Semiconductor enterprises should continue to provide more capacity to meet the demands of the highly competitive semiconductor markets. Photolithography is usually the bottleneck process with the most expensive equipment in a semiconductor wafer fabrication system. Usually, photolithography area controls the performance of whole semiconductor manufacturing system. To improve the performances of the photolithography area with dynamic dispatching combination rules, a dynamic scheduling method based on Kohonen neural network (KNN) was proposed in this paper. A dynamic scheduling framework is also proposed. The method has been integrated into the dynamic scheduling framework. A KNN-based sample learning algorithm for selecting best combination rules is presented. Finally, the results of simulation experiments indicate that the proposed method is effective and feasible in real-time scheduling of semiconductor fabrication system under both closed-loop release policy and open-loop release policy. Copyright © 2013 Springer Science+Business Media New York.
|Journal||Journal of Intelligent Manufacturing|
|Early online date||Apr 2013|
|Publication status||Published - Feb 2015|
CitationZhou, B.-H., Li, X., & Fung, R. Y. K. (2015). Dynamic scheduling of photolithography process based on Kohonen neural network. Journal of Intelligent Manufacturing, 26, 73-85. doi: 10.1007/s10845-013-0763-9
- Semiconductor wafer fabrication system
- Kohonen neural networks
- Dynamic scheduling