economics of speed

5/12/2018 Economics of Speed - slidepdf.com

http://slidepdf.com/reader/full/economics-of-speed 1/54

4/10/07 Leachman - Economics of Speed 1

The Economics of The Economics of

SpeedSpeedProfessor Robert Leachman

Director, Competitive Semiconductor Manufacturing Program

Engineering Systems Research Center

University of California at BerkeleyApril 10, 2007




IntroductionIntroduction

•• The sales price of virtually everyThe sales price of virtually every

semiconductor device and manufacturingsemiconductor device and manufacturing

service declines over time …service declines over time …




““Time is money”Time is money”DRAM price decline history

1%

10%

100%

0 2 4 6 8 10 12 14 16 18 20 22 24 26

months

after

introduction

%

o f I n t r o d u c t o r y P r i c e ( L O G

256K

1M

4M

16M

64M




““Time is money”Time is money”Intel CPU price decline history

10%

100%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

months

after

introduction

%

o f I n t r o d u c t o r y P r i c e ( L O G

P 166

PII 300

PIII 700

P4 1.4G




““Time is money”Time is money”Foundry price decline history

10%

100%

1 8 15 22 29 36 43 50 57 64

months

after

introduction

% o

f i n t r o d u c t o r y p r i c e ( L O G

0.13u

0.15u

0.18u

0.25u

0.35u

0.5u




Introduction (cont.)Introduction (cont.)•• This suggests there must be large economicThis suggests there must be large economic

values for increasing the speed of values for increasing the speed of

technology development, the speed of technology development, the speed of

manufacturing implementation and themanufacturing implementation and the

speed of manufacturing execution ...speed of manufacturing execution ...




Introduction (cont.)Introduction (cont.)•• Most analyses of Most analyses of fabfab economics concern estimation of wafer economics concern estimation of wafer

costs or die costscosts or die costs

– – Reduction of cycle time reduces finance costs for working capitaReduction of cycle time reduces finance costs for working capitall

– – Reduction of cycle time improves yieldsReduction of cycle time improves yields

•• Fewer lots at risk during process or equipment “excursions” notFewer lots at risk during process or equipment “excursions” not detecteddetected

until end of lineuntil end of line

•• Quicker completion of experiments to qualify process or equipmenQuicker completion of experiments to qualify process or equipmentt

changes that improve yieldchanges that improve yield

•• What is needed in addition is a tool to analyze impacts of What is needed in addition is a tool to analyze impacts of

manufacturing and R&D speed on sales revenuesmanufacturing and R&D speed on sales revenues (“revenue(“revenue

gain model”)gain model”)




AgendaAgenda

•• Part 1Part 1 -- Tools to impute value for Tools to impute value for

manufacturing speedmanufacturing speed

•• Part 2Part 2 – – Tools to estimate manufacturingTools to estimate manufacturingspeedspeed




Calculating the value exCalculating the value ex--anteante

•• If we can predict the trend in sales prices,If we can predict the trend in sales prices,

•• and if we can predict the reduction inand if we can predict the reduction in

elapsed times from a proposed engineeringelapsed times from a proposed engineering

project, project,

•• then we can predict the revenue gain fromthen we can predict the revenue gain fromthe projectthe project




Revenue Gain ModelRevenue Gain Model•• Assume the sales market is immediately available for allAssume the sales market is immediately available for all

output that can be completed and that prices are decliningoutput that can be completed and that prices are declining

according to a known function of timeaccording to a known function of time

•• Sales revenues can be increased by reducingSales revenues can be increased by reducing durationsdurations for for

– – process development and qualification, equipment installation an process development and qualification, equipment installation andd

qualificationqualification

– – yield and volume rampsyield and volume ramps

– –

manufacturing cycle time (AKA flow time)manufacturing cycle time (AKA flow time)

•• Revenue gainRevenue gain = (total sales revenue for proposed= (total sales revenue for proposed

durations)durations) -- (total sales revenue for status quo durations)(total sales revenue for status quo durations)




Revenue Gain ModelRevenue Gain Model

•• LetLet PPii(t (t ) denote the sales price of device) denote the sales price of device ii at timeat time t t ..

