Fault detection and isolation for plasma etching using model-based approach

Abstract

A fault detection and isolation system using model-based approach for the chamber pressure of plasma etching is developed. The dynamics of chamber pressure is modeled as a linear multiple-input-single-output closed-loop system and the model parameters are extracted by the system identification technique. The obtained parameters are then converted to physically meaningful features for detecting and isolating faults. The fuzzy inference and Dempster-Shafer evidence combining techniques are employed to detect and isolate fault from the features. The system has been evaluated by the measured data that are collected via SECS-II from the employed Lam-490 plasma etcher for processing practical products. The test results are satisfactory for a large amount of practical data and extensive computer simulations.