Transcript Wafer Starts, Cycle Time, and Tools a complicated

The Ongoing Challenge - Tutorial
The Illusion Of Capacity
Incorporating the Complexity Of FAB Capacity
(tool deployment, routes, & operating curve)
into Central Planning (with fixed linear
representation of capacity and cycle time)
for Demand-Supply Networks for the production of
semiconductor based packaged goods
with substantial non-FAB complexity
Basics
part 1 of 4 that has a part 5
Dr. Ken Fordyce & John Fournier, IBM
Prof. John Milne, Clarkson University (IBM retired) & Dr. Harpal Singh, CEO Arkieva
* Dr. Horst Zisgen, IBM, Rich Burda IBM,
Gary Sullivan (IBM retired), Peter Lyon (IBM retired),
Prof Chi-Tai Wang NCU (Taiwan) (IBM 1998-2009)
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
1
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
2
Theme for This Afternoon’s
Feature Presentation is
The Hunt for CAPAVAIL
(capacity available)
and CAPREQ (capacity required)
in central planning engines
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
4
Answer Question
IBM has
>> PROFIT (CPE) (Edelman, Wagner) and
>> EPOS (Wagner, MASM)
why?
End to end demand supply network plan
300mm EFK FAB planning
Loosely coupled with wafer starts and cycle time
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
5
“Creation of the Plan is simply the start of the planning
and commit process, not the end point. The Plan is
information for planners, executives, & finance.
Additionally it helps set dispatch scheduling priorities
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
6
Rule 001 for capacity hunters
• All models are wrong, some models are useful
• All models are approximations that balance
– “ease of use”
– with accuracy.
• This balance changes over time in both
directions
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
9
Outline (1 of 3)
• Overview of the Demand Supply Network for the
production of semiconductor based package goods
– Warring factions
• Decision Tiers
– Aggregate FAB Planning
– Central Planning
• Two major challenges
– Planned lack of tool uniformity
– Inherent variability
11
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Outline (2 of 3)
• Basics of Aggregate Factory Planning
– Can this wafer start profile be supported
– Near Term Deployment
– WIP Projection
• Basics of Central Planning
– Basic Functions
– Historical emphasis on non-FAB complexity
• Alternate BOM for example
– Handle FAB Capacity with limits stated as wafer starts
• Wafer start equivalents evolved to nested wafer starts (date effective)
• Fixed, but date effective cycle times
– Second look at capacity (CAPREQ and CAPAVAIL)
• Linear methods in central planning engines
• FAB complexity creates miss match
12
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Outline (3 of 3)
• Operating Curve and Cycle time Tax
• Creating CPE type capacity from routes and
consumptions of tools
– The complexity of deployment
• Illustrating complexity of interactions and Illusion of
Capacity
• Central Planning Engine Challenges
• Robust and detailed estimate of what a FAB can do
under what conditions
– Clearing Functions
– WIP Simulation
– EPOS
• Dynamic Network of Planning Tools - challenge
13
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Overview of
Demand Supply Network
for the production of
semiconductor based package goods
Warring factions
14
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Simple view demand supply network
for production of semiconductor based packaged goods
Wafer_2
cycle time = 60 days; start of BOM
chain; one wafer makes 200 devices
Device_2
cycle time = 3 days; requires 1/200 unit of
Wafer_2 to build
Module_2
cycle time = 8 days; requires 1 unit of
Device_2 to build
Card_2
cycle time = 4 days; requires 2 units of
Module_2 to build; end of BOM chain
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Simple view demand supply network
for production of semiconductor based packaged goods
Wafer_2
cycle time = 60 days; start of BOM chain; one wafer
makes 200 devices
Device_2
cycle time = 3 days; requires 1/200 unit of
Wafer_2 to build
Module_2
cycle time = 8 days; requires 1
unit of Device_2 to build
Card_2
cycle time = 4 days; requires 2 units of
Module_2 to build; end of BOM chain
16
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Finished Mod. X
Finished Mod. Y
Sort A
Sort B
60%
40%
30%
Finished Mod. Z
Finished Mod. W
Sort C
50%
70%
30%
20%
Module 1
Module 2
Module 3
Device (Fast)
Device (Medium)
Device (Slow)
60%
10%
30%
POST
FAB
Total
Journey
Device (Untested)
Wafer BEOL
other BEOL wafers
Wafer FEOL
other FEOL wafers
= BOM
= Alternate BOM
= Binning
= Substitution
FAB
Raw Wafer
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
17
MUV
MUV
MUV
Implant
Implant
Implant
Strip
Strip
Strip
Wets
FAB
Wets
Wets
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
MUV
Implant
Strip
Wets
Oper A-1
Tools 1, 2
Prod A
MUV
Implant
Strip
Wets
Oper A-2
Tools 2, 3
MUV
Implant
Strip
Wets
Oper A-3
Tools 3
MUV
3 passes
Implant
Strip
Wets
Oper B-1
Tools 1, 2
Prod B
MUV
Oper B-2
Tools 2
Implant
Strip
Wets
21
2 passes
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Overview of the Demand-Supply Network
• Organizations can be viewed as an ongoing
sequence of loosely coupled activities where
current and future assets are matched with
current and future demand across the demandsupply network.
