• Korean Management Science Review
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• v.26 no.1
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• pp.209-223
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• 2009

In this paper, an analysis problem of repair levels and spare part allocation for MIME(Multi indenture multi echelon) systems is studied using simulation and meta-heuristics. We suggest a method to determine simultaneously repair levels and spare parts allocation to minimize the life cycle cost of MIME system under availability constraint. A simulated annealing method is used to analyze the repair levels and genetic algorithm is used to obtain the optimal allocation of spare parts. We also develop a simulation system to calculate the life cycle cost and system availability. Some numerical examples are also studied.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.311-316
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• 2020

The main cause of DMSMS is the rapid replacement cycle and short life cycle of parts, according to the development of science, compared to the long life cycle of weapons systems. In particular, the problem of the supply and demand of such parts becomes even more acute during the operation maintenance phase after the mass production and power generation stage. To eliminate DMSMS problems that arise continuously from development to the operation of weapon systems and select the most cost-effective countermeasures to obsolescence, this paper suggests a standard to determine the appropriate time for quantitative performance improvement by conducting total life cycle cost analysis. For such purpose, this study examined the domestic and overseas cost analysis methods and applied it to single domestic weapon system to verify the research. This study responds to the issue of discontinuing components and helps reduce the total life cycle cost of military products.

• Clean Technology
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• v.7 no.2
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• pp.99-107
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• 2001

Optimization methodologies have been proposed of find the best environment-friendly recycling pathways of plastic materials based on life-cycle assessment (LCA) methodology. The main difficulty in conducting this optimization study is that multiple environmental burdens have to be considered simultaneously as the cost functions. Instead of generating conservative Pareto or noninferior solutions following multi-objective optimization approaches, we have proposed some practical criteria on how to combine the different environmental burdens into a single measure. The obtained single objective optimization problem can then be solved by conventional nonlinear programming techniques or, more effectively, by a tree search method based on decision flows. The latter method reduces multi-dimensional optimization problems to a set of one-dimensional problems in series. It is expected the suggested tree search approach can be applied to many LCA studies as a new promising optimization tool.

• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.89-98
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• 2011

This study examined the energy performance according to the main design parameters of a solar water heating system for an office building using the life cycle cost (LCC) optimization simulations. The LCC optimization simulations of the system were conducted with TRNSYS and GenOpt employing the Hooke-Jeeves algorithm for cases where water temperature was $60^{\circ}C$ and $50^{\circ}C$. The results showed that for water temperature at $60^{\circ}C$ and $50^{\circ}C$ the global radiation incident on the collector could be decreased by 16.98% and 28.52%, collector useful energy gain could be decreased by 15.04% and 22.59%, energy to load from storage tank could be decreased by 10.86% and 18.06% and AH energy to load could be increased by 16.86% and 38.50% respectively compared to a non-optimized system. The annual average collection efficiency of the collector was increased by 0.88% for $60^{\circ}C$ and 2.78% for $50^{\circ}C$ because of increase of collector slope and decrease of the mass flow rate per collector area. The annual average efficiency of the system was increased by 1.74% and 3.47% compared to the basis system. However, the annual solar fraction of the system was decreased by 6.68% for $60^{\circ}C$ and 11.26% for $50^{\circ}C$ due to decrease of collector area and storage tank volume.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.1
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• pp.17-23
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• 2013

The BESS(Battery Energy Storage System) is an useful device for load leveling, but the high cost, installation space and safety issues are the main barriers for supplying it widely. The important factor in supplying BESS to customers successfully is the payback period. As most of the H/W cost factors are uncontrollable, the optimization of storage volume can be useful factor in improving payback period. In order to obtain optimized BESS volume, the load factor, demand ratio, peak shaving ratio, electric rates and benefits from DR participation of customer should be analyzed. In this paper, we could verify the peak cutting capability and cost effectiveness under the some proposed conditions and changing value of PCS and battery based on the customers data after volume optimization process was applied, and we can identified the saturation point of load factor and shortening of customer's payback period.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.984-991
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• 2015

This paper presents the methodology for optimal design of power grid for offshore wind power plant (OWPP) and optimum location of offshore substation. The proposed optimization process is based on a genetic algorithm, where the objective cost model is composed of investment, power loss, repair, and reliability cost using the net present value during the whole OWPP life cycle. A probability wind power output is modeled to reflect the characteristics of a wind power plant that produces electricity through wind and to calculate the reliability cost called expected energy not supplied. The main objective is to find the minimum cost for grid connection topology by submarine cables which cannot cross each other. Cable crossing was set as a constraint in the optimization algorithm of grid topology of the wind power plant. On the basis of this method, a case study is conducted to validate the model by simulating a 100-MW OWF.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.109-120
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• 2007

In this study, a bridge maintenance system is developed to generate performance-based optimum maintenance strategy by considering the life-cycle cost. A multi-objective combinatorial optimization problem is formulated to generate a tradeoff maintenance scenarios which satisfies the balance among the conflicting objectives such as the performance and cost during the bridge lifetime and a genetic algorithm is applied to the system. By using the developed program, this study proposes a process of optimum maintenance scenario applying to the steel girder bridge of national road. The developed system improves the current methods of establishing the bridge maintenance strategy and can be utilized as an efficient tool to provide the optimum bridge maintenance scenario corresponding to the various constraints and requirements of bridge agency.

• Transactions of Materials Processing
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• v.17 no.7
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• pp.481-485
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• 2008

The subframe type rear suspension consisting of a side member and a front/rear cross member is widely used in a medium car and full car. In the small car case, the beam of tubular type without independent suspension system is used to reduce manufacturing cost. In this study, a subframe type rear suspension by hydroforming has been developed. In designing suspension, a driving stability and durability should be considered as an important factor for the performance improvement, respectively. Thus, we focus on increasing the stiffness of suspension and decreasing the maximum stress affecting a durability cycle life. Several optimization design techniques such as shape, size, and topology optimization are implemented to meet these requirements. The shapes of rear suspension obtained from optimization are formed by using hydroforming process. Through commercial software based on the finite element, the superiority of this design method is demonstrated.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.544-549
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• 2005

Nowadays, most of bridge networks are complete or close to completion. The biggest challenge railroad./highway agencies and departments of transportation face is the maintenance of these networks, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is an urgent need to predict their remaining life from a system reliability viewpoint. And, it is necessary to develop the maintenance models based on system reliability concept. In this paper, maintenance models are developed for preventive maintenance and essential maintenance by using system reliability and lifetime distributions. The proposed model is applied to an existing railroad bridge. The optimal maintenance strategy of this bridge is obtained in terms of services life extension and cumulative maintenance cost.