• 산업경영시스템학회지
• /
• 제33권3호
• /
• pp.55-62
• /
• 2010

Currently, cost estimation is very important to the government acquisition programs to support decisions about funding and to evaluate resource requirement as key decision points. Parametric cost estimating models have been used extensively to obtain appropriate cost estimates in early acquisition phase. However, they have many restrictions to ensure the cost estimating result in Korean defense environment because they are developed in the U.S.A. environment. In order to obtain a good R&D cost estimate, developing our own CERs (Cost Estimation Relationships) using historical R&D data is essential. Nevertheless, there has been little research to develop our own CERs. In this research, we established a CER development process and found some cost drivers in the historical movement weapon system R&D data. The R&D CER is developed using the PCR(Principle Component Regression) method to remove multicollinearity among data and to overcome the restriction of the insufficient number of sample. At least, this research is meaningful as a first attempt in terms of defining the CER development process and obtaining our own R&D CER based on the historical data in Korean weapon system R&D environment.

• 한국국방경영분석학회지
• /
• 제27권1호
• /
• pp.10-27
• /
• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• 산업공학
• /
• 제25권3호
• /
• pp.347-356
• /
• 2012

The acquisition cost of defense weapon system has been continuously increasing because of art-of-technology of it. This phenomenon requires efficiency and transparency in the weapon system acquisition process through cost estimation. Therefore cost estimation is very important to the government acquisition programs to support decisions about funding and to evaluate resource requirement as a key decision point. The Commercial parametric cost estimating models have been using extensively to obtain appropriate cost estimates in early acquisition phase. These models have many restrictions to ensure the cost estimating result in Korean defense environment because they are developed based on foreign R&D data. Also estimation results are different from Korean defense industry accounting system. So, some studies have been tried to develop a CER (Cost Estimation Relationship) based on the Korean historical data. However, there are some restrictions to improve the predictability and ensure the stability of the developed singular CERs which consider the following data characteristics individually. The the abnormal conditions of data that is multicollinearity, outlier and heteroscedasticity under rack of the number of observations. In this paper, a CER's Linear Combining Model is proposed to overcome those limitations which guarantee more accurate estimation (25.42% higher precision) than other singular CERs. At least, this study is meaningful as a first attempt to improve the predictability of CER with insufficient data. The methodology suggested in this study will be useful to develop a complex Korean version cost estimating model development in future.

• 대한토목학회논문집
• /
• 제31권4D호
• /
• pp.595-601
• /
• 2011

고속철도 기본계획단계에서 노반공사의 토공사 공사비 추정은 단위길이당 공사비(원/km)를 활용하고 있다. 이 단가는 과거자료를 기준으로 한 산술평균으로 오차가 클 수 있으며, 기본설계 단계 등 다음단계의 견적과 연계성이 부족한 단점이 있다. 본 연구는 철도연장에 토공사의 기술적 특성인 지질조건을 추가하는 매개변수 기반 개략공사비 산정모델을 제시한다. 데이터분석은 회귀분석법을 적용하였으며, 독립변수는 길이, 지질(토사, 풍화암, 연암, 경암) 구성 비율이고, 36개 공구 실적공사비를 참조하였다. 개발된 모델은 실적공사비와 비교한 결과 -0.4% ~ +31% 범위로 나타나, 전형적 범위인 -30% ~ +50% 이내이므로 유효한 것으로 판정한다. 본 모델은 공사비 영향의 주요요인인 길이에 기술적 특성인 지질요건을 추가함으로써 공사비 산정결과의 신뢰도 향상을 꾀함으로써 단계별 효과적 총사업비관리, 재정지출 감소 및 사업의 경제성 확보에 기여할 수 있을 것으로 기대된다.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2009년도 춘계학술대회 논문집
• /
• pp.331-340
• /
• 2009

This study is objected by suggesting rationalization method of management and maintenance cost for railway investment assessment. The estimate of rational benefit and cost are a work of vital importance to decide railway investment as preliminary feasibility investigation is institutionally reinforced since January 2007. In particular, railway management and maintenance cost have to be applied to realistic and detail cost as railway investment assessment guide. For example, types of railway, construction of new line, improvement of conventional line, double tracking, railway electrification. However, railway investment assessment is inconsistency because of estimating the railway management and maintenance cost using existing unrealistic management and maintenance cost. Therefore, this study is performed parametric analysis effecting on the railway management and maintenance cost considered new technique, enhanced facilities and improved standard. Also, it suggests the itemized standard management and maintenance cost. Finally, it will be helped to establish the base of railway investment through the rationalization method of management and maintenance cost.

