• Journal of the Microelectronics and Packaging Society
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• v.30 no.1
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• pp.1-16
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• 2023

Recently, the shift to next-generation wide-bandgap (WBG) power semiconductor for electric vehicle is accelerated due to the need to improve power conversion efficiency and to overcome the limitation of conventional Si power semiconductor. With the adoption of WBG semiconductor, it is also required that the packaging materials for power modules have high temperature durability. As an alternative to conventional high-temperature Pb-based solder, Ag sintering die attach, which is one of the power module packaging process, is receiving attention. In this study, we will introduce the recent research trends on the Ag sintering die attach process. The effects of sintering parameters on the bonding properties and methodology on the exact physical properties of Ag sintered layer by the realization 3D image are discussed. In addition, trends in thermal shock and power cycle reliability test results for power module are discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.609-612
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• 2021

Government agencies and companies are establishing and promoting digital transformation strategies in various industrial fields, and are leading the era of the 4th industrial revolution through successful technological innovation. In this time of change, we can see many stories of global companies Nike and Starbucks as successful examples of digital transformation. These two companies are showing successful results through digital transformation. Domestic companies are also conducting digital innovation based on mobile, cloud, IoT, artificial intelligence, and AR/VR technologies, and are establishing RPA (Robotic Process Automation) processes for high efficiency and high productivity. In this paper, we introduce the 3D digital twin space construction automation process technique using data from the entire construction cycle of design, construction, and maintenance of the construction industry, and look into the digital transformation strategy of the construction industry in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.124-124
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• 2022

가뭄시 유역 수문량은 하천수/지하수 취·배수, 하·폐수방류량, 용수재이용 등 복잡한 물이용체계에 따른 영향이 크지만 기존 가뭄시 수문량 평가는 이러한 복잡한 물이용체계를 고려하지 않아 정도 높은 예측에 어려움이 있다. 따라서 가뭄시 유력 내 상세물이용체계 및 수문환경특성 인자들의 상호작용 규명을 통한 정도 높은 수문량 평가 기술의 개발이 시급하다. 대하천 주변 광역상수도 공급지역은 가뭄 발생시에도 안정적으로 물이용이 가능하나, 중소하천을 수원으로 하는 하천의 상류지역은 가뭄시 물공급 안정성이 취약하다. 따라서 중소하천을 대상으로 가뭄시 물 공급시설의 효율적 운영, 물부족 위험도 평가, 가용수자원의 최적이용 등 종합적인 대책 마련을 위해서는 신뢰성 높은 수문량(하천유출량 및 수자원가용량) 예측이 필요하다. 가뭄에 따른 중소하천유역의 수문학적 유출거동을 평가하기 위한 해석 모형으로는 국내의 복잡한 유역 수문환경특성을 평가하기 위해 개발된CAT (Catchment hydrologic cycle Assessment Tool)(김현준 등, 2012)을 이용하였다. CAT은 기후변화나 토지이용변화에 따른 유역의 수문환경특성 변동성을 정량적으로 평가하기 위해 개발된 모형이다. CAT은 인위적인 물이용체계 즉, 광역급수, 용수재이용, 지하수 취수, 하천수 취·배수 등을 분석하기 위한 툴을 제공하므로 가뭄시 상세물이용체계에 따른 시·공간적 수문환경특성 분석 및 수문량 평가를 위한 최적의 모형으로 선정하였다. 본 연구에서는 중소하천유역의 수문량 예측기술 실용화 기반을 마련하기 위하여 낙동강, 금강, 영산/섬진강 중권역을 대상으로 정밀 시공간 수문량을 평가하였다. 각 권역별 보정지점을 기준으로 관측유량 자료와 모의자료의 1:1비교를 통해 수문량 예측정확도를 산정하였으며, 모형효율(Nash Sutcliffe Efficiency, NSE) 및 결정계수(Coefficient of Determination, R²)의 권역별 평균은 NSE 72%, R2 79%로 나타났으며, 대부분의 지점에서 70% 이상을 나타내어 환경부 및 지자체의 가뭄시 물관리 정책을 지원하기 위한 실용화 기반을 마련하였다.

• Fashion & Textile Research Journal
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• v.25 no.6
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• pp.673-689
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• 2023

To realize the traceability of sustainable textile products, this study presents a low-carbon process through energy savings in the textile material manufacturing process. Traceability is becoming an important element of Life Cycle Assessment (LCA), which confirms the eco-friendliness of textile products as well as supply chain information. Textile products with complex manufacturing processes require traceability of each step of the process to calculate carbon emissions and power usage. Additionally, an understanding of the characteristics of the product planning-manufacturing-distribution process and an overall understanding of carbon emissions sources are required. Energy use in the textile material manufacturing stage produces the largest amount of carbon dioxide, and the amount of carbon emitted from processes such as dyeing, weaving and knitting can be calculated. Energy saving methods include efficiency improvement and energy recycling, and carbon dioxide emissions can be reduced through waste heat recovery, sensor-based smart systems, and replacement of old facilities. In the dyeing process, which uses a considerable amount of heat energy, LNG, steam can be saved by using "heat exchangers," "condensate management traps," and "tenter exhaust fan controllers." In weaving and knitting processes, which use a considerable amount of electrical energy, about 10- 20% of energy can be saved by using old compressors and motors.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.621-635
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• 2023

