Application of SEERS to real time Plasma Monitoring in Production at different FABs

Transcription

1 AECAPC SYMPOSIUM 21, BANFF Application of SEERS to real time Plasma Monitoring in Production at different FABs Volker Tegeder

2 Sensor Evaluation Calculation of expected Economical Benefit Automatic link to logistical Data Partnership Sensor Supplier, Tool Supplier, Manufacturer Analyze Data and react on conspicuous Data Merge Sensor Data to FDC System Requirements for successful integration of sensors into manufacturing Lessons Learned

3 European SEA IST-Project: APC3 Poly Plasma PlasmaProcess ProcessControl Control Oxide Metal Dresden Dresden HERCULES/APC HERCULES/APC(Plasma-Parameter) (Plasma-Parameter) APC NET (Tool-Parameter) APC NET (Tool-Parameter) Test-Data Test-Data Wafer-Yield Data Database base Correlation between yield and plasma CoO, OEE Rousset Regensburg Start: February 1st, 2 End: October 31st, 21 Participants and Timeline Berlin

4 Calculation of expected Economical Benefit

5 Calculation of expected Economical Benefit Project Planning HW System Set Up Resources allocated to project => Calculation of Benefit first! Involvement of: Process Integration, Maintenance, IT, Product Characterization, Controlling, Process Dep. Impact of Benefit Estimation

6 Calculation of expected Economical Benefit Identify Improvement for Manufacturing List Preconditions and Requirements Correlate Improvement to Economical Benefit Generate Benefit Equations for Verification Collect Data for Calculation (pre/post) System Set Up to Receive the Benefit Calculation Steps

7 Automatic Link to logistical Data

8 Automatic Link to logistical Data Analysis correlate sensor data to in line data yield data tool data benefit calculation Adjustment of settings for sensor alarm (FDC) Logistical Data linked to Sensor Data

9 Partnership: Sensor Supplier, Tool Supplier, Manufacturer

10 Partnership: Sensor Supplier, Tool Supplier and Manufacturer New Platen improves Signal to Noise Ratio Sensor Signal weak because of Liner Regensburg

11 Partnership: Sensor Supplier, Tool Supplier and Manufacturer Sensor Data available at the Tool Synchronized to Tool Data On-line at the Tool Easy to analyse User FDC Fab-Host LAM Domino Collision Rate Internal Network Hercules TCPRFGen ForwardPower BiasRFGen ForwardPower Chamber Universal Plug and Play Interface merging Tool and external Sensor Data Independent, Ethernet based Network (1 Mbit / 1 Mbit) Automatic Sensor Recognition Providing Sensor with logistical Data LAM Plug and Play Interface

12 Analyze & React

13 Analyze & React 1 Electron density [16 x 1/cm3] fre e m as te r/slave Time [s] Strong Fluctuations detected for new Tool - Root Cause: missing Phase Coupling Regensburg

14 Analyze & React collision rate [mean], step 2 Collision Rate 1,8 1,192 1,376 1,56 1,744 1,928 2,112 2,296 2,48 2,664 above CD CD 392, , ,199 41,13 43,828 46,643 49, , ,87 417,91 above Gate Etch DOE Results: Pressure, RF Top/Bottom and O2/Cl2 Variation Rousset

15 optical Endpoint Analyze & React Gas flow changes watt 3 watt TCPRFGenForwardPower_AI 4 4 BiasRFGenForwardPower_AI Electron Density [11 s -1 ] Collision Rate [18 s -1 ] Gas flow changes sec Sensor and Tool Data at LAM Domino 12

16 Analyze & React Hercules Endpoint (AMAT 368,5 nm) Collision Rate [16 x s-1] Intensity EP Time [s] Oxide Process (one Recipe step), Overetch identified by collision rate. SEERS Fingerprint and optical EP

17 Analyze & React 6 35 SiO2 etch recipepara meter change by 2 % Mean Coll. Rate -He-O2 Reference_2 -He-BSC -T_Wall +T_Wall -T_Cathode +T_Cathode -T_Wall -He-O2 +T_Wall +He-O2 -CF4 +CF4 -He-BSC -Mfield Mean / depth +He-BSC +Mfield -RFPower -Pressure +RFPower +Pressure -HBr1 -CL2 +HBr1-35 +CL2 -HBr2-25 +HBr2 1 Uniformity Change % 15 Etch Rate Change % 25 4 Reference_1 Collision Rate [1 8 s -1] 5 std DEV / depth Etch Uniformity Change indicated by collision rate Similar Results for Si Etch at MxP but lower Sensitivity For Poly Etch at DPS not sensitive enough to detect Errors Dresden

18 Merge Sensor Data to FDC System

19 Merge Sensor Data to FDC System 5 Oxide Process 4,5 Electrical Parameter ~ Yield 4 Collision Rate [17s-1] 3,5 3 2,5 2 1,5 1, Time [s] Zero Yield Wafer detected

20 Merge Sensor Data to FDC System Strong Disturbances at one Poly Process Regensburg Process for new Product with bigger open Area was unstable Improvement of the Process by changing the Recipe (Pressure) since 7/19 verified by Collision Rate Stabilization of Process verified

21 Merge Sensor Data to FDC System 2 Sensor data Change in Chamber Pressure impacts the Collision Rate Collision Rate [16 s-1] Process Process Etch Time [s] Pressure 1 18 Pressure 2 Tool data 12 6 Throttle Valve Position Pressure [mtorr] Process Time [s] 8 Tool Error identified by Collision Rate 1

22 Merge Sensor Data to FDC System Slot Slot Aver. Coll. Rate [16 s-1] Collision Rate of indicated 15 wafers Wafermap: Excursion Pattern Slot 6 1 Slot 1 5 Slot Run Root Cause: Mass Flow Controller Malfunction Test Pattern identified at Process Level

23 Co-Authors Daniel Zschäbitz Mark Laqua Enrico Höfer Klaus Reingruber Klaus Behrendt Sven Mueller Robert Ronchi Baudouin Lecohier Julien Pasquet University of Dresden University of Dresden University of Applied Sciences Dresden Regensburg Regensburg AMD Saxony ST Microelectronics ST Microelectronics ST Microelectronics Further Reading: Characterization and Control..., Volker Tegeder et. al. European AECAPC Workshop 2 Supervision of Plasma Etch Processes..., Volker Tegeder et. al. AECAPC Symposium XII 2 The tremendous impact of APC for plasma etch, Volker Tegeder, Robert Ronchi, Sven Mueller, Solid State Technology 21 in press Acknowledgement: The presented work is funded by the European IST program on the SEA-Initiative