Abstract
This research proposes a dynamic task reallocation method for cellular manufacturing systems. When unforeseen changes, such as delays of assembly processes, occur in the manufacturing systems, the predetermined initial task allocation is dynamically modified, in order to minimize the total tardiness of products. All the tasks are reallocated to the individual workers real-timely by using genetic algorithm, and the execution sequences of the reallocated tasks are determined by using a heuristic rule, called as EDD. A learning curve effect is considered in this research in generation of a suitable production schedule. A prototype of reallocation supporting system is developed based on the proposed method, and the effectiveness of the proposed method is verified through some computational experiments.
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