AEC/APC Symposium XV - Electrical and Computer Engineering ...gilgunn/files/gilgunn_SematechXV-1350... · Focus on ROI to make APC happen in your Fab ... Joyce Hartley and Bennie

Never stop thinking.

AEC/APC Symposium XV

Advanced Process Control Implementation in Plasma Etch at Infineon Technologies RichmondPeter Gilgunn, Charles Venditti, Victor Morozov and Patrick Kelly

Presentation Agenda

Presentation ObjectiveAbout the EnvironmentThe Opportunity in Plasma EtchOur Vision of APCAn Implementation in 3 PhasesApplications and Operational BenefitsConclusionsAcknowledgements

Help the community learn from our successes and failures

Presentation Objective

Encourage the Doers:Focus on ROI to make APC happen in your Fab

Share the IFR Plasma Etch APC experience

Tell the Decision Makers:Return on Investment (ROI) can be achieved with APC

About the Environment

Infineon Technologies Richmond200mm CMOS Fab (1st Si in March 1998)Deep trench based DRAM140nm technology in volume production

Plasma etch department Process, equipment and manufacturing> 20 manufactured etch stages>10000 wspw through each manufactured stage>180 process/chamber combinations under control>170 product/parameter combinations under control

Assuming 10000 wspw

52 weeks per year 300 die per wafer

$2 per die

1% yield or volume =

$3 120 000 revenue

Assuming 300 die per wafer

$2 per die

1 scrap lot (25 wafers) =

$15 000 revenue

About the Environment

Where we came fromStatistical process control (SPC) on in-line product dataEquipment health monitoring through blanket wafer qualificationsActivity based preventive maintenanceUnscheduled maintenance driven by excursions (SPC, parametric or yield) and hard tool faults

The Opportunity in Plasma Etch

Irreversible yield critical processSensitive to all incoming variations 3-dimensional process output limits the ability of metrology to represent process health and predict yield

etched feature dimensions and shape must fit

poly-siarc

oxide

nitride

silicon substrate impingement

film thickness and composition effect etch after etch

there is no way back!


Single wafer processing is the ruleMultiple tool subsystems act independently and/or

interact with each other to impact yieldLoad 1 Load 2

Ch 1Ch 2

Ch 3

Idle

1312

Buffer

14

• Pressure

• Temperature

• Gas Flow

• RF power

• Magnetic Field

• … or a combination of …

At throughput of 100 wafers per hour per mainframe

Ch 1 produces 33 scrap wafers in one hour and

>500 scrap wafers in one day!!!!!!!!

Ch 1 goes bad on wafer 13. This could be caused by:


More dataneeded from More sources

Our Vision of APC

Divergences from optimal conditions will be detected and compensated on first wafer (FDC)Every wafer leaves the Fab achieving its maximum yield potential – dynamic artisan processing (R2R)Capital equipment time will be utilized solely for production or predictive maintenance (OEE)Metrology will be a value added process (R2R)

Our Vision of APC

Future ConsiderationsAPC systems should be scaleable Wafer level Fab Cluster levelHigh volume commodity products Complex multi-generational portfolios

An Implementation in 3 Phases

Jan-

00

Apr

-00

Jul-0

0

Oct

-00

Jan-

01

Apr

-01

Jul-0

1

Oct

-01

Jan-

02

Apr

-02

Jul-0

2

Oct

-02

Jan-

03

Apr

-03

Jul-0

3

Oct

-03

Jan-

04

Apr

-04

Jul-0

4

Dedicated APC h/c added and

spun off

Phase 2

Phase 3

Phase 1 Projected m/h

190nm 170nm 140nm 110nm

non-APC m/h

dedicated APC m/h

Non-dedicated APC m/h

Engineering Man hours


• Shallow trench isolation depth control (Jowett and Morozov, “Shallow Trench Isolation Run–to–Run Control Project at Infineon Technologies Richmond”, ASMC 2002)

• 3% yield increase over 2 technology nodes

Phase 1 – Demonstrate Return On Investment (ROI)Reduce scrap with FDC

• Deep trench and metal etch• ~$3M revenue savings over 12 months

Increase yield with R2R

Identify infrastructure and database requirements

Justify additional resource allocation


Plasma Etch Wafer Scrap

0 1 2

6 Month Period

Nor

mal

ized

Waf

ers

Scra

pped

FDC impact at two critical process steps ~$3M revenue savings

65% reduction


Obstacles• Inertia – reliance on traditional paradigm• Skepticism – uncertainty of new paradigm• Skills gap – no experience in APC

