The modelling of plasma etching processes using neural network and statistical techniques

Industrial plasma etcher operation in IC manufacture is often carried out through process recipes, with little or no adjustment based on feedback of important process outputs. The recipes created are not transferable between different etch chemistries or from reactor to reactor and the etch profiles resulting from a given recipe may vary with time as conditions within the reactor change. Two major difficulties with implementing closed-loop control are the need for in situ measurements of important process variables and nonlinear modelling of the process responses to the coupled control parameters. This paper concerns the use of chromatic monitoring as a process feedback measurement and compares two methodologies for the reactive ion etching (RIE) process modelling.