Advanced Process Control Using Virtual Metrology to Cope With Etcher Condition Change

Abstract

In the semiconductor, an advanced process control (APC) system using virtual metrology (VM) for plasma etching is required to achieve further device miniaturization. VM is a method to predict process outputs such as the critical dimension (CD) from equipment data indicating the etcher condition. The prediction model for VM is called VM model. Although a highly accurate VM model is necessary to realize the APC system, the prediction accuracy can be worse when the correlations between the CD and equipment data change because of changes in etcher conditions. To solve the problem, we propose a multiple VM model selection APC system. The proposed APC builds: 1) multiple local VM models that are built using a series of lot data to cope with the correlation change and 2) a global VM model that is built using all of the lot data to improve the robustness of CD prediction. When APC is applied, the proposed APC selects the optimal VM model among the multiple VM models that have been built. This paper shows that the proposed system contributes to improving prediction accuracy even though the correlation change occurs by simulation based on actual etcher experimental data.