• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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• pp.244-244
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• 1993

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2002년도 춘계공동학술발표회요약집
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• pp.180.1-180
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• 2002

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.1569-1570
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• 2011

• 대한산업공학회지
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• 제40권1호
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• pp.118-127
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• 2014

The configuration such as series, parallel and k-out-of-n of a repairable system directly affects its reliability. The maintenance strategy can also affect the overall performance of the system. The objective of this work is to investigate the possible trade-off between the configuration of a repairable k-out-of-n system and its maintenance strategy. The redundancy is considered to be the design decision variables, whereas the preventive maintenance period is considered to be the maintenance decision variables. The optimization model is used to minimize the overall life cycle cost associated with the system, considering constraint on reliability. Finally, genetic algorithm is used to find the optimal values for the decision variables. The result is compared with optimal values for considering redundancy and maintenance respectively.

• International Journal of Aeronautical and Space Sciences
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• 제17권3호
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• pp.423-431
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• 2016

In this study, wing design optimization for long-endurance unmanned aerial vehicles (UAVs) is investigated. The fluid-structure integration (FSI) analysis is carried out to simulate the aeroelastic characteristics of a high-aspect ratio wing for a long-endurance UAV. High-fidelity computational codes, FLUENT and DIAMOND/IPSAP, are employed for the loose coupling FSI optimization. In addition, this optimization procedure is improved by adopting the design of experiment (DOE) and Kriging model. A design optimization tool, PIAnO, integrates with an in-house codes, CAE simulation and an optimization process for generating the wing geometry/computational mesh, transferring information, and finding the optimum solution. The goal of this optimization is to find the best high-aspect ratio wing shape that generates minimum drag at a cruise condition of $C_L=1.0$. The result shows that the optimal wing shape produced 5.95 % less drag compared to the initial wing shape.

• 한국자동차공학회논문집
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• 제15권3호
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• pp.63-71
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• 2007

During the design phase of a product, reliability and design engineers are called upon to evaluate the reliability of the system, The question of how to meet target reliability for the system arises when estimated reliability or cost is inadequate. This then becomes a problem of reliability allocation and system structure design. This study proposes the optimization methodology to achieve target reliability with minimum cost through construction of the cost function of system. In cost function, total cost means the sum of initial cost, repair cost and maintenance cost. This study constructs optimization problem about system structure design and reliability allocation using cost function. This problem constructed is solved by Multi-island Genetic Algorithm(MIGA), and applies to urban transit brake system. Current brake system of the urban transit is series system. Series system is the simplest and perhaps one of the most common system, but it demands high reliability and maintenance cost because all components must be operating to ensure system operation. Thus this study makes a comparative study by applying k-out-of-n system to brake system. This methodology presented can be a great tool for aiding reliability and design engineers in their decision-makings.

• 한국산학기술학회논문지
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• 제17권4호
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• pp.19-25
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• 2016

사회기반시설물을 포함한 구조물은 수명유지 또는 연장을 위하여 적절한 점검과 유지보수가 필수적이다. 이러한 점검과 유지보수는 일반적으로 생애주기비용 평가를 통해 관련 계획이 수립된다. 본 논문에서는 구조물의 생애주기비용과 그 사용으로 인해 발생되는 이익을 고려하는 확률론적 비용-이익분석과 이를 통한 구조물 최적수명 결정 방법을 다루고자 한다. 생애주기비용은 구조물 초기 제작/건설비용, 유지보수 비용과 구조물 파괴로 인한 예상손실을 고려하게 된다. 일반적으로 구조물의 수명연장은 생애주기비용의 증가를 유발하나 사용기간 증가로 인해 발생되는 이익 또한 증가하여, 이를 최적화하는 수명관리에 관심을 가질 필요가 있다. 생애주기 평가에 있어서 유지보수 적용이 구조성능, 구조물 파괴확률 그리고 수명에 미치는 영향을 확률론적 방법을 적용하여 평가하며, 이를 통해 생애주기비용과 이익의 차이를 목적함수로 구성하게 된다. 이 목적함수가 최대가 되는 지점이 설계변수인 구조물 최적수명이 되는데, 최적화문제 구성에 있어서 제한조건의 변화에 따라 유지보수 계획수립도 가능하다. 본 논문에서 다루어지는 구조물 수명관리 최적화기법이 안전성과 효율성을 동시에 고려하는 사회기반시설물 수명관리에 기여할 것으로 기대한다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.73-78
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• 2005

This paper considers a preventive maintenance policy following the expiration of renewing warranty, Most preventive maintenance models assume that each PM costs a fixed predetermined amount regardless of the effectiveness of each PM. However, it seems more reasonable to assume that the PM cost depends on the degree of effectiveness of the PM activity. In this paper we consider a periodic preventive maintenance policy following the expiration of renewing warranty when the PM cost is an increasing function of the PM effect. The optimal number and period for the periodic PM policy with effect dependent cost that minimize the expected cost rate per unit time over an infinite time span are obtained.

• 전기학회논문지
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• 제56권11호
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• pp.1892-1902
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• 2007

This paper presents a new generating unit maintenance scheduling algorithm considering regional reserve margin and transfer capability. Existing researches focused on reliability of the overall power systems have some problems that adequate reliability criteria cannot be guaranteed in supply shortage regions. Therefore specific constraints which can treat regional reserve ratio have to be added to conventional approaches. The objective function considered in this paper is the variance (second-order momentum) of operating reserve margin to levelize reliability during a planning horizon. This paper focuses on significances of considering regional reliability criteria and an advanced hybrid optimization method based on PSO algorithm. The proposed method has been applied to IEEE reliability test system(1996) with 32-generators and a real-world large scale power system with 291 generators. The results are compared with those of the classical central maintenance scheduling approaches and conventional PSO algorithm to verify the effectiveness of the algorithm proposed in this paper.

• Structural Monitoring and Maintenance
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• 제10권2호
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• pp.175-190
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• 2023

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.