This report investigates the effectiveness of Simple Temporal Networks with Uncer- tainty (STNUs) for solving the Stochastic Flexible Job-Shop Scheduling Problem with Sequence-Dependent Setup Times (SFJSP-SDST), comparing it against proactive and reactive Constraint Programming (CP) approaches. Using a benchmark dataset with varying noise levels, the study evaluates solution quality, feasibility, and computational cost. Results show that the reactive method achieves the lowest makespan due to its dy- namic rescheduling capability but incurs high online computation time. The proactive method offers fast execution, while the STNU-based approach provides a dynamically controllable schedule, albeit with conservative makespans.