• These planning, scheduling, and dispatch
decisions across a firm’s demand-supply
network are best viewed as a series of
information flows and decision points organized
in a decision hierarchy or tiers and further
classified by the type of supply chain activity
creating a grid for classification.
26
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Central
Planning
At best loosely and
narrowly linked
Enterprise Wide. global view - central
planning
Decision Tiers FAB
is an entity
FAB
Planning
Enterprise Subunits (manufacturing, distribution,
Different
retail) factory
planning Groups
Different
methods
Capacity
(tools summary
and manpower)
analysis to gauge
impact
of changing
product mix,
identify
challenges,
for
capacity,
routes,
& lot
priorities
review and modify deployment decisions and
> create demand statement (current orders, Focus on tools, starts, and wafer output
manufacturing engineering requirements, and create
forecasts)
capacity constraint information for central
Focus
post
FABWIP, BOM,business policy routes,
> capture
capacity,
reentrant
flow,
Deployment,
priorities
planning
and WIP
status.
Monitorlot
tool
level
> central planning engine to match assets with
Operating
curve,
a
bit
of
headache
performance and take appropriate actions. Establish
demand
rules and metrics to set global lot importance > estimate supply line linked to demand, early
example, how many priority classes, algorithm to set
warning, production requirements, chase
lot importance within a class, limits on number of
situations
expedites.
thatEnterprise
makes wide
Wafers
central planning
“I justweekly/biweeky/monthly
want my wafers”
Tier 2
Tactical
Challenge
Enterprise Wide central planning reduced
focus / what if
> what if commit on large orders
> what if on major asset change
> status of key WIP and actions to take if
needed
> cross factory signals
Provide information to central plan and daily
factory adjustments
> establish target outs, due dates on lots
> maintenance priorities
> short term changes in deployment
> review key lot status and change priority (up or
down) based on progress (either manually or
dynamically)
> one time changes in lot importance guidance
> establish mfg lot vs development lot preference
> revised projected outs for enterprise planning
Better linkage?
How much complexity is needed?
How much can be absorbed?
Tier 3
Operational
"daily"
27
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Two Major Challenges
From FABS
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Focus Two Major Challenges
Deployment
• Planned Lack of Uniformity - not all tools for a manufacturing
process have identical profiles
(alternative machines)
– What operations they handle
– Their production rate
– How does this impact capacity
available
Of course Reentrant flow, single wafer, batching,
time windows,
long raw process
• Process
Inherent Variability
- in the manufacturing
line forcestimes
us to plan for
unusedChanging
capacity (tools
ready to/go,
but patterns
idle due to lack of WIP) to
demand
start
OP Curve
meet the lead time or cycle time objective - Operating curve
– trade-off between utilization and cycle time
– Trade-off between output and cycle time
– Trade-off between wafer starts and cycle time
– Trade-off effective capacity
available and cycle time
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Deployment
FAB Capacity includes a set of partial matches between individual
resources (tools) and manufacturing activities (operations)
• Deployment decisions that restrict which manufacturing activities a
tool is permitted to process
• Manufacturing engineering requirements that limit actual deployment
• Different inherent rates of production (PPH) between tools that
service the same manufacturing activity
• Variation in rates day to day for the same tool depending on floor
opportunities for batching, trains (operational chains), parallel
factors, etc
• Variation in the percentage and distribution of tool availability
More on this later
31
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Deployment Ingredient # 1
Which Tools Can Handle Which Operations
Table 5.1: Deployment Information for PSO Group
Tool A
oper001
oper002
oper003
oper004
oper005
oper006
oper007
number opers
tool covers
1
1
0
0
0
1
1
4
Tool B
1
1
1
0
1
0
0
Tool C
4
3
no tools covering
oper
0
0
1
1
1
0
0
2
2
2
1
2
1
1
1 – oper/tool link active
0 – not allowed
32
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Deployment Ingredient # 2
RPT per widget per time unit
for Tool / Operation Pairing
Table 5.3: RPT information
Tool A
oper001
oper002
oper003
oper004
oper005
oper006
oper007
4
15
10
10
5
8
10
Tool B
20
20
15
9
5
10
10
Tool C
5
6
8
20
5
10
10
33
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Operating Curve
• Trade off between
– tool utilization and lead time / cycle time or
– Output (starts) and cycle time
– Effective capacity available and cycle time
• Move along the curve
– Pick a cycle time, get a tool utilization / capacity available
– Pick a tool utilization (capacity) / get a cycle time
• Shift the curve down and right
– Less variability, lower cycle time for the same tool utilization
