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Progress management is an important scheme of construction management. In practical affairs, many unknown factors may lead to potential project delays and make the schedule risky. To address this issue, this paper proposes a data-driven construction progress evaluation method that employs a probabilistic reliability analysis with BIM to effectively quantify the risk of schedule delay. By identifying critical tasks and probable failure conditions in uncertain environments, this method enables project managers to take proactive measures to keep their projects on schedule. Through our case study, we have demonstrated that the proposed method is highly effective in dynamically evaluating the project progress with both accuracy and efficiency. Besides, this system offers a more efficient way for managers to gather information, evaluate progress, and identify critical tasks, and provides project managers with a data-driven understanding of the risks and uncertainties related to project schedules, enabling them to take proactive measures to minimize the potential delays and ensure successful project delivery.
Zhang et al. (Fri,) studied this question.