• 한국국방경영분석학회지
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• 제23권2호
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• pp.15-24
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• 1997

In this paper we suggested a performance evaluation model for future weapon systems. Weapon Performance Index(WPI) model transform the characteristics of alternatives as indices. We can easily obtain WPIs of alternatives with the model. The highest WPI recommended as the best solution. The performance elements in hierachy for future weapon systems are determined by systems engineering procedure. Priorities in hierachy can be determined through survey of experts engineering procedure. Priorities in hierachy can be determined through survey of experts and statistical analysis. Utility function is formulated as a probability model and utility score is predicted on the basis of historical data about the same category of weapon systems in the world. WPI is calculate from sum of product of priorities and utility scores. The model can be applied to trade-off analysis, cost and effectiveness analysis, war game model.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.351-353
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• 2006

Preventive maintenance can avail the generating unit to reduce cost and gain more profit in a competitive supply-side power market. so, it is necessary to perform reliability analysis on the systems in which reliability is essential. In this paper, FMECA assessment adopted using real historical failure data in Korean power plants for apply RCM analytical method. The stochastic FMECA is an engineering analysis and a core activity performed by reliability engineers to review the effects of probable failure modes of generating unit and assemblies of the power system on system performance. Optimal RCM schedule which is considered the severity level of each generating unit and failure probability from failure prediction of generating unit can be planned using proposed FMECA with IOE index.

• 전기학회논문지
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• 제56권2호
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• pp.254-259
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• 2007

PM(Preventive Maintenance) can avail the generating unit to reduce cost and gain more profit in a competitive supply-side power market. So, it is necessary to perform reliability analysis on the power systems in which reliability is essential. Thus, to schedule optimal PM planning based on reliability that is defined RCM(Reliability-Centered Maintenance), FMECA(Failure Mode Effects and Criticality Analysis) assessment is very important. Therefore, in this paper, the procedure of FMECA assessment for optimal RCM is proposed by probabilistic approach using real historical failure data of combustion-turbine generators in Korean power systems. The stochastic FMECA is performed based on the effects of probable failure modes of combustion-turbine generating unit.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2005년도 연구개발 발표회 논문집
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• pp.607-612
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• 2005

Check valves playa vital role in the operation and protection of nuclear power plants. Check valves failure in nuclear power plants often lead to a plant transient or trip. An overview of the failure history of check valves needs to identify key area where resources can be best applied to further improve their reliability, and provide cost effective means for failure reduction. The analysis of historical failure data gives information on the populations of various types of check valves, the systems they are installed in, failure modes, effects, methods of detection, and the mechanisms of the failures. The results presented are based on information derived from operating records, nuclear industry reports, manufacturer supplied information. A majority of check valve failures are caused by improper application. Failure modes are identified for swing and lift check valves. Failures involving improper seating and valve disc stuck comprised the largest percentage of failures.

• 대한가정학회지
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• 제42권4호
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• pp.179-186
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• 2004

The purpose of this study was to analyzed factors that influenced the degree of satisfaction difference of domestic and imported theatre costumes. One hundred and fifty theatrical artists were surveyed by questionnaires, and response from 128 was statistically analyzed. The data was analyzed using frequency, and paired t-test with SPSSWIN 10.0. The results were as follows. 1. The degree of satisfaction between domestic and imported theatrical costumes was different significantly. 2. The degree of satisfaction of domestic theatrical costumes was tow in the areas of design, color, fabric, and suitability with a historical background, compared with imported costumes. A major cause of the low degree of satisfaction was the lack of funds and professional theatrical costume designers. 3. The degree of satisfaction of imported theatrical costumes was low in the cost, size, and alteration and mending facilities, compared with the domestic costumes. The problems of size was caused by the shape difference between Koreans and a foreigners 4. further research should be conducted into the theatre costumes suitable for the domestic theatrical artists's size, and body shape.

• 전기학회논문지
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• 제57권8호
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• pp.1305-1310
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• 2008

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Journal of Smart Tourism
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• 제1권1호
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• pp.53-64
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• 2021

Upselling is often a critical factor in revenue generation for businesses in the tourism and travel industry. Utilizing passenger data from a major international airline company, we develop the PAX (Passenger, Airline, eXternal) model to predict passengers that are most likely to accept an upgrade offer from economy to premium. Formulating the problem as an extremely unbalanced, cost-sensitive, supervised binary classification, we predict if a customer will take an upgrade offer. We use a feature vector created from the historical data of 3 million passenger records from 2017 to 2019, in which passengers received approximately 635,000 upgrade offers worth more than $422,000,000 U.S. dollars. The model has an F1-score of 0.75, outperforming the airline's current rule-based approach. Findings have several practical applications, including identifying promising customers for upselling and minimizing the number of indiscriminate emails sent to customers. Accurately identifying the few customers who will react positively to upgrade offers is of paramount importance given the airline 'industry's razor-thin margins. Research results have significant real-world impacts because there is the potential to improve targeted upselling to customers in the airline and related industries.

