1. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 1 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, IBM Prof. John Milne, Clarkson University (IBM retired) & Dr. Harpal Singh, CEO Arkieva

2. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 2

3. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 3 Link to video http://youtu.be/DjnRtSxmE-g?hd=1

4. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 4 Theme for This Afternoon’s Feature Presentation is The Hunt for CAPAVAIL (capacity available) and CAPREQ (capacity required) in central planning engines

5. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 5 IBM has >> PROFIT (CPE) (Edelman, Wagner) and >> EPOS (Wagner, MASM) why? Answer Question End to end demand supply network plan 300mm EFK FAB planning Loosely coupled with wafer starts and cycle time

6. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 6 “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

7. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 7 “The great 20th century revelation that complex systems can be generated by the relationships among simple components” (Goldman 2004) – applies to matching assets with demand for planning, scheduling, and dispatch

8. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 8 All models are wrong, some models are useful All models are approximations that balance –“ease of use” –with accuracy. Good models understand the impact of the approximations imbedded in the model. –This enables one to know whether the model is 80/20 or 40/60. Some Basics of Modeling

9. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 9 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

10. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 10 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 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 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

11. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 11 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

12. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 12 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

13. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 13 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

14. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 14 Overview of Demand Supply Network for the production of semiconductor based package goods Warring factions

15. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 15 Card_2 cycle time = 4 days; requires 2 units of Module_2 to build; end of BOM chain Module_2 cycle time = 8 days; requires 1 unit of Device_2 to build Device_2 cycle time = 3 days; requires 1/200 unit of Wafer_2 to build Wafer_2 cycle time = 60 days; start of BOM chain; one wafer makes 200 devices Simple view demand supply network for production of semiconductor based packaged goods

16. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 16 Card_2 cycle time = 4 days; requires 2 units of Module_2 to build; end of BOM chain Module_2 cycle time = 8 days; requires 1 unit of Device_2 to build Device_2 cycle time = 3 days; requires 1/200 unit of Wafer_2 to build Wafer_2 cycle time = 60 days; start of BOM chain; one wafer makes 200 devices Simple view demand supply network for production of semiconductor based packaged goods

17. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 17 = BOM = Alternate BOM = Binning = Substitution Finished Mod. X Finished Mod. YFinished Mod. ZFinished Mod. W Sort A Device (Fast) Module 1 Sort BSort C Module 2Module 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

18. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 18 MUVImplantStripWets

19. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 19 MUVImplantStripWetsMUVImplantStripWetsMUVImplantStripWets FAB

20. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 20 MUVImplantStripWets MUVImplantStripWets MUVImplantStripWets Prod A MUVImplantStripWets MUVImplantStripWets Prod B

21. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 21 MUVImplantStripWets MUVImplantStripWets MUVImplantStripWets Prod A MUVImplantStripWets MUVImplantStripWets Prod B Oper A-1 Tools 1, 2 Oper B-1 Tools 1, 2 Oper A-2 Tools 2, 3 Oper A-3 Tools 3 Oper B-2 Tools 2 3 passes 2 passes

22. © 2009 IBM Corporation22 ? Target ? Package ? Test code ? ? PB bin ? ? ? ? ? ? IC BI PB LHS: Supply RHS: Demand Quantity of a given die package pegged to a given test suite in a given time period [die, grade, package-lead, test-flow, time-period] Output implication; quantity of test-out units by bin: –[die, grade, package-lead, test-flow, bin, time-period] –Bin(i) relative to device and test flow represents a specific collection of performance attributes; core, cache, speed, power, temp. ….. consideration –Resource consumption –Material procurement –cycle time –cost Test-out to OPN allocation  [die, grade, package- lead, test-flow, bin, opn, time-period] Implication –System level test yields and capacity consumption –cycle time, benefits (revenue, fulfillment) Source - from Analytics Based Decision Making For Semiconductor Manufacturing Mehmet F. Candas, IBM Research

23. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 23

24. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 24

25. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 25

26. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 26 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.

27. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 27 Central Planning FAB Planning FAB is an entity that makes Wafers “I just want my wafers” Focus post FAB Different Groups Different summary methods for capacity, routes, & lot priorities Focus on tools, starts, and wafer output routes, reentrant flow, Deployment, lot priorities Operating curve, a bit of headache Challenge Better linkage? How much complexity is needed? How much can be absorbed? At best loosely and narrowly linked

28. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 28

29. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 29 Two Major Challenges From FABS

30. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 30 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

31. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 31 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

32. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 32 Deployment Ingredient # 1 Which Tools Can Handle Which Operations 1 – oper/tool link active 0 – not allowed

33. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 33 Deployment Ingredient # 2 RPT per widget per time unit for Tool / Operation Pairing

34. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 34 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

35. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 35 Operating Curve Basics For Blue Operating Curve to achieve a CTM of 5.00 Requires accepting Tool utilization of 80% Which Means you plan to have 20% 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 WIP Can be viewed as a Tax to Achieve a certain cycle time To maintain the same cycle time But increase tool utilization Requires “shifting” curve Dow and to the right “cheating” the tax man Reduce variability Old concept within industry Thinking how this relates to clearing function

36. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 36 Basics of FAB Planning

37. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 37 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

38. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 38 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

39. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 39 Basics of Aggregate FAB Planning

40. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 40 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

41. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 41 Factory load or starts Statement Representative Factory Routes often aggregating parts into a family Aggregate FAB Capacity Plan Tool Set Character istics Reports on required utilization levels and capacity loss points High level statement of capacity based specified cycle time to limit demand on the factory How additional capacity enables the factory to handle more starts Allocation of tools to families Factory Planning Model has key relationships

42. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 42 Basics of FAB Planning two other functions Deployment or Near Term Tool Planning: refers to determining which operations each tool will be qualified to handle over the short term. WIP Projection - All central planning engines require each factory to project when current WIP in the line will reach either completion or staging point – typically called projected finish.

43. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 43 Basics of Central Planning for the entire demand supply network (supply chain) for the production of semiconductor based packaged goods

44. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 44 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 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

45. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 45 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

46. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 46 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 FAB 1. projected WIP completion 2. capacity statement 3. lead or cycle times

47. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 47 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.a projected supply linked with exit demand 2.identification of at risk orders either to a commit date or request date 3.Synchronization signals across the enterprise 4.Capacity utilization levels 5.Ability to traceproduction & distribution activity that supports meeting a demand

48. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 48 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.

49. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 49 Module_1 Demands CT = 10 days Module_2 Demands CT = 4 days ? ? Device_12 1006 3002 2000 SupDay 2010 Amount Supplied ??06 ??02 ??00 AmtDay ??10 Amount Supplied ??06 ??02 ??00 AmtDay ??10 How do we allocation this supply to met this demand

50. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 50 Emphasis on Optimal Allocation of Supply to Demand

51. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 51 Device_12 2010 3002 1000 SupDay Module_2 CT = 4 days 206B 805A AmtDue dayDem Module_1 CT = 10 days 1512D 10 C AmtDue dayDem Supply Amt ?10 ?02 ?00 AmtDay Supply Amt ?10 ?02 ?00 AmtDay Allocate supply Of devices to Modules 1 & 2 **Device Supply is starting point

52. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 52 Which Solution is better? It depends on demand priorities

53. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 53 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

54. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 54 Allocating Supply to Demand

55. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 55 Device_12 2010 3002 1000 SupDay Module_2 CT = 4 days 206B 805A AmtDue dayDem Module_1 CT = 10 days 1512D 10 C AmtDue dayDem Supply Amt ?10 ?02 ?00 AmtDay Supply Amt ?10 ?02 ?00 AmtDay Allocate supply Of devices to Modules 1 & 2

56. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 56 Which Solution is better? It depends on demand priorities

57. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 57 Allocating Capacity to Demand

58. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 58

59. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 59 Binning

60. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 60 Device_2 Demand = 40 Device_1 Demand = 30 Device_3 Demand = 30 Untested Device substitution 50% 30% 20% substitution # of devices = ? Binning and Down Grade Substitution

61. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 61 Device_2 Demand = 40 Device_1 Demand = 30 Device_3 Demand = 30 Untested Device substitution 50% 30% 20% substitution = 10 50 30 20 Mfg Binning Device_1 is.50 x 100 = 50 Device_3 is.20 x 100 = 20 Device_2 is.30 x 100 = 30 excess = 0 # of devices = 100

62. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 62 Foundry Contracts

63. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 63 DGR Service Demand Service Demand priority applies DGR demand priority applies Reserves kept for further downstream processing by IBM typically end products shipped to external clients; consumes DGR Reserves IBM receives new contracts for foundry parts (typically finished wafers):  Quantities expressed in terms of “daily going rate” (DGR) for finished wafers.  DGRs are either shipped directly to external clients (“Exits”) or made available for “Services” at IBM (“Reserves”). wafer start wafer finish Exits shipped directly to external clients Service Demand cannot drive additional DGR starts Foundry Contracts

64. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 64 Customer Commit & Request Dates

65. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 65 Information passed to customer demand for part A qty = 100 commit date 07/01 request date 06/01 supply for part A qty = 100 projected WIP date 06/01 engine assigns WIP to meet part A demand at what date ? Customer Commit and Request date

66. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 66 Basics of Repair Actions

67. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 67 Repair Actions

68. D001 4/4/06 priority 2 amt 80 D002 4/5/06 priority 1 amt 100 S00A 4/4/06 amt 100 S00B 4/6/06 amt 100 +1 -2 S00A assigned to more important demand – D002 D002 demand met 1 day early S00B assigned to less important demand – D001 D002 demand met 2 days late Attempt to Expedite S00B Initial Solution

69. D001 4/4/06 priority 2 amt 80 D002 4/5/06 priority 1 amt 100 S00A 4/4/06 amt 100 S00B 4/6/06 4/4/06 amt 100 +1 0 change date to 4/4, 2 days earlier Initial Solution forces 2 day Expedite on Factory To meet all demand on time

70. D001 4/4/06 priority 2 amt 80 D002 4/5/06 priority 1 amt 100 S00A 4/4/06 amt 100 S00B 4/6/06 4/5/06 amt 100 0 0 change date to 4/5, 1 days earlier “Better Solution” Change Assignments of supply to demand Reduces chase workload on Factory

71. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 71 Allocating Supply to Demand with Complex Alternative Paths (BOM)

72. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 72 Module_9 demand = 20 priority = 1 Device_8B inventory = 0 Device_8A inventory = 20 Module_8 demand = 20 priority = 8 untested device WIP = 40 on Day 2 substitution P2 P1 20% 40% P2’ P0 substitution can be viewed as an alternative process P2’ Device_8C inventory = 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

73. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 73 Module_9 demand = 20 priority = 1 Device_8B inventory = 0 Device_8A inventory = 20 Module_8 demand = 20 priority = 8 untested device WIP = 40 on Day 2 substitution P2 P1 20% 40% P2’ P0 substitution can be viewed as an alternative process P2’ Device_8C inventory = 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 20 4 This Solution Meets all demands And does not require “new starts”

74. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 74 Wafer Module_2 Module_1 Module_3 Device_1 Device_1B Device_1A Device_3 Device_3B Device_3A = Binning = Alternative BOM = BOM = Substitution Device_2 Device_3C Device_2B Device_2A Raw_ Module_1B Raw_ Module_1A Raw_ Module_3B Raw_ Module_3A Raw_ Module_3C Raw_ Module_2A # of starts = ? Yes, the paths can get this complicated

75. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 75 = BOM = Alternate BOM = Binning = Substitution Finished Mod. X Finished Mod. YFinished Mod. ZFinished Mod. W Sort A Device (Fast) Module 1 Sort BSort C Module 2Module 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

76. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 76 Device_2A 30% of Wafer_2 sorts to Device_2A Wafer_2 cycle time = 30 days, start of BOM chain, one wafer makes 200 devices Device_2B 45% of Wafer_2 sorts to Device_2B Device_2C 25% of Wafer_2 sorts to Device_2C 45% 30% 25% Module_2 cycle time = 6 days, made via process P_1, consumes 1 unit of Device_2A Module_2 cycle time = 8 days, made via process P_2, consumes 1 unit of Device_2B Module_A cycle time = 9 days, made via process P_3, consumes 1 unit of Device_2C Module_2 10% of Module_A becomes Module_2 Module_AA 90% 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_2 cycle time = 2 days, made at vendor VEND001, requires 2 units of Module_2 Card_2 cycle time = 4 days, made at vendor VEND002, requires 2 units of Module_2 Location: VEND001Location: VEND002 Alternative vendors to make Card_2, i.e., Card_2 stocks from two vendors P_1 Modules and alternative BOM 1 2 Simple View of Wafers Complex View of Modules

77. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 77 Historically Central Planning Engines Have focused on non-FAB challenges

78. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 78 Historically Central Planning Engines Handle FAB Capacity with Nested Wafer Starts (Exits) Separate from cycle time CAPAVAIL stated as maximum Number of wafer starts allowed per day For various groupings of parts

79. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 79 nested Wafer Start (exit) limits Logical evolution from Wafer start Equivalents

80. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 80 Review Wafer Start Equivalents

81. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 81 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

82. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 82 current diversity and complexity of parts produced by FAB limits effectiveness example if the FAB has only 10 parts and Photo is divided into DUV and MUV, the pass count numbers might be: experience, local knowledge, culture, simplicity, et al continue to make it appealing Current Circumstances - diversity

83. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 83 With just 10 parts the use of ratios is complicated ADDITIONALLY, ratios “reverse” between DUV and MUV, for example –Part001 requires 5 DUV passes and 7 MUV passes (more MUV than DUV) –Part003 requires 6 DUV passes and 4MUV passes (more DUV than MUV) Current Circumstances - Example

84. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 84 Current Circumstances- Ratios DUV Ratio of Part 001 to Part 005 is 0.56 MUV Ratio of Part 001 to Part 005 is 2.33

85. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 85 When we add in just a few OAK (one of a kind) tools the “wafer” start equivalent method gets a “tad” complicated Current Circumstances – add in a few OAK

86. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 86 Wafer Start Equivalents logical evolution to nested Wafer Start Limits

87. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 87 History – evolved to nested set of 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.

88. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 88 History – evolved to nested set of 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 selected 260(180+60+20) allocated 20 selected 340(=min(340,400) available

89. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 89 In this example a part that maps to option set W also maps to Technology Group B, then Wiring Group 1, and finally “Total FAB”. A part consuming some of the 100 units of Option set W capacity (capacity is stated in wafer starts) simultaneously consumes some of the 300 units of Technology Group B, 600 units of Wiring Group 1, and 1000 units of “Total” FAB. The same applies to Option set X. Similarly a part that maps to Option set Y or Z also maps to Technology Group E, Wiring Group 2, and “Total FAB”. A part might belong to Technology Group B and neither Option Set W or X. Some parts will belong to Technology Group A which has no “option” sets in this statement of capacity. A part can belong to at most one option set, at most one technology group, and at most one wiring group. All parts belong to “Total FAB limit.” History – evolved nested set of limits

90. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 90 This method allows the CPE to start up to, but not exceed any limit to which products are mapped. For example, the total wafers started for parts mapped to Option Set W in Tech Group B in “Wiring Group 1” may not exceed 100 wafers per day (row 004). The total wafers started for parts mapped into Technology Group B (which includes Option sets W and X and parts that belong to Technology group B, but neither option set) can not exceed 300 per day (row 003) in time frame 1. If the business did start 100 per day for option set W, then at most it could start another 200 (=300-100) wafers that belonged to Technology Group B. What if the business started 325 wafers that belong to Technology Group D (row 007); how many could it start in Technology group E (row 008)? Although the direct limit on Technology group E is 250, it can only start 175 since the total limit for Wiring Group 2 (row 006) is 500 and Technology group D has used 325 of these 500 units leaving 175 (=500-325). History – evolved nested set of limits

91. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 91 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. In this example a part that maps to option set W also maps to Technology Group B, then Wiring Group 1, and finally “Total FAB”. A part consuming some of the 100 units of Option set W capacity (capacity is stated in wafer starts) simultaneously consumes some of the 300 units of Technology Group B, 600 units of Wiring Group 1, and 1000 units of “Total” FAB. The same applies to Option set X. Similarly a part that maps to Option set Y or Z also maps to Technology Group E, Wiring Group 2, and “Total FAB”. A part might belong to Technology Group B and neither Option Set W or X. Some parts will belong to Technology Group A which has no “option” sets in this statement of capacity. A part can belong to at most one option set, at most one technology group, and at most one wiring group. All parts belong to “Total FAB limit.” This method allows the CPE to start up to, but not exceed any limit to which products are mapped. For example, the total wafers started for parts mapped to Option Set W in Tech Group B in “Wiring Group 1” may not exceed 100 wafers per day (row 004). The total wafers started for parts mapped into Technology Group B (which includes Option sets W and X and parts that belong to Technology group B, but neither option set) can not exceed 300 per day (row 003) in time frame 1. If the business did start 100 per day for option set W, then at most it could start another 200 (=300-100) wafers that belonged to Technology Group B. What if the business started 325 wafers that belong to Technology Group D (row 007); how many could it start in Technology group E (row 008)? Although the direct limit on Technology group E is 250, it can only start 175 since the total limit for Wiring Group 2 (row 006) is 500 and Technology group D has used 325 of these 500 units leaving 175 (=500-325). History – evolved nested set of limits

92. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 92 Second Look at capacity (resource) allocation in central planning engines (CPE)

93. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 93

94. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 94 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

95. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 95

96. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 96

97. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 97 Simple Example of Central Planning The equations are Maximize 5X T + 7 X L subject to 10X T + 12 X L ≤ 194 08X T + 05 X L ≤ 100 X T ≥ 5 X T ≥ 7

98. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 98 Simple Example of Central Planning Magically Capacity Available (CAPAVAIL) Is known Magically Capacity consumed (CAPREQ) Is known

99. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 99 Estimating CAPREQ & CAPAVAIL for FABS in central planning models Present Real Challenges wafer starts may look better after this review

100. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 100 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

101. Fordyce, Fournier, Milne, Singh Illusion of FAB Capacity in Central Planning – hunt for CAPAVAIL 101 Two Major Challenges Planned Lack of Uniformity - not all tools for a manufacturing process have identical profiles –What operations they handle –Their production rate Inherent Variability - in the manufacturing line forces us to plan for unused capacity (tools ready to go, but idle due to lack of WIP) –Operating curve trade-off between output and cycle time Deployment (alternative machines) OP Curve