• 한국컴퓨터정보학회논문지
• /
• 제14권7호
• /
• pp.1-8
• /
• 2009

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구하였다. 따라서 최적 소프트웨어 방출 정책은 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화 시키는 정책을 수용해야 한다. 본 논문에서는 로그포아송 실행시간모형에 대하여 베이지안 모수 추정법(마코브체인 몬테칼로(MCMC) 기법 중에 하나인 깁스 샘플링과 메트로폴리스 알고리즘을 이용한 근사기법)이 사용되었다. 본 논문의 수치적인 예에서는 Musa의 T1 자료를 적용하여 최우수추정법과 베이지안 모수 추정과의 관계를 빅교하고 또한 최적 방출시기를 추정하였다.

• 국제학술발표논문집
• /
• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
• /
• pp.534-541
• /
• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.

• 디지털융복합연구
• /
• 제12권5호
• /
• pp.139-148
• /
• 2014

최근에는 모수(Parametric) 추정방법을 적용한 전산모델들이 개발되어 비용분석을 보다 효율적으로 예측할 수 있는 용도로 사용되고 있는 추세이다. 본 연구에서는 유도무기체계 분야 중 유도조종장치에 대한 데이터 경험치를 활용하여 공학적 추정 방법과 상용전산모델(Price H, HL, M, S)의 비용분석을 수행하고, 그 결과를 분석하여 차이점과 원인을 파악하였다. 전산모델의 수치적 데이터로 살펴 본 바에 따르면 유사장비 데이터베이스와의 비교 값을 근거로 하여 보정된 결과 값을 도출한 후, 공학적 추정방법으로 산정된 금액과 비교결과 근사한 수치를 보여 보정작업을 통한 데이터의 신뢰도가 향상됨을 알 수 있었다. 본 연구에서 개발비 추정 시, 많은 부분을 불확실한 요소에서 추정하였으나, 객관성을 확보할 수 있는 전산모델을 선택하여 사례를 연구함으로서 신뢰성을 높일 수 있었다. 이는 기존의 축적된 개발비 데이터에 근거하여 변수를 중심으로 한 추정방법을 기초로 합리적인 추정방법으로도 활용할 수 있음을 비용분석의 전산모델 보정(Calibration)을 통하여 밝혀냄으로써 보다 효율적인 비용 예측 기능에 일조할 것으로 사료된다.

• 한국군사과학기술학회지
• /
• 제24권1호
• /
• pp.133-143
• /
• 2021

In government procurement programs, cost estimation and analysis support funding decisions and are the basis for other major decisions, too. Such estimating and analyzing the cost of the weapon systems are crucial in execution of the defense budget. However, existing cost estimations and analyses have focused on domestic R&D projects, thus those are not valid in application to foreign weapon acquisitions. This study aims at foreign weapon systems that are acquired from Direct Commercial Sales. Because the data for price estimation of a foreign weapon is usually not available, we suggest a price estimation model based on performance factors of the weapon. In this study, the proper price of the weapon system is estimated using the parametric cost estimating model. Using the data of helicopter-launched anti-tank guided missiles worldwide, we analyze the effect of each performance factor on the weapon system price by regression analysis, and use step-wise and ridge regression analysis to remove multi-collinearity. This study hopefully contributes to more reasonable decision making on proper price of weapons.

• 한국정밀공학회지
• /
• 제21권9호
• /
• pp.85-94
• /
• 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.