Dynamic scheduling in cellular manufacturing systems: A framework for networked decision making

Abstract This paper describes a dynamic scheduling method for cellular manufacturing systems. Essentially an artificial intelligence based approach for the networking environment, the method is adaptive to the changes in the manufacturing environment and can take into account such information as loading factor, unexpected breakdowns, and new job arrivals. The major features of the method are a distributed task assignment mechanism executed through the communication network for intercell scheduling and a knowledge based system for cell level scheduling. A main advantage of such a method is that the scheduling on both levels can be dynamically executed in real time.

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