• Journal of the Korea Institute of Building Construction
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• v.10 no.6
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• pp.1-6
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• 2010

To analyze the total cost of ownership in a building construction project, we have to consider initial plan, maintenance and operation cost, in addition to the design and construction cost. This is called "Life Cycle Cost (LCC)." Currently, it is difficult to analyze LCC because of a lack of data and the appropriate criteria. This study tries to suggest a way to analyze the LCC of building construction projects, and apply it to case studies of modern apartment houses and Han-Ok, a type of traditional Korean house. The case studies found that a Han-Ok is more efficient than a modern apartment house from an LCC point of view, in terms of maintenance and operation cost.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.777-783
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• 2007

Life cycle costing is one of the most effective cost approaches when we choose a solution from series of alternative so the least long-term cost ownership is achieved. Life cycle costing in railway industry has been focused on the prediction of investment for railway vehicles. But in today, the life cycle cost, LCC, prediction on the aspect of operation and maintenance cost through whole life cycle is highly necessary. In this paper, we present a strategy for the development of life cycle cost estimation software on the aspect of maintenance strategies of railway vehicle. For this purpose, we suggested a structure of LCC software based on the UNIFE LCC model. And we developed a pilot version of software to evaluate the LCC model that we suggested for railway vehicle. We performed LCC analysis on the brake module of metro vehicle in case study and concluded that the software and model developed in this research could enough to support engineers in choosing better cost effective solutions from many alternatives.

• Journal of the Korean Solar Energy Society
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• v.24 no.4
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• pp.55-63
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• 2004

The purpose of this study is to development of life cycle cost analysis methodology of HVAC system for decision maker. The results of this study are as follows; maintenance/management, equipment construction, planning/design, and demolition/sell phases (1) To develop the cost breakdown structure for LCC in HVAC system, this study apply the method of additional pertinent level, title, CBS number, block number and variable index. (2) LCC analysis order of HVAC system compose four phase. (3) Life cycle costing influence diagram can bring us to make the most efficient decision through a visual graphical diagram that is shown relationship among variables and that decision maker traces easily from life cycle cost analysis situation.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.85-94
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• 2004

As over 70% of the total life cycle cost (LCC) of a product is committed at the early design stage, designers are in an important position to substantially reduce the LCC of the products they design by giving due to life cycle implications of their design decisions. During early design stages, there may be competing concepts with dramatic differences. In addition, the detailed information is scarce and decisions must be made quickly. Thus, both the overhead in developing parametric LCC models fur a wide range of concepts, and the lack of detailed information make the application of traditional LCC models impractical. A different approach is needed, because a traditional LCC method is to be incorporated in the very early design stages. This paper explores an approximate method for providing the preliminary LCC, Learning algorithms trained to use the known characteristics of existing products might allow the LCC of new products to be approximated quickly during the conceptual design phase without the overhead of defining new LCC models. Artificial neural networks are trained to generalize product attributes and LCC data from pre-existing LCC studies. Then the product designers query the trained artificial model with new high-level product attribute data to quickly obtain an LCC for a new product concept. Foundations fur the learning LCC approach are established, and then an application is provided.

• Korean Journal of Construction Engineering and Management
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• v.15 no.3
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• pp.113-119
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• 2014

Recently, the demand on the practical application of life-cycle cost effectiveness for design and rehabilitation of structure is rapidly growing unprecedently in engineering practice. Accordingly, in the 21st century, it is almost obvious that life-cycle cost together with value engineering will become a new paradigm for all engineering decision problems in practice. However, in spite of impressive progress in the researches on the LCC, the most researches have only focused on the Deterministic or Probabilistic LCC analysis approach (Level-1 LCC Model) at design stage. Thus, the goal of this study is to develop a practical and realistic methodology for the Lifetime risk based Life-Cycle Cost (LCC)-effective optimum decision-making at design stage.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.557-566
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• 2002

This paper presents an optimum deck and girder system design for minimizing the life-cycle cost(LCC) of steel box girder bridges. The problem of optimum LCC design of steel box girder bridges is formulated as that of minimization of the expected total LCC that consists of initial cost, maintenance cost and expected retrofit costs for strength, deflection and crack. To demonstrate the cost effectiveness of LCC design of steel box girder bridges, the LCC optimum design is compared with conventional design method for steel box girder bridges. From the numerical investigations, it may be positively stated that the optimum design of steel box girder bridges based on LCC will lead to mote rational, economical and safer design.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.155-174
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• 2005

Parametric life-cycle cost(LCC) models have been integrated with traditional design tools, and used in prior work to demonstrate the rapid solution of holistic, analytical tradeoffs between detailed design variations. During early designs stages there may be competing concepts with dramatic differences. Additionally, detailed information is scarce, and decisions must be models. for a diverse range of concepts, and the lack of detailed information make the integration make the integration of traditional LCC models impractical. This paper explores an approximate method for providing preliminary life-cycle cost. Learning algorithms trained using the known characteristics of existing products be approximated quickly during conceptual design without the overhead of defining new models. Artificial neural networks are trained to generalize on product attributes and life cycle cost date from pre-existing LCC studies. The Product attribute data to quickly obtain and LCC for a new and then an application is provided. In additions, the statistical method, called regression analysis, is suggested to predict the LCC. Tests have shown it is possible to predict the life cycle cost, and the comparison results between a learning LCC model and a regression analysis is also shown

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2176-2181
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• 2011

This paper estimates the life cycle cost(LCC) of a propulsion control system using the maintenance information in the high speed train(KTX-1). Life cycle costing is one of the most effective approaches for the cost analysis of long-life systems such as the KTX-1. Until now, most life cycle cost of the system has been studied as a whole system viewpoint. But in case of railway industry, LCC studies are needed on the subsystem like a propulsion control system because subsystems are developed continuously localization. This paper proposes the life cycle cost model which fitted to estimate life cycle cost (LCC) using maintenance information manual. As a result, LCC on propulsion control system increased moderately expect for periodical time when major parts are replaced at the same time. Results will be reflected in the development of domestic products.

• Korean Journal of Construction Engineering and Management
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• v.2 no.4 s.8
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• pp.135-143
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• 2001

The purpose of this study is to estimate and analyze the optimum economic life of office buildings in consideration of their LCC (Life Cycle Cost), and thereby, explore the ways to manage the outlived office buildings economically. In estimating the economic life, initial investment cost and maintenance cost are taken into due consideration. For this study, those office buildings in Yeouido and Mapo region were sampled. The surveyed details were reduced to unit area to calculate a unit value, and then, their optimum economic life was estimated using LCC. Five alternatives for management of outlived office buildings were compared in terms of reconstruction or rehabilitation cost.

• Journal of the Korea Institute of Building Construction
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• v.8 no.1
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• pp.97-102
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• 2008

The report of the Korean Board of Audit and Inspection(BAI) on May 2007 indicates the problems of Life Cycle Cost (LCC) analysis and evaluation in the Design-Build(Turn-Key) and alternative bidding system. The point which the report indicates is that the cost estimation system for LCC analysis has nothing in common each other and there's no consistency among the repair cycle and ratio per facilities parts. For solving these problems, BAI demands the establishment of the guidelines for LCC analysis and evaluation from the competent authority Korean Ministry of Construction And Transportation(MOCT). The objective of this study is to develop the improvement directions for LCC analysis and evaluation which are suitable to the public construction projects especially for the Design-Build and alternative bidding system in Korea. For this study, the LCC related raws and regulations, LCC analysis guidelines of public cooperations, actual condition of LCC analysis and evaluation which include, the elements of LCC, the estimation rules of the initial cost and the maintenance cost, the analysis standards of time value of money, etc. are investigated to provide the improvement directions for LCC analysis and evaluation.