Estimation of etch rate and uniformity with plasma impedance monitoring. Daniel Tsunami

Transcription

1 Estimation of etch rate and uniformity with plasma impedance monitoring Daniel Tsunami IC Design and Test Laboratory Electrical & Computer Engineering Portland State University 1

2 Introduction Plasma Processing in semiconductor manufacturing Plasma Impedance Monitoring (PIM) Advanced Process Control (APC) 2

3 Introduction Plasma Impedance Data Upper and lower frequency ~ 2 MHz and 27 MHz Lower voltage, current and phase 5 harmonics Upper voltage, current and phase 3 harmonics 4 tools, 2-4 chambers per tool Up to 12 recipes for each tool/chamber combination Collected ~ 150k files full data set probably 250k files Only a few will be used for regression 3

4 Background Plasma Impedance Data 4

5 Introduction Etch Rate Data Etch rate measured no less frequently than every seven days using test wafers and procedures for each tool/chamber. Etch rate measured at 17 sites on test wafer Range and mean are used as parameters plotted on statistical process control (SPC) charts 5

6 ER measurements : wafermaps 6

7 ER measurements : wafermaps 7

8 ER measurements : wafermaps 8

9 Etch Rate Variability Etch Rate Data 9

10 Etch Rate Distributions Estimated pdf 4.5 x pm1 pm2 pm3 pm Etch Rate m/min 10

11 Big Idea Plasma impedance measurements contain information about the etch rate of the plasma tool. Regression analysis is a standard tool for discovering relationships in data. Create regression model to characterize relationship between PIM signals and etch rate measurements 11

12 Idea - Details Model Selection/Construction Stepwise regression Model Validation R 2 PRESS Statistics 12

13 Initial Literature Search Garvin and Grizzle : Demonstration of broadband radio frequency sensing: Empirical polysilicon etch rate estimation in a Lam 9400 etch tool Estimate etch rate using regression model and broadband plasma impedance measurements specifically the reflection coefficient phase and magnitude at several different frequencies. Only 20 experiments Good results R 2 = and methodology Active as opposed to passive plasma impedance sensing No model validation to prove that results are not due to overfitting 13

14 Variable Selection 14

15 Variable Selection 1 R a 2 Adjusted R PRESS Data interval from etch rate measurement 15

16 ER Predictions 16

17 ER Estimates 17

18 SPC Chart Mean Etch Rate m/min Etch Rate Range m/min Time (days) 18

19 Initial Yield Correlation pm1 lig12low E(yld ER) Yield Etch Rate m/min 19

20 Yield Nonparametric Regression PM1 LIG12LOW 0.9 Data Points Kernel Regression 95% Confidence Intervals Yield Estimated Etch Rate 20

21 DD Nonparametric Regression PM1 LIG12LOW Data Points Kernel Regression 95% Confidence Intervals 0.35 Defect Density Estimated Etch Rate 21

22 APC Controller Etch Tool Production Data PIM Test Wafer Data Etch Time Test Wafer Etch Rate Measurements Measured Etch Rates Predictors APC Controller Estimated Etch Rates Adaptive Linear Model 22

23 PM1 Predictions Measurements Predictions Etch rate mean Etch rate range Days since Jan

24 PM2 Predictions Etch rate mean Measurements Predictions Etch rate range Days since Jan

25 PM4 Predictions Measurements Predictions Etch rate mean Etch rate range Days since Jan