•• LetLet W W ii((t t ) denote the wafer starts,) denote the wafer starts, Y Y ii((t t ) the yield,) the yield,

CT CT ii((t t ) the manufacturing cycle time, and) the manufacturing cycle time, and H H ii thethe

remaining product life, whereremaining product life, where t t is the time of is the time of

wafer start.wafer start.

•• Then the remaining lifetime revenue isThen the remaining lifetime revenue is

( ) dt t Y t W t CT t P ii

H

ii

i

)()()(0∫ +




ExEx--ante revenue gain model (cont.)ante revenue gain model (cont.)

•• The revenue gain of a project is the totalThe revenue gain of a project is the total

difference in lifetime revenues for all products:difference in lifetime revenues for all products:

( )

( )∑ ∫

∑ ∫

+−

+

i

Bi

Bi

H

Bii

i

A

i

A

i

H

A

ii

dt t Y t W t CT t P

dt t Y t W t CT t P

i

i

)()()(

)()()(

0

0





•• A practical approximation is to model sales price asA practical approximation is to model sales price as

a declining exponential (e.g., prices falling 50% per a declining exponential (e.g., prices falling 50% per

year)year)

•• This facilitates calculation of the integral expressingThis facilitates calculation of the integral expressing

lifetime revenuelifetime revenue

at

iiePt P

−=0)(




ExEx--ante revenue gain model (cont.)ante revenue gain model (cont.)•• Another practical approximation is to model theAnother practical approximation is to model the

yield ramp as one minus a negative exponential:yield ramp as one minus a negative exponential:

Die Yield

0 RT-VT TimeH

YF

Y0

Ramp Phase

Mature Yield

Phase





•• Die yield is modeled as follows:Die yield is modeled as follows:

wherewhere RT RT is the time to ramp to mature yield andis the time to ramp to mature yield and bb

defines the shape of the yield curvedefines the shape of the yield curve

•• This also helps to make the integral expressingThis also helps to make the integral expressinglifetime revenue easier to calculatelifetime revenue easier to calculate

RT t e

eY Y Y t Y

bRT

bt

F ≤−

−−+=

−

−

,1

1)()( 00




The total lifetime revenueThe total lifetime revenue{W Y PTR F 0=

( )( )

⎪⎪

⎭

⎪⎪

⎬

⎫

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

⎥⎦

⎤⎢⎣

⎡

+

−−

−

⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜

⎝

⎛

−

−+⎥

⎦

⎤⎢⎣

⎡ −⎟⎟ ⎠

⎞⎜⎜⎝

⎛ +

− +−−

−

−−−+−

ba

e

a

e

e

Y Y

a

e

Y

Y

a

eee

RT baaRT

bRT

F

aRT

F

aH aRT CT VT a 11

1

11

0

0

wherewhere PP00 is the initial selling price,is the initial selling price, Y Y F F is final yield,is final yield, W W isis

thethe fabfab--in rate,in rate, VT VT is development time,is development time, CT CT is cycle time,is cycle time,

RT RT is yield ramp time,is yield ramp time, H H is process life,is process life, Y Y 00

is initial yield,is initial yield,

a a is rate of price decline, andis rate of price decline, and bb is yield learning rate.is yield learning rate.

TRTR is the total revenue over the product life.is the total revenue over the product life.




Example revenue gains:Example revenue gains:

Compressing the time to first siliconCompressing the time to first silicon

•• Assume sales price is initially $10,000 per 100%Assume sales price is initially $10,000 per 100%--yieldingyielding

wafer and declining 25% per year,wafer and declining 25% per year, H H = 5 years,= 5 years, Y Y 00 = 0.50,= 0.50,Y Y F F = 0.90,= 0.90, W W = 25,000 WSPM= 25,000 WSPM

•• Consider cases of Consider cases of VT VT = 4, 3.5, 3, and 2.5 months= 4, 3.5, 3, and 2.5 months

VT VT Total revenueTotal revenue Revenue gain compared toRevenue gain compared to(days)(days) for 5 yearsfor 5 years prod’nprod’n VT VT = 120 days= 120 days

120120 $6.57 billion$6.57 billion $0$0

105 $6.65 billion105 $6.65 billion $80 million$80 million9090 $6.73 billion$6.73 billion $160 million$160 million

7575 $6.81 billion$6.81 billion $240 million$240 million




Example revenue gains: What is oneExample revenue gains: What is oneday of cycle time worth?day of cycle time worth?

