from pilot line to competitive manufacturing crolles300...

1-3 February 2009 ISS Europe 2009 - Dresden, Germany1

Industry Strategy Symposium (ISS Europe) 2009

Author Picture

(not mandatory)

From Pilot Line to Competitive ManufacturingCrolles300 – A European Business Case

Jean Marc ChéryChief Technical Officer & Executive Vice President Technology R&D

STMicroelectronics

1-3 February 2009 Jean Marc Chéry, STMicroelectronics 2

ISS Europe 2009

CR300 Overview – Agenda• Environment, Background & Mission• Technologies & Products• Facilities Overview• Critical Competitive Dimensions• Productivity & Automated Material Handling• WIP Management Execution• Advanced Process Control• Resources Redistribution• Cycle Time• Yield Learning• Conclusions


ISS Europe 2009

Environment & Background• Location: Crolles, near Grenoble• Ecosystem: 2 Fabs (200mm & 300mm) and R&D• Contribution to the Company: 22% of sales

• 300mm Plant sized for 20K wafers/month• Fully owned by STMicroelectronics, former Crolles2 Alliance• Joint venture with Freescale and NXP ended in Q4-2006

200mm7500 WPW0.25-0.13µ

300mm3000 WPW(actual)

Construction started: Mar-01First equipment in: Sept-02

Total Investment: 1.7b$


ISS Europe 2009

• Production on mature technologies (nodes N-1/N)• Fast prototyping of new products designed in the technology nodes

N+1/N+2 (65nm, 45nm)• Process integration and R&D (node N+3 ~32/28nm)

� combined within the same entity • Provide ST with Best-in-Class high performance Logic and differentiated

technologies:– Accelerated manufacturing ramp-up– Optimized time to market with exemplary services for prototypes

(“design win”)– Cost competitive– Yields at benchmark

Generations N-1 N N+1 N+2 N+3

TechnologyNodes

C120C110

C090C065C055

C045C040

C032C028

Mask levels ML 35 37 41 36 - 38 37 - 39

ML 248nm 30 24 29 21 - 25 23 - 25

ML 193nm 5 13 12

ML 193nm immersion 13 14

Metal layers 6 6 7 7 7

Operations MES 165 187 198 250 265

Process steps 520 589 624 768 800

Complexity factor 0.90X 1.00 1.06X 1.32X 1.36X

CR300 – Missions


ISS Europe 2009

• Technologies:– Advanced CMOS– CMOS Derivatives Options:

• Analog/RF process• Embedded Memories (DRAM, NVM)• CMOS Imagers

• Application segments:– Communication – Wireless

• 3G Digital baseband• Connectivity• Imaging

– Digital Consumers• Digital & HD TV, set-top box

– Computer Peripherals– Automotive

• Safety, power-train

852 3MP 24mm²852 3MP 24mm²

Technologies & Products


ISS Europe 2009

Power:

Installed = 39MVAPeak demand = 15.6MVA

Fab demand = 7.5MVA

Facilities = 8.1MVA

30MWcooling capacity

Process exhausts580 000 m3/hr

80 m3/hr Ultra Pure Water Plant

12’ FAB

Fabsupport

Master plan designed for extension

9 500 m²

2 000 m²

cleanroom≈ 11 500 m² with fab support

Facilities Overview• Prerequisite to competitiveness: Infrastructure robustness

– State-of-the-art facility designed to span several technology generations during its life cycle

– Design criteria = "no limitation by the facilities down to the limits of optical lithography"


ISS Europe 2009

roof structure

plenum

chemical filters

axial fan

mezzanine

subfab

support zones

ballroomwaffle slab

• Specific Features: – Vertical organization of the Fab building– Structural design: high dynamic stiffness & low vibration levels– In-line chemical filtration for AMC’s control (airborne molecular

contamination)

mezzanine

3.6m column grid

chemical filtration on the recirculation air loop

Fab Building Concepts


ISS Europe 2009

Total Volatile Organic Compounds (IPA excluded) in Cr olles 2 clean room atmosphere

