• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2338-2343
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• 2007

The practical studies on the method of particle contamination control for yield enhancement in the cleanroom were carried out. The method of the contamination control was proposed, which are composed of data collection, data analysis, improvement action, verification, and implement control. The partition check method for data collection and data analysis was used in the cellular phone module production lines. And this method was evaluated by the variation of yield loss between before and after improvement action. In case that the partition check method was applied, the critical process step was selected and yield loss reduction through improvement actions was observed. From these results, it is concluded that the partition check method is effective solution for particle contamination control in the cleanroom production lines.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.4
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• pp.325-331
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• 2007

In this study, the inter-metal dielectric material of FSG was changed by low-k material in $0.13{\mu}m$ foundry-compatible technology (FCT) device process based on fluorinated silicate glass (FSG). Black diamond (BD) was used as a low-k material with a dielectric constant of 2.95 for optimization and yield-improvement of the low-k based device process. For yield-improvement in low-k based device process, some problems such as photoresist (PR) poisoning, damage of low-k in etch/ash/cleaning process, and chemical mechanical planarization (CMP) delamination must be solved. The PR poisoning was not observed in BD based device. The pressure in CMP process decreased to 2.8 psi to remove the CMP delamination for Cu-CMP and USG-CMP. $H_2O$ ashing process was selected instead of $O_2$ ashing process due to the lowest condition of low-k damage. NE14 cleaning after ashing process lot the removal of organic residues in vias and trenches was employed for wet process instead of dilute HF (DHF) process. The similar-state of SRAM yield was obtained in Cu/low-k process compared with the conventional $0.13{\mu}m$ FCT device by the optimization of these process conditions.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1290-1300
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• 2022

Objective: "Diagnostic yield," also referred to as the detection rate, is a parameter positioned between diagnostic accuracy and diagnosis-related patient outcomes in research studies that assess diagnostic tests. Unfamiliarity with the term may lead to incorrect usage and delivery of information. Herein, we evaluate the level of proper use of the term "diagnostic yield" and its related parameters in articles published in Radiology and Korean Journal of Radiology (KJR). Materials and Methods: Potentially relevant articles published since 2012 in these journals were identified using MEDLINE and PubMed Central databases. The initial search yielded 239 articles. We evaluated whether the correct definition and study setting of "diagnostic yield" or "detection rate" were used and whether the articles also reported companion parameters for false-positive results. We calculated the proportion of articles that correctly used these parameters and evaluated whether the proportion increased with time (2012-2016 vs. 2017-2022). Results: Among 39 eligible articles (19 from Radiology and 20 from KJR), 17 (43.6%; 11 from Radiology and 6 from KJR) correctly defined "diagnostic yield" or "detection rate." The remaining 22 articles used "diagnostic yield" or "detection rate" with incorrect meanings such as "diagnostic performance" or "sensitivity." The proportion of correctly used diagnostic terms was higher in the studies published in Radiology than in those published in KJR (57.9% vs. 30.0%). The proportion improved with time in Radiology (33.3% vs. 80.0%), whereas no improvement was observed in KJR over time (33.3% vs. 27.3%). The proportion of studies reporting companion parameters was similar between journals (72.7% vs. 66.7%), and no considerable improvement was observed over time. Conclusion: Overall, a minority of articles accurately used "diagnostic yield" or "detection rate." Incorrect usage of the terms was more frequent without improvement over time in KJR than in Radiology. Therefore, improvements are required in the use and reporting of these 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.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.184-195
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• 2004

Current companies 집중 on how to operate and select projects to achieve the best result. 6sigma projects are chosen in the best suitable concept, which are solved by the 6Sigma experts according to the priority. And every project has to be launched not the view of individual management factors but the total factors, Big Y. Therefore, a process needs to be treated to connect the vital few factors in various processes to improve the yield, which is the main performance criteria in a manufacturing industry This report is to make the total optimization through the Vital-Few mapping between quality characteristics and process factors in a manufacturing line. Accordingly, it means to secure lower variance by making the CTP(Critical To Process) optimization and finally to improve the yield.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.04a
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• pp.9-9
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• 2019

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.2
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• pp.105-110
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• 1994

Field experiment was carried out to obtain the basic information on the soil improvement with different improved methods on job's tears yield and soil properties in the newly-reclaimed land from 1985 to 1988. Job's tears yield, soil properties and annual changes of soil were investigated and analyzed. Soil bulk density and hardness of topsoil decreased from 1st year to 3rd year, but those increased in 4th year. Soil pH of topsoil had no differences in different soil depths and cultivated years. Average yield of job's tears in the integrated improvement plot was 2.16ton/ha. That was increased by 49% than the control plot. Crop yield was greatest in order of integrated improvement>subsoiling>phosphate>lime>compost>control plot. Correlation coefficients of job's tears yield with soil pH and organic matter content were higher significantly. Also those of subsoil were higher than topsoil. Ratios of annual changes of soil bulk density and hardness showed significant highly with job's tears yield. Also that soil pH was significant at 5 % level in the topsoil.