• 산업경영시스템학회지
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• 제45권4호
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• pp.240-246
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• 2022

This paper introduces a container loading problem and proposes a theoretical approach that efficiently solves it. The problem is to determine a proper weight of products loaded on a container that is delivered by third party logistics (3PL) providers. When the company pre-loads products into a container, typically one or two days in advance of its delivery date, various truck weights of 3PL providers and unpredictability of the randomness make it difficult for the company to meet the total weight regulation. Such a randomness is mainly due to physical difference of trucks, fuel level, and personalized equipment/belongings, etc. This paper provides a theoretical methodology that uses historical shipping data to deal with the randomness. The problem is formulated as a stochastic optimization where the truck randomness is reflected by a theoretical distribution. The data analytics solution of the problem is derived, which can be easily applied in practice. Experiments using practical data reveal that the suggested approach results in a significant cost reduction, compared to a simple average heuristic method. This study provides new aspects of the container loading problem and the efficient solving approach, which can be widely applied in diverse industries using 3PL providers.

• 한국건설관리학회논문집
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• 제12권1호
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• pp.53-61
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• 2011

건축 프로젝트는 그 다양성과 특수성으로 인해 많은 불확실성을 갖고 있다. 이러한 불확실성을 해소하기 위해 공사비 예측은 건축 프로젝트의 전 과정에 걸쳐 반복적으로 이루어져야 하며 특히 초기단계의 공사비 예측은 효과적인 사업 추진을 위해 매우 중요한 과정이다. 통상 초기단계 공사비 예측은 과거에 수행되었던 실적공사와의 비교를 기반으로 하며, 이러한 원리를 이용한 기계학습방법이 사례기반추론이다. 사례기반추론은 해결하고자 하는 문제와 유사한 사례를 데이터베이스에서 검색, 수정하여 해답을 얻는 방법으로 이를 위해서는 속성 유사도와 속성 가중치의 정의가 필요하다. 그러나 속성 가중치를 결정하는 문제에 있어서, 기존의 방법들은 정성변수의 속성 가중치 결정이 불가능하다는 단점이 있으며, 이는 사례기반추론에 사용할 수 있는 변수를 한정시키기 때문에 공사비 예측의 정확성을 저해시키는 요인이 되고 있다. 따라서 본 연구는 최적화 문제를 해결하는 기법의 하나인 유전 알고리즘을 이용하여 정성변수의 속성 가중치 결정 방법을 제안하고, 이를 국방 병영생활관과 공공아파트에 적용하여 그 유효성을 검증하였다.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2004년도 제5회 정기학술발표대회 논문집
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• pp.317-322
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• 2004

도심지 건축 프로젝트가 초고층화, 대형화됨에 따라, 공사비와 공기의 관점에서 지하공사의 중요성은 점차 증가하고 있다. 지하공사 단계에서 대단히 중요한 것은 적정 말뚝공법을 선정하는 것이다. 그런데 말뚝공사의 경우, 공법 선정 시 고려해야 할 지반조건들이 많고, 불확실한 정보에 기반한 경험적인 공법선정이 이루어지기 때문에, 말뚝공법의 변경이 적지 않게 발생하며, 이것은 프로젝트의 공사비와 공기에 영향을 미친다 본 연구에서는 프로젝트의 설계단계에서 적정 말뚝공법을 선정하는데 활용하고, 시공전 단계에서 기 선정된 말뚝공법의 적정여부를 검증할 수 있는 말뚝공법 선정모델을 제안하였다. 실적데이터에 근간한 신경망 모델은 이미 그 효율성이 입증된 바 있다. 2000년부터 2004년까지 국내에서 시행된 150개의 데이터를 기초로 하여 말뚝공법 선정을 위한 신경망 모델을 개발하였다. 개발한 신경망 모델을 대상으로 학습용 자료에 의해 최적화를 실행하였으며, 그 유효성을 검증하였다.