•• Consider 200mm image sensor Consider 200mm image sensor fabfab:: W W = 10,000 WSPW,= 10,000 WSPW, Y Y F F

= 420 DPW,= 420 DPW, CT CT = 50 days,= 50 days, PP00 = $4.50 declining 25% per = $4.50 declining 25% per

year,year, H H = 2 years remaining product life= 2 years remaining product life

•• Revenue gain from reducing cycle time by one day:Revenue gain from reducing cycle time by one day:

$1.14 million$1.14 million

=+−−+∫ ∫ H H

dt t Y t W CT t Pdt t Y t W CT t P0 0

)()()()()()1(




ExEx-- post valuations of post valuations of fabfab speedspeed

•• If we have actual history of production,If we have actual history of production,

sales, selling prices and elapsed times, wesales, selling prices and elapsed times, we

can calculate the actual revenue gaincan calculate the actual revenue gain

•• Consider a case in which all output is soldConsider a case in which all output is sold

immediately after production. Then theimmediately after production. Then therevenue gain may be expressed as follows:revenue gain may be expressed as follows:




ExEx-- post calculations post calculations

∫ ∫ +−= H H

dt t CT t Pt Odt t Pt O R00

))(Δ()()()(Δ

wherewhere OO((t t ) is the production output at time) is the production output at time t t ,, PP((t t ) is the) is the

average selling price at timeaverage selling price at time t t ,, ΔΔCT(t CT(t )) is the reductionis the reduction

in cycle time for the output at timein cycle time for the output at time t t , and, and ΔΔ R R is the gainis the gain

in revenue over the interval [0,in revenue over the interval [0, H H ].].




Step function approximationStep function approximation•• Suppose cycle time for output in monthSuppose cycle time for output in month t t

was 45 days (compared to 80 days if projectwas 45 days (compared to 80 days if projecthad not been undertaken)had not been undertaken)

•• Then the revenue gain isThen the revenue gain is OO((t t )*)*PP((t t )) --OO((t t )*[(25/30))*[(25/30)PP((t t +1) + (5/30)+1) + (5/30)PP((t t +2)]+2)]

0 30 60 90t t+1 t+2




Example: the SLIM project atExample: the SLIM project at

SamsungSamsung

•• Joint project of Samsung and Leachman &Joint project of Samsung and Leachman &

Associates LLC to reduce cycle timeAssociates LLC to reduce cycle time

•• Time frame: March, 1996Time frame: March, 1996 -- December, 2000December, 2000

•• Application scope: TwoApplication scope: Two fabfab lines initially,lines initially,

eventually expanded to all semiconductor eventually expanded to all semiconductor

factories of the companyfactories of the company




20

30

40

50

60

70

80

90

100

Dec-95 Jun-96 Dec-96 Jun-97 Dec-97 Jun-98 Dec-98 Jun-99

A v g .

f a b c y c l e t i m e ( d a y s )

4M

16M

64M

128M

Samsung’s DRAM cycle timesSamsung’s DRAM cycle times

SLIM

begins

SLIM

beginsSLIM begins

on all lines

Intrinsic

cycle time




Samsung’s DRAM selling pricesSamsung’s DRAM selling prices

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

200.00

Mar-96 Sep-96 Mar-97 Sep-97 Mar-98 Sep-98 Mar-99 Sep-99

A v e r a g e s e l l i n g p r i c e ( $ )

4M

16M

64M

128M




Financial impact of SLIMFinancial impact of SLIM

•• Sales revenues for the DRAM output of Sales revenues for the DRAM output of

Samsung’sSamsung’s fabfab lines over the period March,lines over the period March,