The assessment of structural condition is a crucial process for evaluating its usability and determining the diagnostic cycle. The currently employed manpower-based methods suffer from issues related to safety, efficiency, and objectivity. To address these concerns, research based on deep learning using images is being conducted. However, acquiring structural damage data is challenging, making it difficult to construct a substantial amount of training data, thus limiting the effectiveness of deep learning-based condition assessment. In this study, we propose a foundation model-based 2-step structural damage analysis to overcome the lack of training data in image-based structural condition assessments. We subdivided the elements of structural condition assessment into instantiation and quantification. In the quantification step, we applied a foundation model for image segmentation. Our method demonstrated a 10%-point increase in mean intersection over union compared to conventional image segmentation techniques, with a notable 40%-point improvement in the case of rebar exposure. We anticipate that our proposed approach will enhance performance in domains where acquiring training data is challenging.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.855-866
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• 2023

With the rapid advancement and sophistication of defense weapon systems, the government, military, and the defense industry have conducted various innovative attempts to improve the efficiency of post-logistics support(PLS). The Ministry of Defense has mandated RAM-C(Reliability, Availability, and Maintainability-Cost) analysis as a requirement according to revised Total Life Cycle System Management Code of Practice in May 2022. Especially, for the project budget forecast of new PBL(Performance Based Logistics) business contacts, RAM-C is recognized as an obligatory factor. However, relevant entities have not officially provided guidelines or manuals for RAM-C analysis, and each defense contractor conducts RAM-C analysis with different standards and methods to win PBL-related business contract. Hence, this study aims to contribute to the generalization of the analysis procedure by presenting a cost analysis case based on RAM-C for the supply of military depot maintenance PBL project. This study presents formulas and procedures to determine requirements of military depot maintenance PBL project for repair parts supply. Moreover, a sensitivity analysis was conducted to find the optimal cost/utilization ratio. During the process, a correlation was found between supply delay and total cost of ownership as well as between cost variability and utilization rate. The analysis results are expected to provide an important basis for the conceptualization of the cost analysis for the supply of military depot maintenance PBL project and are capable of proposing the optimal utilization rate in relation to cost.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.841-852
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• 2023

Gas turbines, which are used as generators for frequency regulation of the domestic power system, are increasing in use due to the carbon-neutral policy, quick startup and shutdown, and high thermal efficiency. Since the gas turbine rotates the turbine using high-temperature flame, the turbine inlet temperature is acting as a key factor determining the performance and lifespan of the device. However, since the inlet temperature cannot be directly measured, the temperature calculated by the manufacturer is used or the temperature predicted based on field experience is applied, which makes it difficult to operate and maintain the gas turbine in a stable manner. In this study, we present a model that can predict the inlet temperature of a reheat gas turbine based on Deep Neural Network (DNN), which is widely used in artificial neural networks, and verify the performance of the proposed DNN based on actual data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.117-124
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• 2024

The objective of Value Engineering (VE) is to derive the optimal value at the most efficient life cycle cost, comprising three stages: Pre-Study, Study, and Post-Study. In this study, we propose a method for information collection and analysis during planned site visit surveys in the preparation stage of VE. The 3D spatial model, created using a drone, facilitated observation and analysis of the study area from various angles, both from the center and the outside. Additionally, through the utilization of drones, we conducted on-site investigations of the research area's 3D spatial model, enabling a macroscopic perspective previously only feasible through a microscopic viewpoint during planned site visits in the pre-study phase. Furthermore, the utilization of actual spatial data obtained from observations allowed for real-time information verification during Design VE workshops, enhancing the efficiency and reliability of the VE project.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.1-12
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• 2024

Modern cities are actively adopting smart city services to address various urban challenges. Geospatial information acts as the foundational infrastructure of smart cities, promoting the sustainable development of urban areas. Consequently, as the standardization and utilization of geospatial information increase, the efficiency and sustainability of smart city operations improve. To achieve this, collaboration among diverse stakeholders is crucial for delivering optimal smart city services based on geospatial information. This paper defines smart city services, focusing on transportation and building-energy domains, based on the life cycle of geospatial information technology. Emphasis is placed on the importance of applying and utilizing geospatial information standards. Additionally, this paper proposes the Smart City based on Geospatial Information standards (SCGI) framework to provide insights into standardizing smart city services mapped to geospatial information standards. This research suggests a new paradigm for standardizing smart city services using geospatial information standards to offer customized solutions, thereby discussing the future development possibilities of smart cities.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.5
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• pp.271-279
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• 2023

Fouling is an inevitable problem in membrane water treatment plant. It can be measured by trans-membrane pressure (TMP) in the constant flux operation, and chemical cleaning is carried out when TMP reaches a critical value. An early fouilng alarm is defined as warning the critical TMP value appearance in advance. The alarming method was developed using one of machine learning algorithms, decision tree, and applied to a ceramic microfiltration (MF) pilot plant. First, the decision tree model that classifies the normal/abnormal state of the filtration cycle of the ceramic MF pilot plant was developed and it was then used to make the early fouling alarm method. The accuracy of the classification model was up to 96.2% and the time for the early warning was when abnormal cycles occurred three times in a row. The early fouling alram can expect reaching a limit TMP in advance (e.g., 15-174 hours). By adopting TMP increasing rate and backwash efficiency as machine learning variables, the model accuracy and the reliability of the early fouling alarm method were increased, respectively.