Phase 1 – Demonstrate Return On Investment (ROI)

How We Overcame Them• Charismatic project manager• Small team of consensual junior engineers• Utilized internal competence centers• Workshops and conferences• Hired for missing skills


Phase 2 – Develop Infrastructure and ApplicationsDevelop infrastructure based on Phase 1 learning

• Equipment to CIM communication• Server hardware upgrades for functionality• “Tool server” creation for each vendor

mainframe

Hardware and software training for engineers• Data access• Data handling and manipulation

Identify applications for automation and roll-out



Phase 2 – Develop Infrastructure and ApplicationsObstacles

• Unrealistic expectations• Multiple databases with incompatible data

structure• Lack of resources both capital and human

How We Overcame Them• Prioritized projects • Pareto and FMEA• Included product yield and quality groups• Focused on ROI as top priority


Phase 3 – Automate Applications and Rollout Area-wideAutomate four applications

• Statistical machine control (FDC)• SPC by chamber (FDC)• Run to run (R2R)• Qual elimination (OEE)


Monitor progress and stay on timeline


Obstacles• Lack of capital• Lack of human resources• Managing a large quantity of milestones

Phase 3 – Automate Applications and Rollout Area-wide

How We Overcame Them• Focused on ROI • Created a graphical metric• Tracked unique milestone completion


SMC Capability

EP logbooks

Chamber EP Data

SPC by Chamber

Etchrate Qual

EliminationParticle Qual Elimination

SMC Methods Run to Run

1 Proc1 03ww06 03ww07 03ww08 03ww33 03ww32 x2 Proc2 03ww06 03ww07 03ww08 03ww09 03ww333 Proc3 x 03ww07 03ww08 03ww26 x x x4 Proc4 03ww06 03ww07 03ww08 03ww26 03ww33 x5 Proc5 03ww14 03ww07 03ww20 03ww26 03ww33 x

ProcessItem #

Actual Completion Week

Phase 3 – APC Implementation Metric

SMC Capability

EP logbooks

Chamber EP Data

SPC by Chamber

Etchrate Qual

EliminationParticle Qual Elimination

SMC Methods Run to Run

1 Proc1 03ww06 03ww07 03ww08 03ww09 03ww45 03ww50 03ww45 x2 Proc2 03ww06 03ww07 03ww08 03ww09 03ww27 03ww50 03ww37 03ww443 Proc3 x 03ww07 03ww08 03ww28 x x 03ww41 x4 Proc4 03ww06 03ww07 03ww08 03ww33 03ww45 03ww50 03ww45 x5 Proc5 03ww18 03ww07 03ww20 03ww28 03ww45 03ww50 03ww44 x

ProcessItem #

Target Completion Week

> 20 processes total


Phase 3 - Etch APC Implementation Metric

020406080

100120140160180

03w

w01

03w

w04

03w

w07

03w

w10

03w

w13

03w

w16

03w

w19

03w

w22

03w

w25

03w

w28

03w

w31

03w

w34

03w

w37

03w

w40

03w

w43

03w

w46

03w

w49

03w

w52

Fiscal Week

# of

Mile

ston

es

Target Milestones CompletedActual Milestones Completed

Applications and Operational Benefits

Wafer-chamber data enabled chamber level yield tracking and improved troubleshooting


Product etchrate data enabled qual elimination

Availability to production increased by 2% on average, test wafer usage reduced by 80% and associate productive time was increased


Yield

Helium Leak Rate

Expanded Operating Region

Yield

Helium Leak Rate

Expanded Operating Region

SMC data enabled improved fault management for OEE and predictive maintenance without loss of resolution

Allowing production in the expanded operating region increased availability by 1% and yield by 0.1%

Original fault limit


SMC data provided context to OEE statistics

0

50

100

150

200

250

300

350

Min

(RFH

OU

RA

)

