Data-based scheduling framework and adaptive dispatching rule of complex manufacturing systems

Based on the analysis of the differences and relations between traditional and data-based scheduling methods for complex manufacturing systems, a data-based scheduling framework was proposed and discussed for its implementation into a semiconductor manufacturing system. The state-of-the-art research on the key technologies of data-based scheduling was then introduced together with their development trends. By taking a real wafer fabrication facility (fab) as an example, an adaptive dispatching rule (ADR) was developed. Firstly, a simulation system for the fab was developed, and study samples were generated by simulation. Then, the relations between the parameters of ADR and real-time running state of the fab were obtained by learning with an integration of a binary regression model, backward propagation neuro-network, and particle swarm optimization algorithm from these study samples to realize the adaptive regulations of these parameters of ADR. Finally, ADR was integrated with the simulation system. The simulation results showed that ADR had a positive effect on the operational performance of the fab. Its “move” performance was increased by 2.41 and 7.24 % for the cases of 70 % and 90 % workload, respectively.

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