19961996 -- December 2000 were tallied: $21.9December 2000 were tallied: $21.9

billion billion

•• Sales revenues were reSales revenues were re--computed assumingcomputed assuming

fabfab cycle times had stayed at 80 dayscycle times had stayed at 80 days




Financial impact of SLIMFinancial impact of SLIM•• Through 2000, SLIM increased DRAM salesThrough 2000, SLIM increased DRAM sales

revenues by 4.4% or US $954 millionrevenues by 4.4% or US $954 million – – Including nonIncluding non--DRAM production, theDRAM production, the

revenue gain was $1.1 billionrevenue gain was $1.1 billion

•• Subsequently, Samsung’s DRAM market shareSubsequently, Samsung’s DRAM market share

rose from 18% to 40%. Meanwhile,rose from 18% to 40%. Meanwhile, HynixHynix wentwent

bankrupt, many DRAM makers left the market, bankrupt, many DRAM makers left the market,others experienced large lossesothers experienced large losses




SummarySummary – – Part IPart I•• Ex Ex--anteante andand exex-- post post methods have beenmethods have been

proposed for calculating revenue gains from proposed for calculating revenue gains from

cycle time reductioncycle time reduction

•• Economic impacts of reductions in time toEconomic impacts of reductions in time to

qualification, time to volume and cycle timequalification, time to volume and cycle time

may be calculated using spreadsheet toolsmay be calculated using spreadsheet tools




General Strategy for Cycle TimeGeneral Strategy for Cycle Time

ReductionReduction

•• Routinely calculateRoutinely calculate entitlement entitlement cycle timescycle times•• If entitlement is to be reduced, we must devise andIf entitlement is to be reduced, we must devise and

evaluate engineering projects that reduce itevaluate engineering projects that reduce it

•• At the same time, we improve execution tools toAt the same time, we improve execution tools to

close the gap between actual and entitlementclose the gap between actual and entitlement




Methods for calculating/estimatingMethods for calculating/estimatingentitlement cycle timesentitlement cycle times

•• DiscreteDiscrete--event simulationevent simulation – – centralized dept.,centralized dept.,

expert usersexpert users

•• Queuing theoryQueuing theory – – decentralized spreadsheet tools,decentralized spreadsheet tools,every engineer can be a user every engineer can be a user

•• The application of Queuing Theory to calculateThe application of Queuing Theory to calculate

entitlement cycle times is recommended as a moreentitlement cycle times is recommended as a more

effective strategy organizationallyeffective strategy organizationally




Part IIPart II -- Introduction toIntroduction to

Queuing AnalysisQueuing Analysis

jk jk jk SCT QT CT +=

Cycle time at stepCycle time at step j j on equipment typeon equipment type k k ==

Queue time + Standard cycle timeQueue time + Standard cycle time

Standard cycle time is time from lot start to lotStandard cycle time is time from lot start to lot

complete.complete.

Queue time is time lot spends waiting to start.Queue time is time lot spends waiting to start.




Queuing Analysis (cont.)Queuing Analysis (cont.)

•• Basic formula for queue time per lot:Basic formula for queue time per lot:

– – LetLet j j index process step,index process step, k k index equipment typeindex equipment type

– – LetLet uu denote utilization of availability,denote utilization of availability, PT PT denotedenote

process time per lot or per batch, process time per lot or per batch, mm denote no. of denote no. of

qualified machines,qualified machines, A A denote availability,denote availability, caca denotedenote

arrival c.v.,arrival c.v., cece denote effective service time c.v.:denote effective service time c.v.:

⎟⎟ ⎠

⎞

⎜⎜⎝

⎛

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

−⎟⎟ ⎠

⎞

⎜⎜⎝

⎛ +

=

−+

k

k

k j

m

k k

jk A

PT

um

uceca

QT

j

)1(2

1)1(222





Key point: Wait time ~Key point: Wait time ~

{Variability} { } {Process time/Availability}{Variability} { } {Process time/Availability}

•• One can reduce cycle time if any of the above terms isOne can reduce cycle time if any of the above terms is

reducedreduced

( )( )um

um

−1




Queuing Analysis (cont.)Queuing Analysis (cont.){Variability}{Variability}

•• cece = effective service time c.v. (reflects machine= effective service time c.v. (reflects machine

down time)down time) – – LetLet cc00 denote intrinsic process time c.v.,denote intrinsic process time c.v., cr cr denote repair denote repair

time c.v.,time c.v., A A denote availability,denote availability, MTTR MTTR denote mean timedenote mean time

to repair,to repair, PT PT denote avg. process timedenote avg. process time

k

k k k k k

PT

MTTR A Acr cce )1()(1 22

0

2 −++=

Utilization should be set lower for machines with higherUtilization should be set lower for machines with highervariabilityvariability




Queuing Analysis (cont.)Queuing Analysis (cont.){Utilization}{Utilization}

•• System performance is very sensitive to high utilization levels.System performance is very sensitive to high utilization levels.

