| Citation: |
Chen Shan, Pan Tianhong, Li Zhengming, Jang Shi-Shang. Statistical key variable analysis and model-based control for improvement performance in a deep reactive ion etching process[J]. Journal of Semiconductors, 2012, 33(6): 066002. doi: 10.1088/1674-4926/33/6/066002
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Chen S, Pan T H, Li Z M, Jang S S. Statistical key variable analysis and model-based control for improvement performance in a deep reactive ion etching process[J]. J. Semicond., 2012, 33(6): 066002. doi: 10.1088/1674-4926/33/6/066002.
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Statistical key variable analysis and model-based control for improvement performance in a deep reactive ion etching process
DOI: 10.1088/1674-4926/33/6/066002
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Abstract
This paper proposes to develop a data-driven via's depth estimator of the deep reactive ion etching process based on statistical identification of key variables. Several feature extraction algorithms are presented to reduce the high-dimensional data and effectively undertake the subsequent virtual metrology (VM) model building process. With the available on-line VM model, the model-based controller is hence readily applicable to improve the quality of a via's depth. Real operational data taken from a industrial manufacturing process are used to verify the effectiveness of the proposed method. The results demonstrate that the proposed method can decrease the MSE from 2.2×10-2 to 9×10-4 and has great potential in improving the existing DRIE process. -
References
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