This paper studies the effects of uncertainties in operational factors on performance of a manufacturing system. A simulation model of a hypothetical manufacturing system with multi-stage subassembly is developed and used to study such effects. The study uses simulation as long run planning tools for improving manufacturing performance and compares MRP-push systems versus Kanban-pull systems. A simulation language for discrete-event simulation, SIGMA, is used to model for pull, push systems.  An iterative heuristic algorithm is employed to determine initial model parameters:  the number of Kanban for pull systems, and safety stock levels for push systems. Simulation experiments are conducted in an environment involving changes in two operational factors:  demand and processing time. The experimental results indicate that the pull system outperforms the push system in terms of lead time and work in process (WIP) inventory in such environment.