Semiconductor production line model building, optimizing and scheduling method based on petri net and immune arithmetic

Abstract

The invention provides an optimized scheduling method of a semiconductor production line based on a Petri net and immune algorithm. The method utilizes the Petri net for carrying out modeling to the semiconductor production line, comprising a path scheduling model, an equipment group scheduling model and an equipment scheduling model; and the immune algorithm is embedded in the Petri net model as the scheduling strategy. By the Petri net model, all possible acts of the semiconductor manufacturing system can be described, such as work-piece processing, equipment failure, batch processing, defected wafer rework and the like. The chromosome of the immune algorithm can be directly structured out of search nodes of the Petri net model, and each gene of each chromosome records the scheduling strategy of each equipment group. A better chromosome is obtained by the simulation of the Petri net model, and therefore a sub-optimal scheduling strategy is generated. The optimized scheduling method has the advantages of reducing the complexity of the model and improving the reusability of the model and the scheduling algorithm.

Description

technical field [0001] The invention relates to a semiconductor production line modeling and optimization method based on Petri nets and immune algorithms, in particular to an advanced production management method that intelligently simulates life science immune principles and genetics in production management in the field of microelectronics manufacturing. Specifically, the modeling and scheduling method involved in the present invention uses Petri nets as a modeling tool, uses immune algorithms as a scheduling method, and comprehensively considers multiple indicators such as total movement, total output, on-time delivery rate, and average production cycle. The optimization of the daily work order is determined through simulation, and the actual operation of the production line is guided accordingly. Background technique [0002] Semiconductor devices are very expensive to manufacture. Semiconductor device manufacturing is risky due to the large investment costs required. ...

AI Technical Summary

Problems solved by technology

Use the queuing theory to calculate the waiting time of workpieces. However, due to the different types of workpieces and processing steps, the processing time of workpieces and the setting time of equipment are also different, and the calculation results will have large errors, which cannot be purely based on the queued workpieces. Timed processing is not practical for a production line with multiple product types in the semiconductor industry

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