Virtual Metrology for Prediction of Etch Depth in a Trench Etch Process

In semiconductor manufacturing, advanced process control systems have become essential for cost effective manufacturing at high quality. Algorithms for new control methods such as virtual metrology where post process quality parameters are predicted from process and wafer state information need to be developed and implemented for critical process steps. The objectives of virtual metrology application are to support or replace stand-alone and in-line metrology operations, to support fault detection and classification, run-to-run control, and other new control entities such as predictive maintenance. As virtual metrology is typically based on statistical learning methods, a large variety of potential algorithms are available. The challenge of virtual metrology application is the capability to obtain precise predictions even in complex semiconductor manufacturing processes. In this paper, the approach and results towards the development of a virtual metrology algorithm for the prediction of trench depth after a complex dry-etch process are presented.