• Cycle time is often measured as a multiplier of raw
process time (RPT) called cycle time multiplier (CTM)
– Some times called XF (x factor – for multiplier)
• Cycle time = CTM x RPT
More on this later
34
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Required
idle time
without
Operating
Curve
Basics WIP
MM1 comparison full MM1 and Squeezed
Can be viewed as a Tax
to Achieve a certain cycle time
Xfactor calculated for traditional MM1
24.00
xfactor from Sullivan - Fordyce 10% Sqeezed
xfactor from Sullivan-Fordyce 20% Squeezed
22.00
20.00
18.00
16.00
xfactor
14.00
12.00
10.00
08.00
06.00
04.00
To maintain the same cycle time
But increase tool utilization
For Blue Operating Curve
If you
are willing
to accept
Old aconcept
within
industry
Requires
curve
to achieve
CTM “shifting”
of 5.00
CTM
of 6.0
Thinking
how
this
relates
to
clearing
function
Requires
accepting
Dow and to the
right
Then you only
Tool utilization of 80%
Have to accept
17%tax
unused
“cheating” the
mancapacity
Which Means you plan to have
20% of your capacity
to SIT IDLE due to lack of WIP
02.00
00.00
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
Reduce
0.70
0.75 0.80 0.85 0.90
variability
0.95
1.00
machine utilization
35
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of
FAB Planning
36
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Outline
• Overview of the Demand Supply Network for the
production of semiconductor based package goods
– Warring factions
• Decision Tiers
– Aggregate FAB Planning
– Central Planning
• Two major challenges
– Planned lack of tool uniformity
– Inherent variability
• Basics of Aggregate Factory Planning
– Can this wafer start profile be supported
– Near Term Deployment
– WIP Projection
37
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of FAB Planning
• Focus on matching assets with demand
• Three major classes
– Aggregate FAB planning
– Deployment or near term tool planning
– WIP Projection
• Forward flow of starts dominate method as opposed to
pulling to meet demand
• Wide variation in methods
• Wide variation in how much FAB complexity of
– deployment
– operating curve is handled
38
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of Aggregate FAB Planning
39
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of Aggregate FAB Planning
•
•
•
•
focused on assessing the ability of the factory to meet certain demand
looking to identify “broken” (insufficient capacity to meet demand) toolsets
and creating the capacity inputs required by central planning.
Demand is stated as a starts profile and a lead (cycle) time commit for each
part.
Various levels of sophistication in handling operating curve, deployment,
mix variability, etc
The key challenges for the factory planner are:
– Determine if the workload can be allocated across the tools in such a
way that all of the workload can be allocate without violating capacity
constraints
– If insufficient capacity exits
• find the optimal mix of workload that can be met without violating
capacity constraints
• find the optimal allocation that either minimizes additional capacity
needed incorporating some type of fair share of pain
• Except for advanced methods tough to handle cycle
time output trade-off; even with “methods” culturally
upsetting
40
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of Central Planning
for the entire demand supply network
(supply chain)
for the production of semiconductor
based packaged goods
43
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Outline
•
Overview of the Demand Supply Network for the production of semiconductor based package
goods
–
•
Decision Tiers
–
–
•
Planned lack of tool uniformity
Inherent variability
Basics of Aggregate Factory Planning
–
–
–
•
Aggregate FAB Planning
Central Planning
Two major challenges
–
–
•
Warring factions
Can this wafer start profile be supported
Near Term Deployment
WIP Projection
Basics of Central Planning
–
–
Basic Functions
Historical emphasis on non-FAB complexity
•
–
Handle FAB Capacity with limits stated as wafer starts
•
–
Alternate BOM for example
Wafer start equivalents evolved to nested wafer starts
Second look at capacity (CAPREQ and CAPAVAIL)
•
•
Linear methods in central planning engines
FAB complexity creates miss match
44
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Demand
Statement
Central
Planning
Model has key
relationships
Reports on at risk
orders, capacity
utilization, projected
supply
Information from Factory –
projected completion of WIP,
capacity statement, lead times
Enterprise Wide Central Planmatch assets with demand
Signals to
factories
Signals to
available to
promise (ATP)
45
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Demand
Statement
Information from Factory –
projected completion of WIP,
capacity statement, lead times
Information from FAB
Enterprise Wide Central Plan1. projectedmatch
WIP
completion
assets
with demand
2. capacity statement
3. lead or cycle
times
Signals to
Signals to
Central
Planning
Model has key
relationships
Reports on at risk
orders, capacity
utilization, projected
supply
factories
available to
promise (ATP)
46
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of Enterprise Wide Central Planning
