The study presents two simulation models for generic manufacturing systems operated under MRP-push policy and Kanban-pull policy. The models are designed as long run planning tools for improving manufacturing performance. A simulation language for discrete-event simulation based on event graph is used to construct the models for pull, push systems [5]. The models in this paper are totally data driven. Input data includes machines, products, processes, bill of materials, and demand data. An iterative heuristic algorithm is employed to determine the initial model parameters: the number of Kanban for pull systems, and safety stock levels for push systems. Simulation experiments are carried out to demonstrate the effectiveness of the heuristic and the simulation models. The experiments are conducted in an environment involving changes in two operational factors: demand and processing time. The experimental results indicate that for the same throughput, the pull system outperforms the push system in terms of lead time and work in process (WIP) inventory in such environment
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