• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.244-244
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• 1993

• Proceedings of the Korean Nuclear Society Conference
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• 2002.05a
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• pp.180.1-180
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• 2002

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1569-1570
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• 2011

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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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.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.3
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.19-25
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• 2016

Engineering structures including civil infrastructures require a life-cycle cost and benefit during their service lives. The service life of a structure can be extended through appropriate inspection and maintenance actions. In general, this service life extension requires more life-cycle cost and cumulative benefit. For this reason, structure managers need to make a rational decision regarding the service life management considering both the cost and benefit simultaneously. In this paper, the probabilistic decision tool to determine the optimal service life based on cost-benefit analysis is presented. This decision tool requires an estimation of the time-dependent effective cost-benefit under uncertainty to formulate the optimization problem. The effective cost-benefit is expressed by the difference between the cumulative benefit and life-cycle cost of a deteriorating structure over time. The objective of the optimization problem is maximizing the effective cost-benefit, and the associated solutions are the optimal service life and maintenance interventions. The decision tool presented in this paper can be applied to any deteriorating engineering structure.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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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.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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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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• v.10 no.2
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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.