1. Create a demand statement
2. Capture the flow of materials in the demand supply network
3. Gather and collect key information from the factory
1. Project the completion of WIP to a decision point (often completion of the part).
2. a statement of capacity required and available
3. a statement of lead time or cycle time to complete a new start
4. Create a model captures key relationships (Central Planning Engine – CPE)
5. Create an enterprise wide central plan by matching current and future
assets with current and future demand using the CPE to create a future
projected state of the enterprise and the ability to soft peg the current
position of the enterprise to the projected future position. Information from
the model includes
1.
2.
3.
4.
5.
a projected supply linked with exit demand
identification of at risk orders either to a commit date or request date
Synchronization signals across the enterprise
Capacity utilization levels
Ability to traceproduction & distribution activity that supports meeting a demand
47
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Basics of Central Planning Engine (CPE)
• Core task is deploy modeling methods to match assets
with demand across an enterprise to create a projected
supply linked with demand and synchronization signals.
• CPE has four core components:
– represent the (potential) material flows in production, business
policies, constraints, demand priorities, current locations of
asset, etc., and relate all this information to exit demand.
– capture asset quantities and parameters (cycle times, yields,
binning percentages, etc.).
– search and generate a supply chain plan, relate the outcome to
demand, and modify the plan to improve the match.
– display and explain the results.
48
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Emphasis on Optimal
Allocation of Supply to Demand
50
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Allocate supply
Of devices to
Modules 1 & 2
Device_12
Day
Sup
00
10
02
30
10
20
Module_1
CT = 10 days
Supply Amt
Day
Amt
00
?
02
?
10
?
Dem
Due day
Amt
C
D
10
12
10
15
**Device Supply
Supply
Amt point
is starting
Day
Amt
00
?
02
?
10
?
Module_2
CT = 4 days
Dem
Due day
Amt
A
05
8
51
06
2
Fordyce, Fournier, Milne, Singh B
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Table 4-1: Results of Solution 1
Commitment
Demand
ID
Type
date Quantity
A
Module_2 05
8
B
Module_2 06
2
C
Module_1 10
10
D
Module_1 12
15
actual delivery
date quantity
04
8
04
2
12
10
12
15
Delta
schedule
1
2
-2
0
Which Solution is better?
