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플랜트 건설 리스크 분석 및 리스크 정량화 모델 개발에 관한 연구

Risk Factors Analysis and Quantitative Risk Assessment Model for Plant Construction Project

  • Ahn, Sung-Jin (Department of Architectural Engineering, Mokpo National University) ;
  • Kim, Tae-Hui (Department of Architectural Engineering, Mokpo National University) ;
  • Nam, Kyung-Yong (UTOP E&A) ;
  • Kim, Ji-Myong (Department of Architectural Engineering, Mokpo National University)
  • 투고 : 2018.10.10
  • 심사 : 2019.01.02
  • 발행 : 2019.02.20

초록

플랜트 건설 프로젝트에 대한 수요가 증가하고 복잡해짐에 따라 예기치 못한 위험 요소가 증가하고 있다. 이에 플랜트 건설 프로젝트에 대한 중점 리스크 요인을 바탕으로 정량적 리스크 분석 및 평가 모델 개발이 요구되고 있다. 본 연구는 보험 회사에서 수집 한 보험금 지급 데이터를 사용하여 플랜트 건설 프로젝트의 실제 재정적 손실을 위험 평가 모델의 종속 변수로 반영하였으며 문헌 검토 및 데이터 분석을 바탕으로, 지형, 시운전, 공정률, 총 공시비 및 총 공사기간을 독립변수로 채택하였다. 제안된 손실율 모델은 플랜트 프로젝트 리스크 분석과 시공/시운전 단계의 리스크 분석가이드라인으로 활용될 수 있다.

Due to the increasing demand for and complexity of plant construction projects, unpredictable risk factors are on the consequent increase. For that reason, the quantitative risk analysis is being called for, in order for the development of a risk assessment model using risk indicators for the plant construction projects. This study used the claim payout data collected at a global insurance company to reflect the actual financial losses in plant construction projects as dependent variables in the risk assessment model. In terms of independent variables, the geographic information, i. e., landform, and the construction information including test-run, schedule rate, total cost and duration are adopted. In addition, this study suggests that the regression model containing such independent variables that are statistically significant can be applied to as a foundational guideline for the plant construction project risk analysis during the phase of construction and commissioning.

키워드

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Figure 1. Research procedure

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Figure 2. Histogram and normal Q-Q plot for dependent value

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Figure 3. Histogram and normal Q-Q plot for transformed dependent value

Table 1. Study method and applicable phase of previous studies

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Table 2. Causes of plant construction project losses

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Table 3. Total/average claim payouts by loss causes

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Table 4. Claim payout and frequency by construction phase

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Table 5. Claim payout and frequency by schedule rate

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Table 6. Claim payout and frequency by landform

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Table 7. Claim payout and frequency by total cost

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Table 8. Claim payout and frequency by total duration

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Table 9. Normality test of transformed dependent value

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Table 10. Normality test of dependent value

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Table 11. Categories of independent values

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Table 12. Descriptive statistics

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Table 13. ANOVA and adjusted R square

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Table 14. Coefficients

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