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Application of Weibull analysis to evaluate and forecast schedule performance in repetitive projects

Baqerin, M. H ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1061/(ASCE)CO.1943-7862.0001040
  3. Publisher: American Society of Civil Engineers (ASCE)
  4. Abstract:
  5. Construction managers regularly monitor projects to ensure that the project performance is under control. The earned value method (EVM) is a widely used tool to forecast project cost and time at completion. However, the effectiveness of the EVM in forecasting schedule performance has been questioned particularly because of its inability to address the associated uncertainties and poor performance in predicting project duration. The objective of this study is to present an activity-based model to conduct a probabilistic assessment and estimation of schedule performance in repetitive construction projects. This model, called the Weibull evaluation and forecasting model (WEFM), emphasizes the recurring nature of major activities in repetitive projects to evaluate and forecast schedule performance. WEFM estimates activity completion time and its upper and lower bounds of possibility and presents these estimates in the form of prediction graphs. Moreover, it provides reliability graphs that demonstrate the probability of achieving a target completion time. The major contribution of this study is to utilize capabilities of the Weibull distribution in probabilistic evaluation and forecasting of schedule performance in repetitive projects. A numerical example, which demonstrates application of WEFM on four separate housing projects, underscores its adaptive nature and its advantages over the existing methods
  6. Keywords:
  7. Earned value method ; Budget control ; Forecasting ; Numerical methods ; Probability distributions ; Value engineering ; Weibull distribution ; Activity based modeling ; Earned value ; Probabilistic assessments ; Probabilistic evaluation ; Quantitative method ; Repetitive projects ; Upper and lower bounds ; Weibull analysis ; Project management
  8. Source: Journal of Construction Engineering and Management ; Volume 142, Issue 2 , 2016 ; 07339364 (ISSN)
  9. URL: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0001040