Table 4-2: Results of Solution 2
It depends
on demand
priorities
commitment
actual delivery delta
Demand
ID
A
B
C
D
Type
Module_2
Module_2
Module_1
Module_1
date
05
06
10
12
quantity
8
2
10
15
date quantity
06
8
06
2
10
10
12
15
schedule
-1
0
0
0
52
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Key Tasks
• Allocation of perishable (capacity) and non perishable assets
(inventory) to best meet prioritized demand
• Handle binning and down grade substitution
• Complex binning, general substitution, and alternative BOM
• Lot sizing
• Sourcing
?? Cycle time – output trade-off
• Fair share
• Customer commit and request date
• Min starts
• Date effective parameters
• demand perishability, squaring sets, soft capacity constraints,
alternative capacity, pre-emptive versus weighted priorities, splitting
demand to match partial delays in supply, stability, express lots,
delay assembly to test, dispatch lots
• foundry contracts
?? Complexity of FAB tools
53
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Allocating Supply to Demand
with
Complex Alternative Paths (BOM)
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Complex binning, general substitution, and alternative BOM
Goal is to make best use of existing WIP and capacity
To best meet demand and minimize new starts
untested device
WIP = 40
on Day 2
20%
40%
40%
Device_8A
inventory = 20
P0
Device_8B
inventory = 0
P2
P1
Module_8
demand = 20
priority = 8
Module_9
demand = 20
priority = 1
substitution
Device_8C
inventory = 0
P2’
substitution can be viewed as
an alternative process P2’
72
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
This Solution Meets all demands
And does not require “new starts”
untested device
WIP = 40
on Day 2
8
20%
40%
8
Device_8B is .40 x 40 = 16
Device_8C is .40 x 40 = 16
P2
Device_8B
inventory = 0
40%
Module_8
demand = 20
priority = 8
P1
16
proj. supply of device
(future inventory)
Device_8A is .20 x 40 =
P0
Device_8A
inventory = 20
4
20
Module_9
demand = 20
priority = 1
substitution
16
Device_8C
inventory = 0
P2’
substitution can be viewed as
an alternative process P2’
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Modules
and alternative
BOM
Wafer_2
cycle time = 30 days, start of BOM
chain, one wafer makes 200 devices
30%
Simple View
Device_2C
of Wafers
25%
45%
Device_2A
Device_2B
30% of Wafer_2 sorts
to Device_2A
45% of Wafer_2 sorts
to Device_2B
P_1
25% of Wafer_2 sorts to
Device_2C
P_2
P_1
Module_2
Module_2
Module_A
cycle time = 6 days, made
via process P_1, consumes
1 unit of Device_2A
cycle time = 8 days, made
via process P_2, consumes 1
unit of Device_2B
cycle time = 9 days, made
via process P_3, consumes 1
unit of Device_2C
1
Alternative processes (methods) to make Module_2,
i.e., Module_2 stocks from three production paths
Module_2
10% of Module_A
becomes Module_2
10%
90%
Module_AA
Location: VEND001
Location: VEND002
Card_2
Card_2
cycle time = 2 days,
made at vendor VEND001,
requires 2 units of Module_2
cycle time = 4 days,
made at vendor VEND002,
requires 2 units2of Module_2
90% of Module_A
Complex
becomes Module_AA
View of Modules
76
Fordyce,
Fournier, Milne, Singh
Alternative vendors to make
Card_2,
Illusionstocks
of FAB
Capacity
in Central Planning – hunt for CAPAVAIL
i.e., Card_2
from
two vendors
Historically
Central Planning Engines
Have focused on
non-FAB challenges
77
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Historically
Central Planning Engines
Handle FAB Capacity
with Nestedstated
Wafer as
Starts
(Exits)
CAPAVAIL
maximum
Separate
from cycle
time per day
Number of
wafer starts
allowed
For various groupings of parts
78
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
nested Wafer Start (exit) limits
Logical evolution from
Wafer start Equivalents
79
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Review Wafer Start Equivalents
80
Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
History
• Historically FABs have stated capacity in wafer starts and “traded”
starts using wafer start equivalents (ratios) to limit daily wafer starts
into manufacturing
• For example if my FAB produces three parts and the pinch point
toolset is photo, the pass count numbers might be
part
part001
part002
part003
# passes for photo
10
15
20
• In this case each Part 003 is “worth” two Part 001; two Part 002 are
Wafer Start Equivalent Ratios
worth “three” Part 001, etc
part001
part002
part003
• All of the capacity elements ofpart
the FAB are “summarized”
in one
# passes
10
15
20
single statement of capacitypart001
that is completely
removed
from
actual
10
1:1
3:2
2:1
resources (capacity) consumed
part002
15
2:3
1:1
4:3
part003
20
1:2
3:4
1:1
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Wafer Start Equivalents
logical evolution
to nested Wafer Start Limits
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
History – evolved to nested set of limits
Table 14: Stating FAB Capacity Limits as a Nested Set of Start Limits
row number
Group
Time frame 1 Time frame 2
Time frame 3
001
Wiring Group 1
600
675
675
002
Technology Group A
400
425
450
003
Technology Group B
300
325
350
004
Option set W
100
100
100
005
Option set X
210
300
300
006
Wiring Group 2
500
525
550
007
Technology Group D
350
350
375
008
Technology Group E
250
275
275
009
Option set Y
100
100
100
010
Option set Z
200
200
200
011
•
Total Fab Limit
1000
1100
1150
The overall FAB limit is stated in terms of wafers per day and that each
product is mapped to one or more limit. The current methodology allows
the CPE to start up to, but not over any limit to which products are mapped.
