Endpoint Detection in Low Open Area Ratio Plasma Etching Using Hybrid Method

摘要

In current semiconductor manufacturing, as the feature size of integrated circuit (IC) devices continuously shrinks, detecting endpoint in low open area plasma etch process is more difficult than before. For endpoint detection, various kinds of sensors are installed in many semiconductor manufacturing equipment, and sensor data sampled with predefined sampling rate. To solve this problem, a combination of Signal to Noise Ratio (SNR), Principal Component Analysis (PCA) and Expanded Hidden Markov model (eHMM) technique is applied to optical emission spectroscopy (OES) signals.