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Project Schedule Risk Assessment Based on Bayesian Nets

베이지안넷 기반의 프로젝트 일정리스크 평가

  • Sung, Hongsuk (School of Industrial Engineering and Naval Architecture, Changwon National University) ;
  • Park, Chulsoon (School of Industrial Engineering and Naval Architecture, Changwon National University)
  • 성홍석 (창원대학교 산업조선해양공학부) ;
  • 박철순 (창원대학교 산업조선해양공학부)
  • Received : 2015.11.18
  • Accepted : 2016.01.14
  • Published : 2016.03.31

Abstract

The project schedule risk in the engineering and facility construction industry is increasingly considered as important management factor because the risks in terms of schedule or deadline may significantly affect the project cost. Especially, the project-based operating companies attempt to find the best estimate of the project completion time for use at their proposals, and therefore, usually have much interest in accurate estimation of the duration of the projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, and then performing risk assessment with simulation such as Monte-Carlo simulation method. However, since these approaches require the accumulated executional data, which are not usually available in project-based operating company, and, further, they cannot reflect various schedule constraints, which usually are met during the project execution, the project managers have difficulty in preparing for the project risks in advance of their occurrence in the project execution. As these constraints may affect time and cost which role as the crucial evaluation factors to the quality of the project result, they must be identified and described in advance of their occurrence in the project management. This paper proposes a Bayesian Net based methodology for estimating project schedule risk by identifying and enforcing the project risks and its response plan which may occur in storage tank engineering and construction project environment. First, we translated the schedule network with the project risks and its response plan into Bayesian Net. Second, we analyzed the integrated Bayesian Net and suggested an estimate of project schedule risk with simulation approach. Finally, we applied our approach to a storage tank construction project to validate its feasibility.

Keywords

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