Virtual Metrology Modeling for Plasma Etch Operations

The objective of this paper is to present the utilization of information produced during plasma etching for the prediction of etch bias. A plasma etching process typically relies on the concentration of electrically activated chemical species in a reaction chambers over time, depending on chamber pressure, gas flow rate, power level, and other chamber and wafer properties. Plasma properties, as well as equipment factors, are complex and vary over time. In this paper, we will use various statistical techniques to address challenges due to the nature of plasma data: high dimensionality, colinearity, parameter interactions and nonlinearities, variation of data structure due to equipment condition changing over time, etc. The emphasis will be data integrity, variable selection, accommodation for process dynamics, and model-building methods. Different techniques will be evaluated with an industrial dataset.