Towards a Complete Plasma Diagnostic System

1. Towards a Complete Plasma Diagnostic System SFR Workshop May 24, 2001 Dong Wu Zhao, Costas Spanos Berkeley, CA 2001 GOAL: Install automated OES and Z-scan sensor on LAM 9400 and build large statistical database of process fingerprinting data by 9/30/2001.

2. Motivation • Plasma signals are difficult to characterize. • Drifts are subject to preventive maintenance, machine aging, chamber memory effects, etc. • One needs to describe signals both qualitatively and qualitatively by syntactic analysis. • One needs to extract meaningful features effectively from a large amount of data, for endpoint detection, wafer state modeling, etc. • Useful diagnostic signals come from a variety of sensors (OES, RF, etc), and must be combined for best diagnostic results.

3. Available Data from LAM 9400 • We have three distyinct sources of signals: • Optical Emission Spectroscopy (200 – 1100 nm). • Z-scan signals of current voltage, impedance, at five harmonics of 13.56 Mhz. (sensor and software donated by Advanced Energy) • Regular machine signals & settings, power, pressure, temperature, gas flow rate. • An automated data management system monitors all three data sources and builds a large data base over time. machine settings machine signals Z OES

4. Hardware Setup in the Berkeley Microlab Workstation SECII Lam 9400 OES sensor Z-scan sensor

5. OES CF2 line for Endpoint Detection This is a Cl2 poly etch step. CF2 lines 321nm, 275nm show transition down to 1% area exposure. Notice that CF4 etches oxide.

6. Wafer State Modeling of Uniformity & Etch Rate: combined sensor signals give the best results

7. Database Exploring Software Features • We are developing a software tool to visually explore the nature of data. • Select data based on date/time, recipe, or machine settings. • Generate machine settings and signal value distributions. • Compute signal correlation. • Generate within-wafer plot, I.e., signal vs. time. • Generate cross-wafer plot, I.e., signal vs. signal.

8. Assign codes to OES peaks, Z-scan harmonics, and machine signals: Large increase: 2 Moderate increase: 1 Unchanged: 0 Moderate decrease: -1 Large decrease: -2 Selectively monitor numerical values of certain signals. For example, if pressure consistently drifts away from the setting point, we should fire an alarm. Syntactic Analysis Put the code in a stream: {OES peak codes}{Z-scan harmonic codes}{machine signal codes}, e.g., {0 0 0 1 0 2 0…. 0 –1}{0 0 –2 –1 … 0 1 0}{0 2 1 0 … 0 –1 0}

9. 2002 and 2003 Goals Deploy automated fault detection system using high sampling rate RF fingerprinting. Study automated generation of syntactic analysis rules for RF fingerprinting, by 9/30/2002. Study systems of real-time instability detection and plasma stabilization control; perform field studies of automated OES classification for fault diagnosis, by 9/30/2003.