12Se

p200

2 12

:00

AM

14Se

p200

2 12

:00

AM

16Se

p200

2 12

:00

AM

18Se

p200

2 12

:00

AM

20Se

p200

2 12

:00

AM

22Se

p200

2 12

:00

AM

24Se

p200

2 12

:00

AM

26Se

p200

2 12

:00

AM

28Se

p200

2 12

:00

AM

30Se

p200

2 12

:00

AM

02O

ct20

02 1

2:00

AM

04O

ct20

02 1

2:00

AM

06O

ct20

02 1

2:00

AM

08O

ct20

02 1

2:00

AM

10O

ct20

02 1

2:00

AM

12O

ct20

02 1

2:00

AM

14O

ct20

02 1

2:00

AM

16O

ct20

02 1

2:00

AM

18O

ct20

02 1

2:00

AM

20O

ct20

02 1

2:00

AM

22O

ct20

02 1

2:00

AM

24O

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02 1

2:00

AM

26O

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02 1

2:00

AM

28O

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02 1

2:00

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02 1

2:00

AM

01N

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02 1

2:00

AM

03N

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02 1

2:00

AM

05N

ov20

02 1

2:00

AM

07N

ov20

02 1

2:00

AM

09N

ov20

02 1

2:00

AM

11N

ov20

02 1

2:00

AM

13N

ov20

02 1

2:00

AM

15N

ov20

02 1

2:00

AM

17N

ov20

02 1

2:00

AM

19N

ov20

02 1

2:00

AM

21N

ov20

02 1

2:00

AM

23N

ov20

02 1

2:00

AM

25N

ov20

02 1

2:00

AM

27N

ov20

02 1

2:00

AM

29N

ov20

02 1

2:00

AM

01D

ec20

02 1

2:00

AM

03D

ec20

02 1

2:00

AM

05D

ec20

02 1

2:00

AM

07D

ec20

02 1

2:00

AM

09D

ec20

02 1

2:00

AM

11D

ec20

02 1

2:00

AM

13D

ec20

02 1

2:00

AM

15D

ec20

02 1

2:00

AM

17D

ec20

02 1

2:00

AM

19D

ec20

02 1

2:00

AM

21D

ec20

02 1

2:00

AM

Mi n(Run Date)

Gradient = f(UT)

TTCR

Chamber idle: Eng eval for yield issue

Process restriction

Unscheduled wet cleans

0

50

100

150

200

250

300

350

Min

(RFH

OU

RA

)

12Se

p200

2 12

:00

AM

14Se

p200

2 12

:00

AM

16Se

p200

2 12

:00

AM

18Se

p200

2 12

:00

AM

20Se

p200

2 12

:00

AM

22Se

p200

2 12

:00

AM

24Se

p200

2 12

:00

AM

26Se

p200

2 12

:00

AM

28Se

p200

2 12

:00

AM

30Se

p200

2 12

:00

AM

02O

ct20

02 1

2:00

AM

04O

ct20

02 1

2:00

AM

06O

ct20

02 1

2:00

AM

08O

ct20

02 1

2:00

AM

10O

ct20

02 1

2:00

AM

12O

ct20

02 1

2:00

AM

14O

ct20

02 1

2:00

AM

16O

ct20

02 1

2:00

AM

18O

ct20

02 1

2:00

AM

20O

ct20

02 1

2:00

AM

22O

ct20

02 1

2:00

AM

24O

ct20

02 1

2:00

AM

26O

ct20

02 1

2:00

AM

28O

ct20

02 1

2:00

AM

30O

ct20

02 1

2:00

AM

01N

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02 1

2:00

AM

03N

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02 1

2:00

AM

05N

ov20

02 1

2:00

AM

07N

ov20

02 1

2:00

AM

09N

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02 1

2:00

AM

11N

ov20

02 1

2:00

AM

13N

ov20

02 1

2:00

AM

15N

ov20

02 1

2:00

AM

17N

ov20

02 1

2:00

AM

19N

ov20

02 1

2:00

AM

21N

ov20

02 1

2:00

AM

23N

ov20

02 1

2:00

AM

25N

ov20

02 1

2:00

AM

27N

ov20

02 1

2:00

AM

29N

ov20

02 1

2:00

AM

01D

ec20

02 1

2:00

AM

03D

ec20

02 1

2:00

AM

05D

ec20

02 1

2:00

AM

07D

ec20

02 1

2:00

AM

09D

ec20

02 1

2:00

AM

11D

ec20

02 1

2:00

AM

13D

ec20

02 1

2:00

AM

15D

ec20

02 1

2:00

AM

17D

ec20

02 1

2:00

AM

19D

ec20

02 1

2:00

AM

21D

ec20

02 1

2:00

AM

Mi n(Run Date)

Gradient = f(UT)

TTCR

Chamber idle: Eng eval for yield issue

Process restriction

Unscheduled wet cleans

x – Process 1 + - Process 2 • - Process 3

Productive Wafers

Idle Time

Eng Unsch Down

Non Productive Wafers

PM

69.5% 6.9% 3.8% 18.4% 1.2% 0.2%

60

70

80

90

100

110

Med

ian(

YDC

_Reg

_A)

Oct

0120

02 1

2:00

AM

Oct

0820

02 1

2:00

AM

Oct

1520

02 1

2:00

AM

Oct

2220

02 1

2:00

AM

Oct

2920

02 1

2:00

AM

Nov

0520

02 1

2:00

AM

Nov

1220

02 1

2:00

AM

Nov

1920

02 1

2:00

AM

Nov

2620

02 1

2:00

AM

Dec

0320

02 1

2:00

AM

Dec

1020

02 1

2:00

AM

Dec

1720

02 1

2:00

AM

Dec

2420

02 1

2:00

AM

Dec

3120

02 1

2:00

AM

Mi n(Run Date)

-300

-250

-200

-150

-100

-50

0

50

100

Proc

ess

Mix

MTLA05 Median 140nm R1 YDC_A Compared with Yield

Process mixing

Process dedication

Start of wet clean cycle

60

70

80

90

100

110

Med

ian(

YDC

_Reg

_A)

Oct

0120

02 1

2:00

AM

Oct

0820

02 1

2:00

AM

Oct

1520

02 1

2:00

AM

Oct

2220

02 1

2:00

AM

Oct

2920

02 1

2:00

AM

Nov

0520

02 1

2:00

AM

Nov

1220

02 1

2:00

AM

Nov

1920

02 1

2:00

AM

Nov

2620

02 1

2:00

AM

Dec

0320

02 1

2:00

AM

Dec

1020

02 1

2:00

AM

Dec

1720

02 1

2:00

AM

Dec

2420

02 1

2:00

AM

Dec

3120

02 1

2:00

AM

Mi n(Run Date)

-300

-250

-200

-150

-100

-50

0

50

100

Proc

ess

Mix

MTLA05 Median 140nm R1 YDC_A Compared with Yield

Process mixing

Process dedication

Start of wet clean cycle


SMC data provided context to chamber yield performance

Process dedication increased yield by 0.7%


Wafe

r Mea

n

Date/Time Stamp

Tool1 Tool2 Tool3 Process

Systems and data for monitoring dynamic metrology performance

Tool2 does not match other gauges


Happier engineers• Workload reduced by approx. 15%• Able to answer more questions• Able to prove the answer with data• Fewer excursions to clean up• More time to focus on interesting

engineering projects … like sensors!

Conclusions

APC implementation was a long road (3+ years for reasonable functionality and process coverage)The payoff is worth the effortOperational benefits in addition to FDC and R2R will be obtainedFocus on ROI to overcome obstaclesWe still have not reached the final destination

Next step – sensor integration??$$??

Acknowledgements

Contributions to the success of APC in etch were made by: The IFR CIM and EI team - Glenn Thompson, Mike Bussey, Norman England, Joyce Hartley and Bennie Fiol, without whose support our APC infrastructure would not existThe APC Team – James Welsh, Matt England and Gary Skinner, whose support on application development made our ideas reality and opened our minds to new possibilitiesThe Etch Cimco – Dean Smith, who supported our tool server upgrades and maintained our connectivity to the production equipmentIFX APC CoC – Ralf Otto for FDC wisdomErnst-Günter Mohr for the inspiration to get started

References

1. Thomas Sonderman, AMD, “APC as a Competitive Manufacturing Technology: AMD's Vision for 300mm”, Keynote Address, 3rd European AEC/APC Conference, April 2002

2. Brian Harrison, “Expanding the Control Paradigm by Excellence in Manufacturing Execution”, Keynote Address, AEC/APC Symposium XIV, September 2002

3. Hopp and Spearman, Factory Physics, 2nd Edition, page 254. Jowett and Morozov, “Shallow Trench Isolation Run–to–Run Control Project at Infineon

Technologies Richmond”, ASMC 20025. Karzhavin et al, “Advanced Process Control Project at Infineon Technologies Richmond”, Future

Fab volume 12

Documents

AEC/APC Symposium XV - Electrical and Computer Engineering ...gilgunn/files/gilgunn_SematechXV-1350... · Focus on ROI to make APC happen in your Fab ... Joyce Hartley and Bennie