Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk

Area of Science:

• Construction Management
• Risk Analysis
• Project Management

Background:

• Construction projects frequently face risks impacting timely and budget-conscious completion.
• Project success hinges on effective risk control and understanding risk interactions.
• Existing models often neglect the aggregated impact and amplification of interacting risks.

Purpose of the Study:

• To develop a novel structure for assessing the aggregated impact of construction project risks on completion time.
• To address the limitations of current models in estimating the combined and intensifying effects of risks.
• To provide a validated framework for proactive risk management in construction.

Main Methods:

• Integration of Monte Carlo simulation and Bayesian network methodologies.
• Development of a risk assessment structure accounting for inter-risk dependencies.
• Application and validation of the proposed model through an industrial case study.

Main Results:

• The developed structure provides an indicator for estimating the aggregated impact of risks, considering their interactions.
• The case study validated the model's functionality and demonstrated its implementation procedure.
• The study highlights the importance of assessing intensified risk impacts in construction projects.

Conclusions:

• The proposed structure enhances the assessment of aggregated risk impacts on construction project timelines.
• Effective management of interacting risks is crucial for improving project success rates.
• The integrated simulation and network approach offers a robust tool for construction risk management.