Aircraft design and development projects involve high levels of uncertainty due to their complex structure, making effective project scheduling critically important. This study addresses the limitations of deterministic scheduling approaches in managing uncertain activity durations within projects conducted in collaboration with Turkish Aerospace Industries. The main problem lies in the inability of traditional methods to adequately capture uncertainties arising from design changes, certification processes, and supply chain disruptions. To overcome this issue, an integrated methodology based on Critical Path Method (CPM), PERT, and Monte Carlo Simulation is proposed and implemented. Initially, CPM established a baseline schedule with an estimated completion time of 2955 days. To incorporate uncertainty, PERT and a 10,000-iteration Monte Carlo Simulation were executed. Results demonstrated that the deterministic CPM approach provided a highly optimistic estimate with a mere 1.26% probability of realization. In contrast, PERT calculated the expected duration as 3071 days, while the Monte Carlo simulation revealed a more realistic average completion time of 3143 days under worst-case scenario distributions. The findings suggest that incorporating stochastic uncertainty into project planning significantly improves decision-making and enhances the accuracy of schedule predictions. This study contributes to the literature by proposing and numerically validating an integrated framework for analyzing uncertainty in aircraft development projects, providing a foundation for more robust and risk-aware planning practices in the defense industry.

Keywords

Project Scheduling, Risk Analysis, CPM, PERT, Monte Carlo Simulation.