AVS 58th Annual International Symposium and Exhibition
    Plasma Science and Technology Division Thursday Sessions
       Session PS-ThA

Paper PS-ThA7
Experimental Implementation of Robust Multivariable Real-time Feedback Control Design for RIE Plasma Processing System

Thursday, November 3, 2011, 4:00 pm, Room 201

Session: Plasma Diagnostics, Sensors and Control II
Presenter: Yang Zhang, NCPST Dublin City University, Ireland
Authors: Y. Zhang, NCPST Dublin City University, Ireland
B.J. Keville, NCPST Dublin City University, Ireland
A. Holohan, NCPST Dublin City University, Ireland
S. Daniels, NCPST Dublin City University, Ireland
Correspondent: Click to Email

A robust multivariable real-time feedback control strategy for improving output characteristics of a reactive ion etching (RIE) plasma system is presented. Semiconductor fabrication is one of the major applications of low-pressure plasmas. During the course of manufacturing of semiconductor devices, it is often necessary to etch dielectric and/or metal layers to provide features in the layers for subsequent semiconductor processing steps. Reducing process variation is becoming ever more critical and challenging due to shrinking IC device feature dimensions and an increase in wafer size. Developments in process control are struggling to keep pace with these more stringent demands due to the fact that most semiconductor manufacturing tools are run in open loop mode. In this case, key plasma parameters such as ion flux and radical densities at the substrate surface are sensitive to drift in tool subsystems, changes in wall condition and wafer loading, for example. Disturbances to key plasma parameters may affect process metrics such as etch depth and anisotropy and result in a significant degradation in device yield and performance.

In this paper, we report the development of a robust multivariable, real-time feedback controller for the improvement of process repeatability and reproducibility of a RIE tool. Key plasma variables are sensed and their responses to the process inputs are identified experimentally. A MIMO controller then is developed and implemented to control these variables. H-infinity control theory and software are used for a systematic tuning procedure. This controller can effectively reduce cross-coupling effects and cope with parameter uncertainties and external disturbances in real-time in order to achieve robustness and optimal performance of the multivariable system.