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Abstract
Wafer inspection plays a significant role in monitoring the quality of wafers production for continuous improvement. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a high priority to reduce production cost. Several sampling methods in the literature were proposed to achieve this goal. They utilised real sampling inspections as the representatives for the other related wafers to monitor the whole production process. Under the condition of stable manufacturing process, virtual metrology (VM) may be applied to monitor the quality of wafers, while real metrology is unavailable. Therefore, the sampling rate may further be reduced with a sampling decision scheme being designed according to reliable VM. Nevertheless, once a new production variation occurs between planned samplings and no real metrology is available during this period for updating the VM models, un-reliable VM predictions may be produced. The authors have developed the automatic virtual metrology (AVM) system for various VM applications. Therefore, this paper focuses on applying various indices of the AVM system to develop an intelligent sampling decision scheme for reducing sampling rate, while VM accuracy is still sustained.
Acknowledgements
The authors thank the United Microelectronics Corporation in Taiwan for providing the raw data used in the illustrative examples and the National Science Council of the Republic of China for financially supporting this research under contract Nos. NSC102-2622-E-006-022-CC2 and NSC102-2221-E-006-118-MY2. The authors also thank the Advanced Institute of Manufacturing with High-tech Innovations (AIM-HI), National Chung Cheng University, Taiwan for financially supporting this research.