Abstract

Traditional semiconductor manufacturing relies on a fixed process-recipe combined with a classical statistical process control that is used to monitor the production process. Leading-edge manufacturing processes require higher levels of precision and accuracy, which necessitate the use of tighter process control. Advanced Process Control (APC) is becoming a critical component to improve performance, yield, throughput, and flexibility of the manufacturing process using run-to-run, wafer-to-wafer, within wafer and real-time process control. The complexity of device manufacturing process as well as the strong coupling effect of several input parameters on the final process outputs prohibit the use of a classical single variable feedback control method. Therefore, multivariate, model-based APC system is developed in conjunction with feed-forward and feedback mechanisms to automatically determine the optimal recipe for each wafer based on both incoming wafer and tool state properties. The APC system uses wafer metrology, process models and sophisticated control algorithms to provide dynamic fine-tuning of intermediate process targets that enhance final device targets. The design of the APC system enables scalable control solutions across a single chamber, a process tool, multi-tools, a process module and multi-process modules using similar building blocks, concepts and algorithms.

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