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Abstract
A knowledge-based scheduler (KBS) for FMS which adopts the hierarchical approach and utilizes simulation techniques is developed. It is basically a rule-based system with a generic structure which allows tailoring to specific managerial and system needs. The KBS schedules the loading of parts in the system based on global knowledge and dispatches parts to workstations based on local knowledge. It generates realistic schedules by satisfying a set of user-defined top and local goals and constraints. It is built on top of KEE, a hybrid AI environment and its use is demonstrated in a flexible printed circuit board assembly system.