•• Balancing utilizationBalancing utilizationreduces wait time.reduces wait time.

•• Increasing theIncreasing the

number of qualifiednumber of qualifiedmachines reducesmachines reduces

wait time:wait time:

Wait Time vs. Utilization

01

2

3

4

5

6

7

8

9

10

0 . 0 5 0 .

1 0 .

1 5 0 . 2

0 . 2 5 0 .

3 0 .

3 5 0 . 4

0 . 4 5 0 .

5 0 . 5 5 0 .

6 0 . 6 5 0 .

7 0 . 7 5 0 .

8 0 . 8 5 0 .

9 0 . 9 5

Utilization

W a i t T i m e

Wait Time (1 machine)

Wait Time (2 machines)







General strategy:General strategy:

•• Compute entitlement cycle times for status quoCompute entitlement cycle times for status quo

•• Compute estimates of cycle time reduction fromCompute estimates of cycle time reduction from

implementing potential new qualifications, addition of implementing potential new qualifications, addition of

new machines, changes in recipes, assignment of new machines, changes in recipes, assignment of recipes to machines, etc.recipes to machines, etc.

•• Determine CT ROI per engineering hour or per unitDetermine CT ROI per engineering hour or per unit

capital expenditure, rank projects and implementcapital expenditure, rank projects and implement

accordinglyaccordingly




Extensions for special casesExtensions for special cases

•• Batch tools (e.g., diffusion furnaces)Batch tools (e.g., diffusion furnaces)

– – Queuing entities in this case are batch recipes rather Queuing entities in this case are batch recipes rather

than productthan product--steps (which share recipes)steps (which share recipes)

– – Extra wait time to build up batchExtra wait time to build up batch

jk jk jk jk SCT QT BT CT ++=

Cycle time for recipeCycle time for recipe j j on equipment typeon equipment type k k ==

Batching time + Queue time +Batching time + Queue time + Standard cycle timeStandard cycle time




Batch tools (cont.)Batch tools (cont.)

•• Basic formula for batching time:Basic formula for batching time:

– – LetLet j j index recipe,index recipe, k k index equipment type,index equipment type, ii index productindex product

– – LetLet bb jk jk denote avg. batch size for recipedenote avg. batch size for recipe j j on equipmenton equipment k k ,,

SSii denote total weekly lot starts rate of productdenote total weekly lot starts rate of product i,i, nn ji ji denotedenote

number of times recipenumber of times recipe j j occurs in the process flow of occurs in the process flow of product product ii

⎟⎟

⎟

⎠

⎞

⎜⎜

⎜

⎝

⎛

⎟⎟ ⎠

⎞⎜⎜⎝

⎛ −

= ∑∈ ),(

168

2

1

k ji

i ji

jk

jk Sn

b BT




Batch tools (cont.)Batch tools (cont.)•• Another key point:Another key point:

The batch size can be set either too big or too small. BestThe batch size can be set either too big or too small. Best

value depends on lot arrival rate and machine utilization:value depends on lot arrival rate and machine utilization:

Cycle time vs. Batch size for TEL_OXWETG

3.5

3.75

4

4.25

4.5

4.75

5

5.25

5.5

1.5 2 2.5 3 3.5 4 4.5 5 5.5

Avg. batch size (Lots)

A v

g . c y c l e t i m e ( h o u r

s )




Extensions (cont.)Extensions (cont.)