• International Journal of Quality Innovation
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• v.10 no.1
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• pp.1-23
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• 2009

Face the process yield rate improvements of motherboard, although general enterprises finish deployment goal of each functions by overall quality managements, through quality improvement methods, industry engineering methods, plan-do-check-act (PDCA) methods and other improvement solutions, but it is only can be improved partially and unable to enhance the yield rate of product to the target. It only can takes one step ahead to enhance the process yield rate of motherboard with six sigma ($6{\sigma}$) overall DMAIC process and tactics. This research aimed to use six sigma quality improvement tactics by DMAIC systematic procedure and tactics, and find the key factors that effect to the process yield rate of surface mount technology. It also identified the keys input and process and output index to satisfy customer requirements and internal process index. The results showed that the major effective factors by fishbone and process failure modes and effects analysis (PFMEA). If the index of input and output that can be quantified, the optimum parameter can be found through design of experiment to ensure that the process is stable. If the factor of input and output that cannot be quantified, we found out the effective countermeasure by Mind_Mapping, make sure whole processes can be controlled stably, to reach the high product quality and enhance the customer satisfaction.

• Journal of The Korean Society of Grassland and Forage Science
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• v.11 no.1
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• pp.22-29
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• 1991

This study was experimented to obtain the basic information on the changeable aspect and improvement of soil fertility in newly-reclaimed sloped land. Silage corn was cultivated under the six different treatments for 4 years. The relation between the amount or ratio of annual changes of soil physico-chemical properties and yield of silage corn were analyzed. Soil bulk density was decreased in 3rd year at topsoil, but that decreased in 4th year at subsoil. Soil organic matter also decreased in 2nd year at topsoil, and decreased continuously at subsoil. Bulk density and hardness of soil depths showed significant negative simple correlation with dry matter yield and cation exchange capacity showed positive. Correlation coefficient of chemical properties with dry matter yield were low. The range of annual changes of moisture percent, hardness and organic matter were wider than the other properties. The significantly different of physical properties were higher than the chemical properties, and those of topsoil were higher than subsoil. According to multiple regression between yield and physico-chemical properties of subsoil, bulk density and cation exchange capacity were in the greatest contribution at the variations, but bulk density was greatest at the ratios.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.12
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• pp.1813-1821
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• 2002

The aim of this study was to identify useful secondary traits for estimating genetic ability of milk production traits. We investigated the value of using plasma metabolites concentrations. Two hundred and nineteen cattle out of 271 had only milk production traits records (G1), 33 had only metabolites records (G2), and 19 had both milk production traits and metabolites records (G3). Fifty two calves with metabolites records (G2 and G3) were born from 1992 to 1997. Forty three calves (29 females, 14 males) were used from 10 to 90 d of age and the others (3 females, 6 males) from 10 to 60 d of age. A total of 566 records of milk yield, fat yield and protein yield for 240 to 305 d on 238 heads (G1 and G2) were collected The collected blood samples were divided into three age groups: AG1, 10 to 30 d; AG2, 40 to 60 d; and AG3, 70 to 90 d. Heritabilities of milk yield, fat yield and protein yield were $0.45{\pm}0.04$, $0.50{\pm}0.04$ and $0.38{\pm}0.04$, respectively. Heritability of plasma glucose concentration at AG1 was $0.45{\pm}0.08$. Genetic correlations between plasma glucose concentration and milk yield, fat yield and protein yield were -$0.35{\pm}0.28$, $0.64{\pm}0.24$ and $0.36{\pm}0.35$, respectively. When the plasma glucose concentration at AG1 was used to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 8.2%, fat yield increased 24.2% and protein yield increased 9.5%. Heritability of plasma total cholesterol concentration at AG3 was $0.83{\pm}0.04$. Genetic correlation between plasma total cholesterol concentration and milk yield, fat yield and protein yield were $0.58{\pm}0.21$, $0.42{\pm}0.20$ and $0.45{\pm}0.22$, respectively. When the plasma total cholesterol concentration at AG3 was using to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 19.0%, fat yield increased 9.6%, and protein yield increased 13.5%. The annual genetic gain is in proportion to the reliability of selection. These results show that the plasma metabolite concentrations would be useful for improvement of genetic ability for milk production traits in the genetic improvement in herd of cows, where half of the animals selected are from a herd without its own milk record.