Probabilistic risk analysis for elevated metro rail construction using Monte Carlo simulations

Metro rail projects in rapidly urbanizing regions often face schedule delays and cost overruns due to uncertainty and complex risk interactions. This study presents a Monte Carlo simulation–based framework for probabilistic risk analysis in elevated metro rail construction by integrating deterministic scheduling in Primavera P6 with risk modelling in Risk Analyzer. The framework comprises baseline scheduling, uncertainty integration, risk modelling, mitigation planning, and sensitivity analysis. A baseline schedule of 711 days with an estimated cost of ₹2,598.8 million was developed, and 1,000 Monte Carlo simulations were conducted using three-point estimates for activity duration and cost. Seventeen project risks were identified and prioritised using a probability–impact approach. Activity uncertainties increased the mean project duration to 778 days (9.4%), with a maximum of 831 days, while the mean cost marginally increased to ₹2,601.7 million. Considering all risks, the mean duration increased to 842 days (18.4%), with a maximum of 1,008 days, and the mean cost rose to ₹2,621.7 million. A mitigation plan costing ₹3.32 million reduced mean and maximum durations by 26 and 76 days, respectively, yielding potential savings of up to ₹23.1 million. Sensitivity analysis identified critical activities requiring proactive management, demonstrating the framework’s effectiveness in improving schedule reliability and cost control.