A real-time scheduling algorithm is proposed, that is, to first make a fuzzy classification for the operations of jobs in real-time and then, according to their fuzzy sort, to schedule them with the heuristic. The heuristic is obtained by training a neural network offline with the genetic algorithm. Based on these ideas a real-time scheduler is built with neuro-fuzzy network (NFN). Finally the simulation for the real-time scheduling and the rescheduling are made. The results show that the real-time scheduling algorithm is effective and highly efficient compared to the first in and first out (FIFO) and the Lagrangian relaxation (LR) method.

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Recent research in fixture computer -aided design systems generally emphasizes the automation of the fixture design process , but a complete system is not yet available. Some theoretical problems for fixture intelligent computer aided design (FICAD) are discussed in this paper. The focus of the contribution is the system structure and modeling method. The system structure mainly includes production FICAD , variable FICAD and design bases. The modeling method adopts parametric feature modeling. Based on parametric feature modeling , the feature structure and content are discussed and a feature base is set up.