• 품질경영학회지
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• 제31권1호
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• pp.142-147
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• 2003

Burn-in is a widely used method to eliminate the initial failures. Preventive maintenance policy such as block replacement with minimal repair at failure is often used in field operation. In this, paper burn-in and maintenance policy are taken into consideration at the same time. The cost of a minimal repair is assumed to be a non-decreasing function of its age. The problems of determining optimal burn-in times and optimal maintenance policy are considered.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.147-151
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• 2002

Burn-in is a widely used method to eliminate initial failures. Preventive maintenance policy such as block replacement with minimal repair at failure is often used in field operation. In this paper burn-in and maintenance policy are taken into consideration at the same time. The cost of a minimal repair is assumed to be a non-decreasing function of its age. The problems of determining optimal burn-in times and optimal maintenance policy are considered.

• 한국터널지하공간학회 논문집
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• 제24권1호
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• pp.57-78
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• 2022

TBM의 굴착효율을 높이는 가장 중요한 인자인 디스크커터와 커터비트는 커터헤드 설계 및 시공 시 핵심요소로 지반조건에 맞는 디스크커터의 배치, 간격, 개수, 크기, 재질 등은 TBM 공사의 성패를 좌우한다. 또한, 디스크커터는 대표적인 소모성 부품으로 교체횟수에 대한 정확한 예측이 수반되지 않으면, 공사비는 물론 공사에 막대한 지장을 초래 할 수 있다. 이에 본 연구에서는 대구경 이수식 쉴드TBM 현장에 대하여 설계 시 산정된 디스크커터의 교체횟수와 실제 시공 시 발생한 디스크커터의 마모깊이 및 교체위치에 대하여 현장데이터를 분석하여 비교·연구하였다. 정량적인 비교를 위하여 일정한 굴진데이터를 나타내는 구간에서 지반에 따라 풍화토/풍화암, 연암, 경암으로 나누어 구분하였으며, 디스크커터의 위치에 따라 동심원의 궤적이 다르므로 위치에 따라 비교분석 하였다.

• 한국콘텐츠학회논문지
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• 제4권3호
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• pp.71-80
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• 2004

분산파일시스템 환경에서는 디스크 접근 비용을 줄이기 위해 각 노드에 캐시된 데이터를 서로 공유하는 협력캐시 알고리즘이 사용된다. 협력캐시 알고리즘은 분산되어있는 시스템들의 캐시정보를 서로 공유하여 가상으로 더 큰 캐시를 형성함으로써 캐시 히트율을 높이고 디스크 접근을 줄이는 방법이다. 기존에 제안된 협력캐시 알고리즘들은 캐시에 대한 근사정보를 이용하여 메시지 비용을 줄이고, 로컬캐시영역과 글로벌캐시 영역을 가변적으로 사용하여 캐시 히트율을 높이고 있다. 또한 버퍼 교체 시 교체된 버퍼를 비활동적인 노드로 보내어 계속 캐시에 유지하도록 하여 전역 버퍼 히트율을 높이는 장점을 갖는다. 그러나 잘못된 근사정보가 성능을 저하시킬 수 있으며 일관성 유지를 위한 메시지교환 비용이 많이 든다는 단점을 갖고 있다. 또한 비활동적인 노드를 선정하기 위해 사용되는 각 노드의 에이지 정보 관리비용이 많이 드는 단점을 갖고 있다. 본 논문에서는 정확한 캐시정보를 유지하며 일관성 유지비용과 버퍼 에이지 정보 관리비용을 최소화시키는 협력캐시 알고리즘을 제안한다. 그리고 성능평가를 통해 기존의 협력캐시 알고리즘과 비교하여 제안하는 알고리즘의 우수성을 보인다.

