• 한국건축시공학회지
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• 제10권6호
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• pp.1-6
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• 2010

건축물의 총 소유비용을 분석하기 위해서는 초기단계의 설계와 시공비용 이외에도 기획비용, 유지관리 및 운영비용을 고려해야 한다. 이를 LCC(Life Cycle Cost)라고 부른다. 현재, 충분한 데이터와 기준의 부족으로 인해 LCC의 분석에 많은 어려움을 겪고 있다. 본 연구에서는 건축물의 LCC 분석 방법을 제시하고, 현대식 아파트와 전통 한옥 주택에 대한 LCC 사례 분석을 수행하고자 한다. 사례 연구의 결과 한옥이 현대식 아파트에 비해 유지보수와 운영 비용에 있어서 보다 효율적인 것으로 조사되었다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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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.

• 한국태양에너지학회 논문집
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• 제24권4호
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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.

• 한국정밀공학회지
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• 제21권9호
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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.

• 한국건설관리학회논문집
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• 제15권3호
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• pp.113-119
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• 2014

LCC 분석은 건축물의 설계단계 뿐만 아니라 유지관리 단계에서의 보수 보강 또는 교체에 대한 최적 의사결정의 도구로서 이론적으로나 실무적으로 각광을 받고 있는 분석 방법이다. 이는 초기 투자비용의 효율성을 극대화 하고 유지관리를 통한 구조물 사용성의 효율적 증대를 극대화하는 노력의 일환으로 최근 건축물의 설계 및 유지관리 시 LCC 분석효과의 실질적인 적용이 요구되어 지고 있다. 따라서 본 논문은 일반적인 분석기법에 그치고 있는 기존 LCC 연구를 생애위험도를 고려한 LCC분석을 통해 설계단계 최적 의사결정을 위한 새로운 분석 방법론을 도출하였다.

• 한국전산구조공학회논문집
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• 제15권4호
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• pp.557-566
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• 2002

본 논문에서는 강상자형교의 바닥판과 주형에 대한 생애주기비용(Life-Cycle Cost : LCC)를 고려한 최적설계 방법을 제안하였다. 생애주기비용의 최적설계 문제는 초기비용, 유지관리비용 그리고 강도와 처짐 그리고 균열에 대한 파손 기대비용의 최소화 문제로 정식화할 수 있다. 기존의 재래적인 설계방법과의 비교를 동해서 강상자형교의 생애주기비용 최적설계의 우수성을 입증하였다. 또한 수치적인 결과의 고찰을 통하여 LCC에 근거한 최적설계가 여타의 설계방법들보다 좀 더 합리적이고 경제적이며 안전한 설계를 유도하는 것으로 분석되었다.

• 대한안전경영과학회지
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• 제7권5호
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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

• 전기학회논문지
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• 제60권11호
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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.

• 한국건설관리학회논문집
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• 제2권4호
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• pp.135-143
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• 2001

본 연구는 오피스건축물의 최적경제수명을 Life Cycle Cost를 고려하여 추정분석하고, 이를 통해 최적경제수명 이후의 건축물을 어떻게 관리하는 것이 경제적으로 유리한가에 대한 것이다. 경제수명의 추정에서 초기투자비와 유지관리비를 중요한 요소로 고려하여, 여의도$\cdot$마포지역의 오피스건물을 대상으로 조사한 내용을 단위면적 당 동일한 가치로 환산한 뒤, LCC를 이용하여 최적경제수명을 추정하였다. 마지막으로 최적경제수명 이후의 관리방법으로 재건축 및 보수공사 시 투입되는 금액에 따라 5개의 안으로 비교하였다.

• 한국건축시공학회지
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• 제8권1호
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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.