•• Machines with setups (e.g., implanters)Machines with setups (e.g., implanters)

– – Queuing entities in this case are setup batches rather Queuing entities in this case are setup batches rather

than lots (which share setups)than lots (which share setups)

– – Extra wait time for lot’s turn within the setup batchExtra wait time for lot’s turn within the setup batch

jk l jk jk SCT BT QT CT ++=

Cycle time at stepCycle time at step j j on equipment typeon equipment type k k in batchin batch l l ==

Queue time + Batch time + Standard cycle timeQueue time + Batch time + Standard cycle time




Setup machines (cont.)Setup machines (cont.)

•• Basic formula for waitBasic formula for wait--withinwithin-- batch time: batch time:

– – LetLet bbll denote avg. batch size for setup typedenote avg. batch size for setup type ll

– – LetLet PT PT ll denote the average process time per batchdenote the average process time per batch

ll

l

ll st PT

b

b BT +⎟⎟

⎠

⎞⎜⎜⎝

⎛ −=

2

1




Case-study in Entitlement

Cycle Time Planning




Introduction to the Fab

•• FabFab A had approx. $650M installed capital,A had approx. $650M installed capital,was fabricating approx. 15K 8was fabricating approx. 15K 8--inch siliconinch silicon

wafers per month in technologies rangingwafers per month in technologies rangingfrom 500nm down to 90nmfrom 500nm down to 90nm

•• Most volume was 150nm or 130nmMost volume was 150nm or 130nm




Introduction toIntroduction to FabFab (cont.)(cont.)

•• Wafer fabrication involved building up ~18 layers of Wafer fabrication involved building up ~18 layers of

circuitry on silicon wafers, ~ 500 total stepscircuitry on silicon wafers, ~ 500 total steps

•• Wafers moved from step to step in lots of 25Wafers moved from step to step in lots of 25

•• There were 66 equipment types involved, anywhereThere were 66 equipment types involved, anywherefrom 1 to 15 machines in each equipment typefrom 1 to 15 machines in each equipment type

•• “New” machines cost anywhere from $150K to $15M“New” machines cost anywhere from $150K to $15M




Management strategyManagement strategy•• Carry out queuing analysis to predict changes inCarry out queuing analysis to predict changes in

cycle time as a function of cycle time as a function of

– – product mix and volume product mix and volume

– – equipment set and machine qualificationsequipment set and machine qualifications

•• Analyze CT ROI for alternative machine andAnalyze CT ROI for alternative machine and

engineering investments (or engineering investments (or disdis--investments)investments)

•• Find the cheapest way to maintain good CTFind the cheapest way to maintain good CT performance performance




Input dataInput data

•• Arrival rate c.v. (Arrival rate c.v. (caca): no data, set equal to unity): no data, set equal to unity

•• Intrinsic service rate c.v. (Intrinsic service rate c.v. (cc00): no data, set equal to unity): no data, set equal to unity

•• Process timeProcess time PT PT andand SCT SCT : actual statistics for photo, IE stop: actual statistics for photo, IE stop--

watch standards for all other equipment typeswatch standards for all other equipment types

•• Actual data for Actual data for mm

•• uu computed fromcomputed from fabfab starts ratestarts rate andand PT PT

•• Actual statistics for Actual statistics for b, MTTRb, MTTR,, cr cr , , andand A A

,)1(2

1)1(222

⎟⎟ ⎠

⎞⎜⎜⎝

⎛

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

−⎟⎟

⎠

⎞

⎜⎜

⎝

⎛ +=

−+

k

k

k j

m

k k

jk A

PT

um

ucecaQT

j




ImplementationImplementation

•• The queuing models and heuristics wereThe queuing models and heuristics wereincorporated into Excel workbooksincorporated into Excel workbooks

– – Automated refresh of most input data fromAutomated refresh of most input data from fabfab

databasesdatabases – – Every process engineering dept. uses its queuingEvery process engineering dept. uses its queuing

workbooksworkbooks




Implementation and resultsImplementation and results•• Validation: theValidation: the fabfab--wide average cycle time predictedwide average cycle time predicted

by the model was 87% of actual by the model was 87% of actual

fabfab

--wide averagewide average

cycle timecycle time

– – The impact of lot and process holds (not modeled)The impact of lot and process holds (not modeled)

accounted for most of this gapaccounted for most of this gap

•• The model was used to plan a volume ramp fromThe model was used to plan a volume ramp from

