An Operation-Group Based Soft Scheduling Approach for Uncertain Semiconductor Wafer Fabrication System

This paper tackles a large-scale and uncertain scheduling problem of semiconductor wafer fabrication system. Two kinds of uncertainties are considered here, including the machine breakdowns and the fluctuations of processing times. Instead of using the traditional rigid schedule, we propose a novel...

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Veröffentlicht in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2018-08, Vol.48 (8), p.1332-1347
Hauptverfasser: Zhong, Huaxing, Liu, Min, Hao, Jinghua, Jiang, Shenglong
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper tackles a large-scale and uncertain scheduling problem of semiconductor wafer fabrication system. Two kinds of uncertainties are considered here, including the machine breakdowns and the fluctuations of processing times. Instead of using the traditional rigid schedule, we propose a novel concept of operation-group-based soft schedule which is used as the new decision variable of the studied problem. The inherent idea of this concept is to make some critical scheduling decisions at the beginning of the scheduling horizon, and allow the remaining decisions to be made during the execution of the initial soft schedule. Furthermore, an operation-group-based soft scheduling approach (OGSSA) is proposed to deal with the uncertainties, which contains an offline optimization layer and an online dispatching layer. In the offline optimization layer, a prediction-based decomposition scheduling method is proposed to generate a soft schedule, and a global scheduling objective prediction model is constructed to evaluate the soft schedule. Then, the initial soft schedule is released to the online dispatching layer, and an online heuristic rule is designed to decide in real time, which operations and when to process. The computational results on the practical production data demonstrate the effectiveness of OGSSA under uncertain production environments.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2017.2669212