• 대한안전경영과학회지
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• 제20권3호
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• pp.27-36
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• 2018

The steel pipe manufacturing industry deals with facilities and materials. Especially thermal facilities are close to vapor cloud explosion (VCE) and may cause secondary damage to facilities because they deal with corrosive substances such as hydrofluoric acid, sulfuric acid and acid, fire, explosion, leakage etc. It is in danger. In this study, hazard identification method was conducted using HAZOP techniques and quantitative risk analysis was conducted using e-CA, a program that supports accident impact analysis. Equipment in the influence range of ERPG - 3 was determined to be a facility requiring replacement. It was decided that neutralization is necessary using slaked lime. Based on the cost of loss, We presented the proper replacement which is the timing of the dangerous facility. As a result, It was ideal to replace the facilities with 20 years of heat treatment facilities, one year of hydrofluoric acid storage tank, 20 years of sulfuric acid storage tank, and 5 years of hydrochloric acid storage tank.

• 대한안전경영과학회지
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• 제10권3호
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• pp.117-126
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• 2008

RFID system the key technology of ubiquitous era, has been emphasized in logistics. Logistic enterprises are required to apply RFID systems considering their investment costs, actual effectiveness, operational satisfaction and so on. For such a purpose, many applicable methods of RFID system have been developed A method that RFID tags are directly attached to products or pallets is utilized in most cases. However, this method requires expensive investment cost, frequent replacement of damaged tags for the small and medium (SM) third party logistics. In this paper, we analyze statistically the current status and requirements of SM third party logistics. Based on their requirements, we propose the realtime warehousing-delivery management by the method to attach a RFID tag to each warehouse rack, together with the economy analysis index in order to evaluate economical efficiency. Consequently, this method is expected to reduce Investment cost and to improve operational effectiveness and satisfaction.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권2호
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• pp.114-121
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• 2018

Purpose: This study proposes a process for evaluating the preventive maintenance policy for a system with degradation characteristics and for calculating the appropriate preventive maintenance cycle using time- and condition-based maintenance. Methods: First, the collected data is divided into the maintenance history lifetime and degradation lifetime, and analysis datasets are extracted through preprocessing. Particle filter algorithm is used to estimate the degradation lifetime from analysis datasets and prior information is obtained using LSE. The suitability and cost of the existing preventive maintenance policy are each evaluated based on the degradation lifetime and by using a minimum repair block replacement model of time-based maintenance. Results: The process is applied to the degradation of the reverse osmosis (RO) membrane in a seawater reverse osmosis (SWRO) plant to evaluate the existing preventive maintenance policy. Conclusion: This method can be used for facilities or systems that undergo degradation, which can be evaluated in terms of cost and time. The method is expected to be used in decision-making for devising the optimal preventive maintenance policy.

• KIEAE Journal
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• 제16권5호
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• pp.39-45
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• 2016

Purpose: The purpose of this study is to analyze the energy saving and cost benefit analysis of the Low-income Energy Efficiency Treatment Program supported by KOREF(Korea Energy Foundation). This program was launched in 2007 and performs building energy retrofit for the low-income and energy poverty houses. Method: Energy simulation and cost benefit analysis were accomplished for the low-income detached houses. The structure of detached house was a lot og block structure, wood frame (single glass) and concrete roof. Baseline model of the low-income detached houses was proposed. Result: Annual heating energy consumptions were decreased by about 3.2% with the window system replacement(Case 1), 9.3% with reinforcement of insulation(Case2), and 12.5% with both(Case 3) compared to those of baseline model. The construction cost will be recouped within 5 years for the Case 1, 3 years for the Case 2, and 3 years for the Case 3. Case 3 was the most cost beneficient construction method in the analyzed cases in this study.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.386-397
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• 2007

One major development in bridge life cycle cost analysis (LCCA) in recent years is to develop deterioration model for bridge components so that the times of repair/replacement throughout a component's life span can be properly determined. Taiwan also developed her own bridge LCCA model in 2003, integrating with the bridge inspection database in the local bridge management system (T-BMS). Under the framework of the local LCCA model, this study employs the reliability method in developing a deterioration model of bridge components. A component deteriorates through time in its reliability, which represents the probability of a component's condition index exceeds a user specified threshold. Model assumptions and rationale are described in the paper. The steps for applying the developed model are explained in detail. Results and findings are reported.

• 품질경영학회지
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• 제52권1호
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.