• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.707-716
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• 2009

The role of cost modeller is to facilitate the design process by systematic application of cost factors so as to maintain a sensible and economic relationship between cost, quantity, utility and appearance which thus helps in achieving the client's requirements within an agreed budget. There are a number of research on cost estimates in the early design stage based on the improvement of accuracy or impact factors. It is common knowledge that cost estimates are undertaken progressively throughout the design stage and make use of the information that is available at each phase, through the related research up to now. In addition, Cost estimates in the early design stage shall analyze the information under the various kinds of precondition before reaching the more developed design because a design can be modified and changed in all process depending on clients' requirements. Parametric cost estimating models have been adopted to support decision making in a changeable environment, in the early design stage. These models are using a similar instance or a pattern of historical case to be constituted in project information, geographic design features, relevant data to quantity or cost, etc. OLAP technique analyzes a subject data by multi-dimensional points of view; it supports query, analysis, comparison of required information by diverse queries. OLAP's data structure matches well with multiview-analysis framework. Accordingly, this study implements multi-dimensional information system for case based quantity data related to design information that is utilizing OLAP's technology, and then analyzes impact factors of quantity by the design criteria or parameter of the same meaning. On the basis of given factors examined above, this study will generate the rules on quantity measure and produce resemblance class using clustering of data mining. These sorts of knowledge-base consist of a set of classified data as group patterns, of which will be appropriate stand on the parametric cost estimating method.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.417-424
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• 2009

For a construction project to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need effective estimation strategies. Practically, parametric cost estimates are the most commonly used method in these initial phases, which utilizes historical cost data (Karshenas 1984, Kirkham 2007). Hence, compilation of historical data regarding appropriate cost variance governing parameters is a prime requirement. However, precedent practice of data mining (data preprocessing) for denoising internal errors or abnormal values is needed before compilation. As an effort to deal with this issue, this research proposed a statistical methodology for data preprocessing and verified that data preprocessing has a positive impact on the enhancement of estimate accuracy and stability. Moreover, Statistically Preprocessed data Based Parametric (SPBP) cost models are developed based on multiple regression equations and verified their effectiveness compared with conventional cost models.

• 한국국방경영분석학회지
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• 제27권1호
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• pp.10-27
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• 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.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.176-181
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• 2011

A role of cost modeler is that of facilitating design process by the systematic application of cost factors so as to maintain sensible and economic relationships between cost, quantity, utility and appearance. These relationships help to achieve the client's requirements within an agreed budget. The purpose of this study is to develop a parametric cost estimating model for the early design stage by using the multi-dimensional system of OLAP (On-line Analytical Processing) based on the case of quantity data related to architectural design features. The parametric cost estimating models have been adopted to support decision making in the early design stage. These models typically use a similar instance or a pattern of historical case. In order to effectively use this type of data model, it is required to set data classification and prediction methods. One of the methods is to find the similar class in line with attribute selection measure in the multi-dimensional data model. Therefore, this research is to analyze the relevance attribute influenced by architectural design features with the subject of case-based quantity data used for the parametric cost estimating model. The relevance attributes can be analyzed by Analytical Characterization. It helps determine what attributes to be included in the OLAP multi-dimension.

• 대한산업공학회지
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• 제1권2호
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• pp.27-38
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• 1975

This paper explores a quantitative decision-making system for planning production, inventories and work-force in a multi-item production system. The Multi-item Parametric Decision Rule (MPDR) model, which assumes the existence of two types of linear feed-back rules, one for work-force level and one for production rates, is basically an extension of the existing method of Parametric Production Planning (PPP) proposed by C.H. Jones. The MPDR model, however, explicitly considers the effect of manufacturing progress and other factors such as employee turn-over, difference in work-days between month etc., and it also provides decision rules for production rates of individual items. First, the cost relations of the production system are estimated in terms of mathematical functions, and then decision rules for work-force level and production rates of individual items are establised based upon the estimated objective cost function. Finally, a direct search technique is used to find a set of parameters which minimizes the total cost of the objective function over a specified planning horizon, given estimates of future demands and initial values of inventories and work-force level. As a case problem, a hypothetical decision rule is developed for a particular firm (truck assembly factory).

• 한국군사과학기술학회지
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• 제15권5호
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• pp.565-576
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• 2012

Cost estimates are necessary for government acquisition program to support decisions about funding, to develop annual budget requests and to validate resource requirements at key decision points. Many researches have been done about cost estimating technique recently. Parametric cost estimating models based on CERs(Cost Estimating Relationships) have been mainly used using regression method with historical data. However, there are many restrictions in developing Korean version CERs because the number of data points are too small. Specially, data collection and data management system are unstable in Korean defense environment, when developing CERs. In this research, we analyzed the historical data, and found some cost drivers in guided weapon system area. We developed the Acquisition Unit Cost CER using the regression to remove multicollinearity in the historical data. So we could overcome the restriction of the insufficient sample number. This research as a first attempt is meaningful in terms of obtaining our own Acquisition Unit Cost CER using historical cost and physical characteristic in Korean development environment.

• 산업경영시스템학회지
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• 제33권3호
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• pp.55-62
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• 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.

• 산업공학
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• 제25권3호
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• pp.347-356
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• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.305-307
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• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• 한국건설관리학회논문집
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• 제20권1호
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• pp.141-150
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• 2019

해외 플랜트 건설시장에서 국내기업의 기술적 위상은 크게 향상되었으나 기술적 측면에 비해 프로젝트 관리 측면의 역량은 미비한 수준으로 평가되고 있다. 프로젝트 관리 중 프로젝트 수행 초기인 기획단계에서의 사업관리 역량은 선진 건설 기업의 핵심 역량으로 볼 수 있으며, 그 중 초기 원가산정 기술은 국내 기업의 역량 향상이 시급하다. 본 연구에서는 플랜트 프로젝트 기획단계에서 진행되는 개산견적 방법론에 대해 조사 및 분석하고, 사례분석을 통해 개산견적 방법을 제시하였다. 기존의 개산견적 방법론 중 비용지수법과 변수견적법의 로직을 토대로 플랜트 프로젝트에 특화된 입출력 변수를 도출하여 개산견적 도구를 개발하였다. 제시된 방법론의 유효성은 사례 프로젝트의 개산견적 금액과 실적 프로젝트 금액 간의 정확도 비교를 통해 평가하였다. 개발된 플랜트 개산견적 방법론의 활용성 증대를 위해 실적 프로젝트의 체계적인 데이터화가 필수적이다. 향후 프로젝트 원가산정의 정확성을 높이는 것은 기업의 프로젝트 수주 및 수익확보와 직결되므로, 개발된 도구의 적극적 활용이 기대된다.