanced densification and hardness.

• Journal of the Korean Society for Heat Treatment
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• v.22 no.1
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• pp.16-22
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• 2009

The rolling process is an efficient and economical approach for the manufacturing of plate metals. In the rolling process, the temperature variation is very critical for plate thickness accuracy. The main cause of thickness variation in hot plate mills is the non-uniform temperature distribution along the length of the slab. Also the exit plate thickness is mainly affected by the rolling conditions such as mill modulus, plate thickness and plate width. Hence the thickness variation in top-end is also dependent on these factors. Therefore this study has concentrated on determining the correct amounts of thickness variation due to top-end temperature drop and process parameters.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.513-516
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• 2004

Evolutionary operation is useful to improve on-line full-scale manufacturing processes by systematically changing the levels of the process variables while meeting production schedule. Evolutionary operation was developed using two or three process variables for process operators who are not good at statistics. Recently, when a product is developed, it is very important for the engineers to make the production line stable as soon as possible. And there are many causes which have influences to the product performance. This paper presents an evolutionary operation procedure with many process variables using saturated two level fractional factorial designs including Plackett-Burman design.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.463-473
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• 2011

The warm shrink fitting process is generally used to assemble automobile transmission parts (shaft/gear). But the fitting process can cause the dimensions of addendum and dedendum of the gear to change with respect to the fitting interference and the profile of the gear. As a result, there may be additional noise and vibration between gears. To address these problems, we analyzed the warm shrink fitting process according to process parameters; the fitting interference between the outer diameter of the shaft and the inner diameter of the gear, the inner diameter of the gear, addendum and dedendum of the gear, the heating temperature. In this study, a closed form equation for predicting the amount of deformation of addendum and dedendum in the R-direction was proposed. And the FEA method to analyze the cooling process was proposed for thermal-structural-thermal coupled field analysis of the warm shrink fitting process (heating-fitting-cooling process).

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.768-769
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.770-771
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• 2004

• Progress in Superconductivity and Cryogenics
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• v.25 no.4
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• pp.60-64
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• 2023

The manufacturing process of antibody drugs comprises two main stages: the upstream process for antibody cultivation and the downstream process for antibody extraction. The domestic bio industry has excellent technology for the upstream process. However, it relies on the technology of foreign countries to execute downstream process such as affinity chromatography. Furthermore, there are no domestic companies capable of producing the equipment for affinity chromatography. High gradient magnetic separation technology using a high temperature superconducting magnet as a novel antibody separation and purification technology is introduced to substitute for the traditional technology of affinity chromatography. A specially designed magnetic filter was equipped in the bore of the superconducting magnet enabling the continuous magnetic separation of nano-sized paramagnetic beads that can be used as affinity magnetic nano beads for antibodies. To optimize the magnetic filter that captures superparamagnetic nanoparticles effectively, various shapes and materials were examined for the magnetic filter. The result of magnetic separation experiments show that the maximum separation and recovery ratio of superparamagnetic nanoparticles are 99.2 %, and 99.07 %, respectively under magnetic field (3 T) and flow rate (600 litter/hr).