Proceedings Article10.1109/COASE.2013.6654027
Attribute selection algorithm of data-based scheduling strategy for semiconductor manufacturing
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TL;DR: The goal is to investigate which attributes play the key roles in the manufacturing scheduling according to a specific performance criterion and a genetic algorithm-based selection approach for feature production attributes is proposed.
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Abstract: In today's digital and information-based manufacturing environment, data are basic elements for almost every production control and management activity. This paper focuses on production data processing based on attribute analysis. There are thousands of attributes in semiconductor manufacturing. However, some of them are irrelevant and/or redundant to some optimal production control and management issues. It is hard to decide which attributes should be considered as input references. Rational attribute selection may lead to an accurate scheduling strategy and finally exerts a positive impact on the performance of the whole production line. This is the motivation of this work. Its goal is to investigate which attributes play the key roles in the manufacturing scheduling according to a specific performance criterion. A genetic algorithm-based selection approach for feature production attributes is proposed. Its prediction accuracy is verified via a practical wafer production line.
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Citations
Industrial big-data-driven and CPS-based adaptive production scheduling for smart manufacturing
TL;DR: The proposed adaptive scheduling solution is applied and verified on an experimental semiconductor manufacturing system and the results demonstrate that the proposed method outperforms the dynamic scheduling method in terms of multiple objectives under different disturbance levels.
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Dynamic Scheduling of a Semiconductor Production Line Based on a Composite Rule Set
TL;DR: In this paper, a composite dispatching rule based on heuristic rules that comprehensively consider various factors in a semiconductor production line is developed, and a model of the response surface is developed to find the optimized parameters of a composite rule for various production states.
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Dynamic Scheduling for Semiconductor Production Line Based on Composite Rule
Zhihong Min,Wu Wenjing,Yumin Ma(,Fei Qiao +3 more
- 01 Jan 2016
TL;DR: This paper develops a composite dispatching rule based on heuristic rules that comprehensively consider various factors in a semiconductor production line to optimize production performance according to real-time production line state.
Learning-based dynamic scheduling of semiconductor manufacturing system
Yumin Ma,Fei Qiao,Jianfeng Lu +2 more
- 01 Aug 2016
TL;DR: The result indicates that the learning-based scheduling method is superior to single scheduling rules and it also meets the requirements of real-time manufacturing scheduling.
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