The Ongoing Challenge - Tutorial The Illusion Of Capacity

Fordyce, Fournier, Milne, SinghIllusion of FAB Capacity in Central Planning – hunt for CAPAVAIL

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The Ongoing Challenge - Tutorial

The Illusion Of Capacity

* Dr. Horst Zisgen, IBM, Rich Burda IBM, Gary Sullivan (IBM retired), Peter Lyon (IBM retired), Prof Chi-Tai Wang NCU (Taiwan) (IBM 1998-2009)

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, IBMProf. John Milne, Clarkson University (IBM retired) & Dr. Harpal Singh, CEO Arkieva


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Theme for This Afternoon’s Feature Presentation is

The Hunt for CAPAVAIL(capacity available)

and CAPREQ (capacity required)

in central planning engines


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IBM has >> PROFIT (CPE) (Edelman, Wagner) and >> EPOS (Wagner, MASM) why?

Answer Question

End to end demand supply network plan300mm EFK FAB planning

Loosely coupled with wafer starts and cycle time


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“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


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• 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

Rule 001 for capacity hunters


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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


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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


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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


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Overview of Demand Supply Network

for the production of semiconductor based package goods

Warring factions


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Card_2cycle time = 4 days; requires 2 units of Module_2 to build; end of BOM chain

Module_2cycle time = 8 days; requires 1 unit of

Device_2 to build

Device_2cycle time = 3 days; requires 1/200 unit of

Wafer_2 to build

Wafer_2cycle time = 60 days; start of BOM chain; one wafer makes 200 devices

Simple view demand supply networkfor production of semiconductor based packaged goods


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Card_2cycle time = 4 days; requires 2 units of Module_2 to build; end of BOM chain

Module_2cycle time = 8 days; requires 1

unit of Device_2 to build

Device_2cycle time = 3 days; requires 1/200 unit of

Wafer_2 to build

Wafer_2cycle time = 60 days; start of BOM chain; one wafer

makes 200 devices

Simple view demand supply networkfor production of semiconductor based packaged goods


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= BOM= Alternate BOM

= Binning

= Substitution

Finished Mod. X Finished Mod. Y Finished Mod. Z Finished Mod. W

Sort A

Device (Fast)

Module 1

Sort B Sort C

Module 2 Module 3

Device (Medium) Device (Slow)

Device (Untested)

Wafer BEOL

Wafer FEOL

Raw Wafer

other BEOL wafers

other FEOL wafers

60% 40% 30%

60%

20% 50% 70%

30%

10% 30%

Total Journey

FAB

POST FAB


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MUV Implant Strip Wets



FAB


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Prod A


MUV Implant Strip WetsProd B

Oper A-1Tools 1, 2

Oper B-1Tools 1, 2

Oper A-2Tools 2, 3

Oper A-3Tools 3

Oper B-2Tools 2

3 passes

2 passes


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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 demand-supply 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.


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Enterprise Wide. global view - central planning

Enterprise Subunits (manufacturing, distribution, retail) factory planning

Tier 2 Tactical

Enterprise wide central planning weekly/biweeky/monthly> create demand statement (current orders, forecasts)> capture capacity, WIP, BOM,business policy> central planning engine to match assets with demand> estimate supply line linked to demand, early warning, production requirements, chase situations

Capacity (tools and manpower) analysis to gauge impact of changing product mix, identify challenges, review and modify deployment decisions and manufacturing engineering requirements, and create capacity constraint information for central planning and WIP status. Monitor tool level performance and take appropriate actions. Establish rules and metrics to set global lot importance - example, how many priority classes, algorithm to set lot importance within a class, limits on number of expedites.

Tier 3 Operational"daily"

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

Decision Tiers

Central Planning

FAB Planning

FAB is an entity that makes Wafers

“I just want my wafers”

Focus post FAB

Different GroupsDifferent summary methods

for capacity, routes, & lot prioritiesFocus on tools, starts, and wafer output

routes, reentrant flow, Deployment, lot prioritiesOperating curve, a bit of headache

Challenge

Better linkage?How much complexity is needed?

How much can be absorbed?

At best loosely and narrowly linked


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Two Major ChallengesFrom FABS


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Focus Two Major Challenges

• Planned Lack of Uniformity - not all tools for a manufacturing process have identical profiles– 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 – 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

Deployment(alternative machines)

OP Curve

Of course Reentrant flow, single wafer, batching, Process time windows, long raw process times

Changing demand / start patterns


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DeploymentFAB 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


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Tool A Tool B Tool Cno tools covering

oper

oper001 1 1 0 2

oper002 1 1 0 2

oper003 0 1 1 2

oper004 0 0 1 1

oper005 0 1 1 2

oper006 1 0 0 1

oper007 1 0 0 1

number opers tool covers 4 4 3

Table 5.1: Deployment Information for PSO Group

Deployment Ingredient # 1Which Tools Can Handle Which Operations

1 – oper/tool link active0 – not allowed


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Tool A Tool B Tool Coper001 4 20 5oper002 15 20 6oper003 10 15 8oper004 10 9 20oper005 5 5 5oper006 8 10 10oper007 10 10 10

Table 5.3: RPT information

Deployment Ingredient # 2RPT per widget per time unitfor Tool / Operation Pairing


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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


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MM1 comparison full MM1 and Squeezed

00.00

02.00

04.00

06.00

08.00

10.00

12.00

14.00

16.00

18.00

20.00

22.00

24.00

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 0.70 0.75 0.80 0.85 0.90 0.95 1.00

machine utilization

xfac

tor

Xfactor calculated for traditional MM1 xfactor from Sullivan - Fordyce 10% Sqeezed xfactor from Sullivan-Fordyce 20% Squeezed

Operating Curve Basics

For Blue Operating Curveto achieve a CTM of 5.00

Requires acceptingTool utilization of 80%

Which Means you plan to have20% of your capacity

to SIT IDLE due to lack of WIP

If you are willing to accept CTM of 6.0

Then you only Have to accept

17% unused capacity

Required idle time without WIPCan be viewed as a Tax

to Achieve a certain cycle time

To maintain the same cycle timeBut increase tool utilizationRequires “shifting” curve

Dow and to the right

“cheating” the tax man

Reducevariability

Old concept within industryThinking how this relates to clearing function


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Basics of FAB Planning


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Outline • Overview of the Demand Supply Network for the

production of semiconductor based package goods– Warring factions





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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


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Basics of Aggregate FAB Planning


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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


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Basics of Central Planningfor the entire demand supply network

(supply chain)for the production of semiconductor

based packaged goods


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Outline • Overview of the Demand Supply Network for the production of semiconductor based package

goods– Warring factions




• 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– Second look at capacity (CAPREQ and CAPAVAIL)

• Linear methods in central planning engines• FAB complexity creates miss match


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Demand Statement

Information from Factory – projected completion of WIP,

capacity statement, lead times

Enterprise Wide Central Plan- match assets with demand

Reports on at risk orders, capacity

utilization, projected supply

Signals to factories

Signals to available to

promise (ATP)

Central Planning

Model has key

relationships


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Demand Statement

Information from Factory – projected completion of WIP,

capacity statement, lead times

Enterprise Wide Central Plan- match assets with demand

Reports on at risk orders, capacity

utilization, projected supply

Signals to factories

Signals to available to

promise (ATP)

Central Planning

Model has key

relationships

Information from FAB1. projected WIP completion2. capacity statement3. lead or cycle times


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Basics of Enterprise Wide Central Planning

1. Create a demand statement 2. Capture the flow of materials in the demand supply network3. 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 available3. 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. a projected supply linked with exit demand2. identification of at risk orders either to a commit date or request date3. Synchronization signals across the enterprise4. Capacity utilization levels 5. Ability to traceproduction & distribution activity that supports meeting a demand


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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.


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Emphasis on OptimalAllocation of Supply to Demand


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Device_12

2010

3002

1000

SupDay

Module_2CT = 4 days

206B

805A

AmtDue dayDem

Module_1CT = 10 days

1512D

1010C

AmtDue dayDemSupply Amt

?10

?02

?00

AmtDay

Supply Amt

?10

?02

?00

AmtDay

Allocate supplyOf devices toModules 1 & 2

**Device Supplyis starting point


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Table 4-1: Results of Solution 1 Commitment actual delivery Demand

ID Type date Quantity date quantity Delta schedule

A Module_2 05 8 04 8 1 B Module_2 06 2 04 2 2 C Module_1 10 10 12 10 -2 D Module_1 12 15 12 15 0

Table 4-2: Results of Solution 2

commitment actual delivery Demand ID Type date quantity date quantity

delta schedule

A Module_2 05 8 06 8 -1 B Module_2 06 2 06 2 0 C Module_1 10 10 10 10 0 D Module_1 12 15 12 15 0

Which Solution is better?It depends on demand priorities


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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• 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

?? Cycle time – output trade-off?? Complexity of FAB tools


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Allocating Supply to Demandwith

Complex Alternative Paths (BOM)


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Module_9demand = 20priority = 1

Device_8Binventory = 0

Device_8Ainventory = 20


untested deviceWIP = 40on Day 2

substitution

P2

P120%

40%

40%

P2’

P0

substitution can be viewed as an alternative process P2’

Device_8Cinventory = 0

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


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Device_8Binventory = 0

Device_8Ainventory = 20


untested deviceWIP = 40on Day 2

substitution

P2

P1

20%

40%

40%

P2’

P0

substitution can be viewed as an alternative process P2’

Device_8Cinventory = 0

proj. supply of device(future inventory)

Device_8A is .20 x 40 = 8

Device_8C is .40 x 40 = 16

Device_8B is .40 x 40 = 16

8

16

16

20 4

This Solution Meets all demandsAnd does not require “new starts”


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Device_2A30% of Wafer_2 sorts

to Device_2A

Wafer_2cycle time = 30 days, start of BOM chain, one wafer makes 200 devices

Device_2B45% of Wafer_2 sorts

to Device_2B

Device_2C25% of Wafer_2 sorts

to Device_2C

45%30% 25%

Module_2cycle time = 6 days, made via process P_1, consumes

1 unit of Device_2A

Module_2cycle time = 8 days, made

via process P_2, consumes 1 unit of Device_2B

Module_Acycle time = 9 days, made via process P_3, consumes

1 unit of Device_2C

Module_210% of Module_A becomes Module_2

Module_AA90% of Module_A

becomes Module_AA

P_1 P_2

90%10%Alternative processes (methods) to make Module_2,i.e., Module_2 stocks from three production paths

Card_2cycle time = 2 days,

made at vendor VEND001,requires 2 units of Module_2

Card_2cycle time = 4 days,

made at vendor VEND002,requires 2 units of Module_2

Location: VEND001 Location: VEND002

Alternative vendors to make Card_2,i.e., Card_2 stocks from two vendors

P_1

Modulesand alternative

BOM

1

2

Simple View of Wafers

ComplexView of Modules


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HistoricallyCentral Planning Engines

Have focused on non-FAB challenges


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HistoricallyCentral Planning Engines

Handle FAB Capacity

with Nested Wafer Starts (Exits) Separate from cycle time

CAPAVAIL stated as maximumNumber of wafer starts allowed per day

For various groupings of parts


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nested Wafer Start (exit) limitsLogical evolution fromWafer start Equivalents


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Review Wafer Start Equivalents


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• 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

• In this case each Part 003 is “worth” two Part 001; two Part 002 are worth “three” Part 001, etc

• All of the capacity elements of the FAB are “summarized” in one single statement of capacity that is completely removed from actual resources (capacity) consumed

History

part # passes for photopart001 10part002 15part003 20

part001 part002 part003# passes 10 15 20

part001 10 1:1 3:2 2:1part002 15 2:3 1:1 4:3part003 20 1:2 3:4 1:1

Wafer Start Equivalent Ratios

part


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Wafer Start Equivalentslogical evolution

to nested Wafer Start Limits


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History – evolved to nested set of limits

row number Group Time frame 1 Time frame 2 Time frame 3

001 Wiring Group 1 600 675 675002 Technology Group A 400 425 450003 Technology Group B 300 325 350004 Option set W 100 100 100005 Option set X 210 300 300006 Wiring Group 2 500 525 550007 Technology Group D 350 350 375008 Technology Group E 250 275 275009 Option set Y 100 100 100010 Option set Z 200 200 200

011 Total Fab Limit 1000 1100 1150

Table 14: Stating FAB Capacity Limits as a Nested Set of Start Limits

• 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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History – evolved to nested set of limits

row number Group Time frame 1 Time frame 2 Time frame 3

001 Wiring Group 1 600 675 675002 Technology Group A 400 425 450003 Technology Group B 300 325 350004 Option set W 100 100 100005 Option set X 210 300 300006 Wiring Group 2 500 525 550007 Technology Group D 350 350 375008 Technology Group E 250 275 275009 Option set Y 100 100 100010 Option set Z 200 200 200

011 Total Fab Limit 1000 1100 1150

Table 14: Stating FAB Capacity Limits as a Nested Set of Start Limits

• 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.

180 selected

40 available (300-260)

340(=600-260) available

60 selected260(180+60+20) allocated 20 selected

340(=min(340,400) available


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Second Lookat capacity (resource) allocation

in central planning engines (CPE)


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IBM Systems and Technology Group: Advanced Supply Chain Planning

Device 12

4000

SupDay

Module 1CT = 1day

resource utilization = 2

1504D

1002C

AmountDue dayDemand

Module 2CT = 4 days

resource utilization = 3

1903B

0802A

AmountDue dayDemand

Amt Resource 12

??03

??02

??01

AmtDay

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?

How Do I Best Allocate a Perishable Asset

?

?Amt Resource 12

??03

??02

??01

AmtDay

Amt Res12 Avail

6003

3002

3001

AVLDay


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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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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 areMaximize 5XT + 7 XL

subject to 10XT + 12 XL ≤ 194

08XT + 05 XL ≤ 100

XT ≥ 5

XT ≥ 7


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Simple Example of Central Planning

MagicallyCapacity Available

(CAPAVAIL)Is known

MagicallyCapacity consumed

(CAPREQ)Is known

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


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Estimating CAPREQ & CAPAVAIL for FABS

in central planning modelsPresent Real Challenges

wafer starts may look better after this review


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Focus Two Major Challenges

• Planned Lack of Uniformity - not all tools for a manufacturing process have identical profiles– 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 – 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

Deployment(alternative machines)

OP Curve

The Ongoing Challenge - Tutorial The Illusion Of Capacity

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