0

20

40

60

80

100

120

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180

200

1 2 3 4 5 6 7 8 9 10

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2003 2004

Con

cent

ratio

n (p

pbV

)

1 - TT2

2 - CMPW/OX

2 - MET-LITHO

3 - ETCH2

3 - LITHO1

4 - LITHO1

5 - DIEL2

6 - DEF

ZO - IMPLANT

B1 - labo

Linear (Limite - Fab)

Sum of Total estimation sans IPA

Année SEM

PlenumBay

W4 : VOC Filters installation in RECChemical filters installation in recirc air

0.01

0.1

1

10

100

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

NO2

NH4

µg/m3

µg/m3

CR300 Photo background

ambient

5

SO2

0.5

scanner

reticules storage

Targets for 193nm photolithography

Sulfur dioxide (SO2) and Ammonia (NH4)

concentration limits

mask hazing

• Contamination Control Driver: air "chemical" quality – Permanent containment against molecular contamination resulting from

fugitive leaks & chemical spills (AMC)• Centralized recirculation with fan towers includes 3-stages of chemical filtration:

– VOC (volatile organics compounds)– Acids– Bases (ammonia, amines)

• Eliminate reticle hazing during introduction of 193nm lithography• Reduce level of AMC's in the fab down to the ppb level

AMC’s levels in the Fab ambient before

and after in-line chemical filtration

(NH4)2S04 crystal formation

Molecular Contamination Control


ISS Europe 2009

• Open ballroom = 9 500 m²• Cleanliness Class = IS04 (formally Class100) – Isolation technology (FOUP

+ mini-environment at tool level)• Ceiling filter coverage higher than the benchmark for 300mm ballroom (50%)• Capacity = 3000 WPW• 315 main equipment• 4800/5000 WPW at

saturation

• Maintain cleanliness Class IS04 in operations• Maintain 160 air changes/hr: heat dissipation,

better ESH and working conditions• Background cleanliness for tool maintenance

The Cleanroom at a Glance

FOUP300mm

lot carrier

~ 9 kg with 25 wafers


ISS Europe 2009

5%

7%

9%

11%

13%

15%

17%

19%

21%

23%

25%

27%

50 65 80 95 110

125

140

155

170

185

200

215

230

245

260

275

290

305

320

335

350

365

380

395

410

425

440

455

470

485

500

515

530

545

560

575

590

605

620

635

650

665

680

695

710

725

Critical Competitive Dimensions• When difficult conditions prevail, some paradigms that ruled the industry

economics are no longer valid.– If “small is not always beautiful… Mega-Fabs are not necessarily

mandatory…”• The statistical fallacy behind the Economy of Scale equation:

– Mainly driven by the belief that manufacturing performances follow the Central Limit theorem:

varia

bilit

y

(waf

er c

ost)

N

average variability in performances according to the central limit theorem

population / size

where N = number of Fabs, nbr of m², nbr of tools, nbr of people, nbr of wafer starts…

√N

1≈

Conventional wisdom: the bigger your Fab, the better !

Is it true ?


ISS Europe 2009

√N

1≈

2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,0001,000

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

0.9

Wafer Starts per Week

Rel

ativ

e $$

per

WS

PW

Equipment CAPEX Required versus InstalledCapacity for 65nm Technology

Beyond 5K, investment mainly driven by immersion lithography photo cells

45

Critical Competitive Dimensions (2)• For SOC (System On Chip) products mix

spans several technologies in the same Fab• Lithography drives equipment Capex• Introduction of immersion lithography at

45nm & 32nm distorts the depreciation figure (becoming more “linear”)

• CR300 Fab model/goal ≈ 5000 wafers/week0

500

1000

1500

2000

2500

3000

3500

100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550

0

500

1000

1500

2000

2500

3000

3500

Required units in the tool set to match capacity

CapexPhoto cells immersion (scanners & tracks)

• 5000 WPW• 10 000m² CR• Census ~ 1000• Yield & wafer cost at

benchmark with foundries


ISS Europe 2009

Competitiveness Roadblocks• Factors jeopardizing competitiveness of semiconductor manufacturing

in Europe:

– Currency disparities – €/$ exchange rate artificially increases manufacturing costs

– Stringent labor policies, lack of sectorial flexibility in working hours and employment conditions

– Weak education system in Industrial Engineering and Manufacturing Sciences

– Excessive cost of process equipment maintenance (contracts & spare parts)

– Stringent legislative environment and pressure from the EU in the field of ESH and Security

– Raising cost of Energy through the entire supply chain

♣

♣

♣


ISS Europe 2009

Direct Labor Productivity (and flexibility)• Factors jeopardizing competitiveness of

semiconductor manufacturing in Europe:

– stringent labor policies,

– lack of flexibility in working hours and employment conditions

• Options retained:

– Target productivity gains compatible with skilled jobs creation

– Deploy Automation Fab wide:

• Retrofit pilot line with Automated Material Handling System (AMHS)

• WIP Management (including R&D lots and Engineering loops)

• Large scale deployment of tools for Advanced Process Control

580 540

650

INDIRECTS Operations

INDIRECTSSTD

DIRECTS

Fab staffing = 1 230

∑ census = 1 770 with STD (Silicon Technology Development Team)


ISS Europe 2009

1) stocker installation 2) overhead track installation

Automated Material Handling System3) Vehicles introduction

4) debugging and checking safety

5) “hands-free” lot loading and unloading

• Retrofit completed in 3 quarters from move-in of first stocker to release of first set of tool in Semi-auto mode

• Zero incident – Zero interruption to production (ITP)


ISS Europe 2009

Automated Material Handling System (2)

Metrology tool set

OHB storage(buffer storage just above tools)

OHT vehicle (*)

stocker

• Note the buffer storage of the lot/FOUP under the ceiling (OHB = Over Head Buffer) in close proximity to the “next tool” to reduce delivery time when the tool will become available

Equipment load port

track

(*) OHT = Over Head Transportation

bypass track

"fast lane"

• View of Photo Metrology bay after AMHS retrofit


ISS Europe 2009

AMHS & Automation Deployment• 15 months from "manual" handling to Auto mode• 100 tools under AMHS (33%) – Full deployment in 2009• Activity coverage ~ 58% (% of lot moves performed by the AMHS)• Full Auto mode implies development of some complex dispatching rules

7%

18%

24%

39%

44%

62%58%

14 726

0

5 000

10 000

15 000

20 000

25 000

2007

w01

2007

w03

2007

w05

2007

w07

2007

w09

2007

w11

2007

w13

2007

w15

2007

w17

2007

w19

2007

w21

2007

w23

2007

w25

2007

w27

2007

w29

2007

w31

2007

w33

2007

w35

2007

w37

2007

w39

2007

w41

2007

w43

2007

w45

2007

w47

2007

w49

2007

w51

2008

w01

2008

w03

2008

W05

2008

W07

2008

W09

2008

W11

2008

W13

2008

W15

2008

W17

2008

W19

2008

W21

2008

W23

2008

W25

2008

W27

2008

W29

2008

W31

2008

W33

2008

W35

2008

W37

2008

W39

0%

10%

20%

30%

40%

50%

60%

70%

80%

AMHS coverage transports per day fab activity (lots)

Significant paradigm shift moving from

"operator centric" to "system centric"

operations


ISS Europe 2009

Productivity – Operator Task BreakdownTasks eliminated in FULL-AUTO mode(lot dispatching by the “system”)

Tasks eliminated in SEMI-AUTO mode(lot selection by operator)

• Semi-Auto mode � Direct Productivity improves by 40%

• Full Auto mode � Direct productivity improves by 70%

Goal: 95% of the tool set integrated with the AMHS and under automation

Manual

handling

46%

Job prep, lot

selection

15%Lot selection

16%

Break,

logistics

8%

Gather

instructions,

passdown

15%

Load, unload

FOUP

33%

Walk with a

FOUP

30%

Retrieve lot

from stocker

11%

Walk without

a FOUP

26%


ISS Europe 2009

Auto Mode Deployment – Census Evolution• AMHS coverage in Q4-08 = 58% � 18% productivity increase at ~ constant

Direct census• AMHS coverage plan by Q4-09 = 90% � 45% productivity increase � 37%

reduction in Direct census

DPP Direct productivity (arbitrary unit)

Tot

al D

irect

Cen

sus

300 32

5

329

334

330

328

332

334

323

323

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337

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327

319

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321

321

303

235

40 74 100 115 118 120 122

238

278

240

242

245

256

262

2020201893 125

100

103 10

9

110

110

111

112

108 11

2

113

116

118 12

5

126

126

129 13

8 145 15

4 160 16

4

165

168

170

650

560

535

0

100

200

300

400

500

600

700

Jan-

08

Feb

-08

Mar

-08

Apr

-08

May

-08

Jun-

08

Jul-0

8

Aug

-08

Sep

-08

Oct

-08

Nov

-08

Dec

-08

Jan-

09

Feb

-09

Mar

-09

Apr

-09

May

-09

Jun-

09

Jul-0

9

Aug

-09

Sep

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Oct

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-09

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∆ census(gain)

Directs

Directs TPM,TPP

DPPMoves/hr


ISS Europe 2009

Reticle MngtiReticle

WIP MngtFactory Works

EquipmentMngt

MaintenanceMngtXsite

Wipper(home made)

PrioritiesMngt

(home made)

Alarms NotificationOCAP Mngt

Business Works

ECN(home made)

ExperimentMngt

(home made)

� Ensure the security of all changes inside Manufacturing Execution System

� Allow Engineering and R&D engineers to define new process flows for experiments, short loops & trials

� Allow Production Control to change/assign specific priorities to the lots

� Allow operators to allocate or select the next lot to be processed on a given equipment based on process capability criteria (dispatch list)

� Workflow to model the list of actions to perform in case of out of control events (fault detection, alarms, SPC limits …)

Factory Operations

Fab Userinterface

Brooks

MES – WIP Management Execution

Manufacturing Execution System (300works)

300works Business Rules

M.E.S Database

Process Control


ISS Europe 2009

RTD – Real TimeDispatching

Brooks

Execution SystemActivity Manager

Brooks

MCS – MaterialControl System

Muratec

� Event driven software that triggers workflows running based on different events coming from others MES modules

� MCS – AMHS controller, manage the storage, transport, loading & unloading of the lot carriers (FOUPs)

command




EquipmentMngt


M.E.S Database

Process ControlMaintenance

MngtXsite

Wipper(home made)

PrioritiesMngt

(home made)


Business Works

ECN(home made)

ExperimentMngt

(home made)

Factory Operations

� Dispatching system allocating a lot's) or defining the next task to be processed on a given equipment

Fab Userinterface

Brooks

MES – WIP Management Execution


ISS Europe 2009

Engineering Data Collection

SPC- SpaceCamline

FDC - Fault Detection

Maestria - PDF

APCRun to run

Adventa

RMS – RecipeMngt

Camline

PRT – Recipethroughput(home made)

� Manage FDC strategy, collect data, perform analysis at equipment level

� Run-to-Run advanced process control at lot level (2007), deployment at wafer level (2008)

� Verifies recipe before process starts, tracks revisions, manage recipe status and approval loop

� Calculate/update equipment/recipe throughput for accurate capacity model

� Events and alarms manager, fault detection summary for real-time actions

PrioritiesMngt

(home made)

ECN(home made)

ExperimentMngt

(home made)

Fab Userinterface

Brooks




EquipmentMngt


M.E.S Database

MaintenanceMngtXsite

Factory OperationsRTD – Real Time

DispatchingBrooks

Execution SystemActivity Manager

Brooks

Wipper(home made)

Event & AlarmMngt

StarView


Business Works

Process Control

MES – Advanced Process Control


ISS Europe 2009

APC Implementation

PROCESSEQUIPMENT

METROLOGYEQUIPMENT SPC

OUT OFCONTROL

� STOP EQUIPMENT� STOP DOWNLOAD

RECIPE

OCAP

YES

Step (N)

NO

1. OCAP System (Out of Control Action Plan): alarm notification; basic solution to manage out of control events occurring during manufacturing

PROCESSEQUIPMENT


OUT OFCONTROL


RECIPE

OCAP

tool & sensors data

SilverBox TM

FAULTDETECTION

OUT OFCONTROL

YES

YES

NO

Step (N)

NO

2. FDC System : Fault Detection and Classification; monitors the process equipment, provides “health” data and alarm logs with drill-down capability into tool and internal sensors for troubleshooting by engineers receiving fault notification

PROCESSEQUIPMENT


OUT OFCONTROL


RECIPE

OCAP

tool & sensors data

SilverBox TM

FAULTDETECTION

OUT OFCONTROL

YES

YES

NO

PROCESSEQUIPMENT

(N-n)

METROLOGYEQUIPMENT

(N-n)

Step (N-n)

Step (N)

NO

RUN-to-RUNProcess centering

Recipe update

Recipe up load

Feed Forward data

3. RUN to RUN Control


ISS Europe 2009

Lot Dispatching & Process Control – Auto Mode

RTDReal Time Dispatcher

AMActivityManager

EventtriggerWhat’s

next ?

Next lotselected

MES300works

Transport command Materialcontrol system

Lottransport

EIEquipmentAutomation

Loading

handshake

Data collection plan

Process specifications

RMSRecipe

Management

Recipe download

Run to RunAPC

AdvancedProcessControl

Adjust Run-to-Run parameters

process starts

SPC data collection

EngineeringDatabase

tool parameters transfer

process ends

EQUIPMENT

Job outEventtrigger

Transport command

Where’snext ?

Next destinationis selected

Lottransport

Statuschange

PROCESS CONTROL

FACTORY OPERATIONS

AMHS

unloading

FDCFault

Detection

Job in


ISS Europe 2009

Resources Redistribution• Factors jeopardizing competitiveness of semiconductor manufacturing in

Europe:– Weak education system in Industrial Engineering and Manufacturing

Sciences– Excessive cost of process equipment maintenance

• Strategy reorientation: Repatriation of activities and re-deployment of internal know-how:– Cross-learning from other industries (Industrial Engineering) – Go back to basics, “re-discover” Lean Manufacturing principles – Largest sources of productivity gains reside at the boundaries between the

functions – Eliminate the go-between’s !!– Reduce dependence on suppliers FSE (Field Service Engineers):

• Internal training (maintenance, failure analysis)• Manage employee “memory” knowledge

– Internal repair center– Alternative sourcing for spare parts supply (create local economic value)


ISS Europe 2009

1.02

0.48

0

0.25

0.5

0.75

1

1.25

1.5

1.75

QueuingTime

ProcessTime

Service for Prototypes – Cycle Time• Manufacturing Cycle Times are very long

– 68% queuing– 32% running

• Queuing time reduction:

1. improve equipment availability (OEE)2. reduce availability variance 3. reduce lot transportation time (AMHS)

4. reduce “white space” = tool idling time between unloading a processed lot and waiting for the delivery and loading of the next one (advanced scheduling)

Cycle time in Day per Mask Level (DPML)

Production lots

1.5 DPML

12-Nov-07

14-Nov-07

16-Nov-07

18-Nov-07

20-Nov-07

22-Nov-07

24-Nov-07

26-Nov-07

28-Nov-07

30-Nov-07

02-Dec-07

04-Dec-07

06-Dec-07

08-Dec-07

10-Dec-07

AC

TIV

E

NIS

O

NW

ELL

YP

VT

PV

T2

NW

GO

PW

ELL

YN

VT

NV

T2

PW

GO

GO

2

NP

RE

D

PP

RE

D

GA

TE

NLD

DG

PLD

DG

PLD

DS

NLD

DS

XN

LDS

PLD

DL

NLD

DL

NS

D

PS

D

SIP

RO

CO

NT

A

LIN

E1

LIN

E2

VIA

1

LIN

E3

VIA

2

LIN

E4

VIA

3

LIN

E5

VIA

4

VIA

5

LIN

E6

VIA

6

LIN

E7

PA

DO

P

ALU

CA

PA

D

SH

IP

FAB HC (0.67 dpml) FAB ACT• Process complexity implies cycle time target < 1 day per mask level

C065 Prototype41 mask levelsCycle time = 23 daysRate = 0.55 DPMLclose to theoretical process time Flow chart (620 steps - 40 masks)

23 d

ays

Production (average)36 mask levelsCycle time = 54 daysRate = 1.5 DPML


ISS Europe 2009

Yield Learning Acceleration – 65nm

Yield learning acceleration based on:• PDF methodology using short loops and

Characterization Vehicles – designed with specific patterns sensitive

to defectivity– electrically testable on massively

parallel testers• ST’ test vehicles: Provide structures to

support modeling, process development and yield learning (Promo65, Ryde65)

• Divisions support:– Electrical test of Engineering lots– Fast feedback on prototypes

• Trend for SOC Manufacturing:– Continuous increase of the contribution of parametric and device layout

yield losses with introduction of nodes• Collaboration with PDF Solutions:

– yield improvement– process variability tracking and control

RYDE65

PROMO65

0% 50% 100%

45nm

65nm

90nm

120nm

Random

Layout/product

Parametric

Yield loss mechanism evolution with technology nodes

Detractors

random

layout/product

parametric

Characterization Vehicles (CV®’s)


ISS Europe 2009

Layout Attributeswidths, lengths, spacing,

counts, densities, borders, antennas, etc.

Yield Models and Failure Rates

customized models for metal, contact, via, transistor

performance, etc.

Product Layout In line inspection

Metrology Data

Characterization Vehicles

Other Test Chips

Yield Impact Matrix (YIMPTM)

Yield Ramp Simulator (YRSTM)

Layout attributes extractions based on wafer target,

NOT just drawn

PDF-specific method assesses impact of design on

product(s) yield

Yield Learning – PDF Methodology

∫∞

xo

dxxDSDxCA )()(

Yproduct= Yrandx Ysys

Yrand= exp (- )

Ysys= e -λsys

λsys = f (design, process)

Determine defect rates required to achieve target yields

Pred Yield

Poly all poly 0.99M1 shorts 0.95M2 shorts 0.96M3 shorts 0.98

Contact N+AA 0.97Contact P+AA 0.98Contact N+Contact 0.98

V2 Borderless 0.90V2 Border 1.00V3 all 0.99

Parametric VthP 0.97

Module

YIELD MODEL


ISS Europe 2009

Yield Learning – D 0 TrendYield Learning / 3-year D0 trend

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

2.20

2.40

2.60

2.80

3.00

Q3-05 Q4-05 Q1-06 Q2-06 Q3-06 Q4-06 Q1-07 Q2 -07 Q3-07 Q4-07 Q1-08 Q2-08 Q3-08 Q4-08

D0 Poisson (def/cm

2)

D0 90nmD0 65nmD0 120/110nmARIMA 90nmARIMA 65nmARIMA 120/110nm

C090

C065

C110

ARIMA = 0.95

ARIMA = 0.88ARIMA = 0.85

ARIMA = Auto Regressive Integrated Moving Averageex: ARIMA = 0.85 � Poisson D0 gap to target reduced by 15% per month


ISS Europe 2009

Conclusions• Mid-size Fabs (~5000 wafers/wk) are viable economical models for SOC

manufacturing in Europe as long as the risks of variability in performances are balanced by:

– Large scale implementation of Advanced Process Control and predictive fault detection techniques

– WIP Management tools integrating automated dispatching of lots and advanced planning of tasks

• Maintaining manufacturing capability despite stringent employment policies and restrictive legislation implies pro-active strategies and breaking few paradigms:

– Unleash productivity through elimination of non-added value tasks (AMHS)

– Create skilled job through internal repatriation and integration of activities directly impacting the wafer cost competitiveness:

• Tool maintenance & repair

• Automation & IT systems

– Anticipate future European legislative initiatives (ESH field)

from pilot line to competitive manufacturing crolles300...

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