3350 WSPW to 4900 WSPW, determining what tools3350 WSPW to 4900 WSPW, determining what tools

to buy and what photo qualifications work toto buy and what photo qualifications work tocompletecomplete




Algorithm for capacity planningAlgorithm for capacity planning•• Determine baseline cycle time (current volume andDetermine baseline cycle time (current volume and

mix)mix)

•• Determine cycle time for next volume/mixDetermine cycle time for next volume/mixincrement if no equipment additions are madeincrement if no equipment additions are made

•• Determine cycle time reduction individually for eachDetermine cycle time reduction individually for each

tool type if one new tool is addedtool type if one new tool is added

•• Divide this reduction by cost of that equipment toDivide this reduction by cost of that equipment to

establish a CT ROIestablish a CT ROI

•• Incrementally add equipment in order of decreasingIncrementally add equipment in order of decreasing

ROI until baseline CT is recoveredROI until baseline CT is recovered




ResultsResults

•• Ramp plan to increase wafer volume by 45%Ramp plan to increase wafer volume by 45%

involved only ~ $20M in noninvolved only ~ $20M in non-- photo capital and photo capital and

only ~ $20M in photo capital (compared to $650Monly ~ $20M in photo capital (compared to $650M

for existingfor existing fabfab), at the same time the mix was), at the same time the mix wasstrongly shifted to newer process technologiesstrongly shifted to newer process technologies

•• Cycle time performance was maintained duringCycle time performance was maintained during

rampramp




Results (cont.)Results (cont.)

•• CaseCase--study company uses TSMC foundry as a back study company uses TSMC foundry as a back --upup

production source production source

•• For 150nm devices, TSMC charged $1600 per wafer.For 150nm devices, TSMC charged $1600 per wafer.

Company’s wafer cost is $800, i.e.,Company’s wafer cost is $800, i.e., 50% less!50% less!

•• TSMC’sTSMC’s cycle time is 2.3 DPML (18 layers);cycle time is 2.3 DPML (18 layers);

Company’s cycle time was 1.6 DPML (was 2.3 DPMLCompany’s cycle time was 1.6 DPML (was 2.3 DPML

before project started), i.e., before project started), i.e., 30% less!30% less!

d h




Proposed approach to processProposed approach to process

engineeringengineering

•• Every proposal for an engineering project mustEvery proposal for an engineering project must

quantify changes inquantify changes in fabfab throughput, yield andthroughput, yield andcycle timecycle time

•• These changes areThese changes are dollarizeddollarized and the trueand the true

economic value of the project is demonstratedeconomic value of the project is demonstrated

•• Engineering is rewarded for improving entitlementEngineering is rewarded for improving entitlement

cycle time as well as for yield or throughputcycle time as well as for yield or throughput

improvementimprovement




ConclusionsConclusions

•• Cycle time has a large economic impact thatCycle time has a large economic impact thatcan and should be measuredcan and should be measured

•• Cycle time can and should be managed withCycle time can and should be managed with

as much discipline and sophistication as hasas much discipline and sophistication as has been brought to yield management been brought to yield management

– – Effective spreadsheet tools have beenEffective spreadsheet tools have been

developed and demonstrated in actual practicedeveloped and demonstrated in actual practice




Textbook reference onTextbook reference onQueuing AnalysisQueuing Analysis

•• Factory Physics, Factory Physics, by by HoppHopp and Spearman,and Spearman,McGrawMcGraw--Hill, ISBN 0Hill, ISBN 0--256256--2479524795--11

ReferencesReferences Economics of SpeedEconomics of Speed




ReferencesReferences – – Economics of SpeedEconomics of Speed

•• Report CSMReport CSM--47, “Understanding47, “Understanding FabFab

Economics,” may be ordered from the CSMEconomics,” may be ordered from the CSM

website:website: http://http://euler.berkeley.edu/esrc/csmeuler.berkeley.edu/esrc/csm

•• The CSMThe CSM FabFab Economics Workbook can beEconomics Workbook can be

downloaded at no charge from the web sitedownloaded at no charge from the web site

•• You can eYou can e--mail questions to me atmail questions to me [email protected]@ieor.berkeley.edu

economics of speed

Documents