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
History – evolved to nested set of limits
Table 14: Stating FAB Capacity Limits as a Nested Set of Start Limits
row number
Group
Time frame 1 Time frame 2
Time frame 3
001
Wiring Group 1
600
675
675
340(=600-260)
available
002
Technology Group A
400
425
450
340(=min(340,400)
available
003
Technology
300
350
260(180+60+20)
allocated Group B20 selected
40325
available (300-260)
004
Option set W
100
100
100
60 selected
005
Option set X
210
300
180 300
selected
006
Wiring Group 2
500
525
550
007
Technology Group D
350
350
375
008
Technology Group E
250
275
275
009
Option set Y
100
100
100
010
Option set Z
200
200
200
011
•
Total Fab Limit
1000
1100
1150
The overall FAB limit is stated in terms of wafers per day and that each
product is mapped to one or more limit. The current methodology allows
the CPE to start up to, but not over any limit to which products are mapped.
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Second Look
at capacity (resource) allocation
in central planning engines (CPE)
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
IBM Systems and Technology Group: Advanced Supply Chain Planning
How Do I Best Allocate a Perishable Asset
Module 1
Amt Resource 12
Day
Device 12
Day
Sup
00
40
01
??
02
??
03
??
?
CT = 1day
resource utilization = 2
Demand
Due day
Amount
C
02
10
D
04
15
Amt Resource 12
Day
Amt Res12 Avail
Day
Amt
AVL
01
30
02
30
03
60
Amt
01
??
02
??
03
??
?
Module 2
CT = 4 days
resource utilization = 3
Demand
Due day
Amount
A
02
08
B
03
19
Module 1 and Module 2 are both made from Device 12 and we have 40 units in stock. Each module
consumes 1 device. The cycle time is 1 day for each Module. Module 1 needs 2 units of the
Resource 12 to make a module. Module requires 3 units of Resource 12 to make a module. The
demand for each module is posted.
?? How do I best allocate Resource12 to Modules 1 and 2?
26
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Core Steps of Resource Allocation in Central Planning
• linking a manufacturing activity (decision node)
to one more resources
• CAPREQ - establishing a consumption rate for
each unit of production by that manufacturing
activity for the selected resource(s)
• CAPAVAIL - providing the total available
capacity for each resource.
• connecting manufacturing releases (starts) to
resource consumption with a linear relationship
– No batching, parallel factor, etc
– No explicit ability to trade an increase in cycle time for
an increase in output
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Simple Example of Central Planning
Our factory makes two parts Tiger and Lion.
The two decision variables are:
 XL is the number lion starts per day
 XT is the number of tiger starts per day
The profit per unit of production for Tiger is 5 and 7 for Lion
Capacity Consumed (required)
 For each unit of production for Tiger consumes
o 10 units of resource A and
o 08 units of resource B
 For each unit of production Lion consumes
o 12 units of resource A and
o 05 units resource B.
Capacity Available
The amount of capacity available daily
 for RES A is 194
 for RES B is 100
Minimum Demand (Min Starts)
The minimum number of starts
 Tiger is 5 and
 Lion is 7.
The equations are
Maximize
5XT + 7 XL
subject to
10XT + 12 XL ≤ 194
08XT + 05 XL ≤ 100
XT ≥ 5
XT ≥ 7
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Simple Example of Central Planning
Capacity Consumed (required)
 Capacity
For each Available
unit of production for Tiger consumes
Theoamount
of capacity
available
daily
10 units
of resource
A and
 for
RES
A is of
194
o 08
units
resource B
foreach
RESunit
B is of
100production Lion consumes
 For
o 12 units of resource A and
o 05 units resource B.
Magically
Capacity consumed
(CAPREQ)
Is known
Magically
Capacity Available
(CAPAVAIL)
Is known
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Estimating
CAPREQ & CAPAVAIL for FABS
in central planning models
Present Real Challenges
wafer starts may look better after this review
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL
Focus Two Major Challenges
Deployment
• Planned Lack of Uniformity - not all tools for a manufacturing
process have identical profiles
(alternative machines)
– What operations they handle
– Their production rate
– How does this impact capacity
available
• Inherent Variability - in the manufacturing line forces us to plan for
unused capacity (tools ready to go, but idle due to lack of WIP) to
meet the lead time or cycle time objective - Operating curve
OP Curve
– trade-off between utilization and cycle time
– Trade-off between output and cycle time
– Trade-off between wafer starts and cycle time
– Trade-off effective capacity
available and cycle time
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Fordyce, Fournier, Milne, Singh
Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL