21-Mar-00 • 1 • PDF Solutions, Inc.
Ramping New Products Yields Ramping New Products Yields in the Deep - - PowerPoint PPT Presentation
Ramping New Products Yields Ramping New Products Yields in the Deep - - PowerPoint PPT Presentation
Ramping New Products Yields Ramping New Products Yields in the Deep Submicron Submicron Age Age in the Deep ISQED 2000 March 21st, 2000 PDF Solutions, Inc. John K. Kibarian 21-Mar-00 1 PDF Solutions, Inc. Major Points Major
21-Mar-00 • 2 • PDF Solutions, Inc.
Major Points Major Points
G Increasing design and process complexity becoming
critical factor leading to yield loss
G Systematic yield loss component is significant,
growing, and recoverable
G Fundamental new approach, focused on integration
between design, process and manufacturing, is required to recover yield loss
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Outline Outline
G Product Yield Ramps: the market pressures G The Design-Manufacturing Integration Problem G Solution G Examples G Concluding remarks
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Complexity is Increasing Across the Board Complexity is Increasing Across the Board
IC Complexity: Processing Steps
100 200 300 400 500 600 1997 1999 2002 2005 2008
Processing Steps IC Complexity: Transistors
1 10 100 1,000 1997 1999 2001 2003 2005 2008
Transistors (M)
IP Reuse is IP Reuse is Critical to Get Critical to Get Designs to Market Designs to Market Faster Faster Unless Corrected, Unless Corrected, Increased Processing Increased Processing Complexity Reduces Complexity Reduces Yield up to 5% per Year Yield up to 5% per Year
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The Window is Tightening The Window is Tightening
Years to 1 Million Sales
1 2 3 5 10 15 20 25
Sales Volume 1 Million Units
Playstation II DVD Cellular PC VCR Color TV Cable TV B&W TV PCS 5 10 15 20
1000 2000 3000 4000 5000 12 24 36
Months to Full Production Wafers per Week
Design Rules: 0.13u 0.18u 0.25u 0.35u 0.5u 0.8u Accelerating Ramp Rates
The demand is The demand is accelerating accelerating There is less time There is less time to bring up the to bring up the volume volume
Sources: 1) D. Merriman, “Wireless Comm. Report”, BIS, Boston, 1995+Dataquest 2) IC Insights/Ross Assoc.
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Missing the Window is Expensive Missing the Window is Expensive
Integration effects market entry point, Integration effects market entry point, performance, and cost basis performance, and cost basis
Annual COGS Savings per 10,000 Wafers1 $0m $100m $200m Top 25% Top 5%
Three costs: Three costs:
- Lost market share
Lost market share
- Increased NRE
Increased NRE
- Increased Costs of
Increased Costs of Goods Sold (COGS) Goods Sold (COGS)
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And Those Yield Loss $$$ are Recoverable ... And Those Yield Loss $$$ are Recoverable ...
Recoverable Yield Loss
0% 25% 50% 75% 100% Mature (.35um) Advanced (.18um) Design Manufacturing Integration Contamination Materials+Other Process Variation
Yield Loss Components
0% 25% 50% 75% 100% Mature (.35um) Advanced (.18um) Design Manufacturing Integration Contamination Materials+Other Process Variation
Bad News: Bad News:
Integration Issues Integration Issues Now Account for 30% Now Account for 30%
- f Yield Loss During
- f Yield Loss During
Ramp Ramp
Good News: Good News:
Nearly All Integration Nearly All Integration Related Loss is Related Loss is Recoverable Recoverable
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… but, an Integrated Approach is Required … but, an Integrated Approach is Required
Traditional Traditional
Isolated Approach Design Design Design Process Process Process Manufacturing Manufacturing Manufacturing
Holistic Holistic
Manufacturing Manufacturing Manufacturing Process Process Process Design Design Design Integrated Solution
— — Rob Chaplinsky, general partner of Mohr Davidow Ventures
“Ask yourself this: Why does a MIPS core cost 25 cents, and you go to QED and there's a 100-fold increase in value? … the QED part is worth $25 because it is implemented in silicon.”
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Technical Issues Have Both Design and Technical Issues Have Both Design and Manufacturing Implications Manufacturing Implications
New Technology Impact on Design / Manufacturing Interface Compensation Design – Manufacturing Issue Chemical Mechanical Polishing (CMP)
- ILD Variability
- Depth of focus
- Capacitance
variability
- Dummy fill
- Increased design
margin
- What is the circuit
performance impact?
- What is the optimal
dummy fill strategy? I-Line @ 0.35µm DuV @ 0.25µm and below
- Large w/in chip line
width variation
- Optical Proximity
Correction
- Printability verification
after OPC?
- Gap fill issues?
Channel & Source Drain Engineering RTA, Tox, Poly CD
- Increased relative
variability of transistor performance
- Statistical design
- Increase margins
- Traditional worst case
corners not valid Re-use of large design cores
- Debugging product
yield issues
- Black box yield
models
- Fault localization
difficult
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Design or Manufacturing Problem? Design or Manufacturing Problem? Both! Both!
Die X (mm) Die X (mm) Die Y (mm) Die Y (mm) Dielectric thickness (um)
CMP causes layout dependent dielectric variation which causes yield loss Dummy fill improves uniformity But capacitance can go up!
CA CA CB CB (b) CC CD
Optimal solution depends on both design and process considerations
- B. Stine et al, Transactions on Electron Devices, Vol 45 No. 3
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Simulating Design - Manufacturing Simulating Design - Manufacturing Integration Integration
Process Recipe Libraries
Design Design Design
Design Analyzer Design Design Analyzer Analyzer Characterization Vehicles Characterization Characterization Vehicles Vehicles Yield Modeler Yield Modeler Yield Modeler Characterization Vehicle Analysis Characterization Characterization Vehicle Analysis Vehicle Analysis
Design Manufacturability Components Manufacturing Models
Yield Impact Matrix Yield Impact Yield Impact Matrix Matrix
Design and Process Improvements Product Design
Manufacturing Manufacturing Manufacturing
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The Yield Impact Matrix The Yield Impact Matrix
Layout Attributes Yield Models IP Layouts Pre-tapeout Product Layouts SRAM Layouts Defect CV Data Layout-Process CV Data Device CV Data
Yield Impact
Overall Chip 85.7% 58.0% 49.8% Block A 95.0% 93.0% 88.4% Block B 95.0% 65.0% 61.8% Virgin Cache 80.0% 80.0% 64.0% Cache w/ Repair 95.0% 96.0% 91.2%
Yield Impact Matrix
Product A Defectivity Design Dependent
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Design Predict Fab Specific Yield
Yes
Design yield issue? Production selection Mask Data Processing fix? Block redesign? Foundry specific yield models
- f module
failure rates Feedback to product group Make fix Internal External Shrink Tape out Tape out Redesign Tape out
Yes No No
Using Simulated Integration Results to Make Using Simulated Integration Results to Make Production Decisions Production Decisions
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Example 1: Via Short Flow CV Example Example 1: Via Short Flow CV Example
Floorplan Floorplan
Via2 Loading Contact Loading Isolated Vias Via1 Loading Via2 Misalignment Contact Misalignment Redundancy Size Long Runners Long Runners Long Runners
- Via1/Via2/Contact Loading:
Compute yield impact of density.
- Via2/Contact Misalignment:
Compute yield impact of misalignment
- f via to underlying layers.
- Redundancy:
Compare fault rates of single via chains to redundant via chains.
- Size:
Compute yield impact of via size. Check process margin.
- Long Runners:
Compute yield impact of long metal runs in via chain.
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Example 1: Yield Modeling Example 1: Yield Modeling
Process Specific Via Yield Model Process Specific Via Yield Model
Single Vias Redundancy = 2 Redundancy = 2 Single Vias density density density density
Via Yield Model:
Yvia(non-redundant) = f1(misalignment, density, N) Yvia-redundant) = f2(misalignment, density, N)
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Example 1: Design Yield Entitlement Example 1: Design Yield Entitlement
Product Specific Via Yield Prediction Product Specific Via Yield Prediction
Product B
Via Yield Model:
Yvia(non-redundant) = f1(misalignment, density, N) Yvia-redundant) = f2(misalignment, density, N) Misalignment Data Via-density Product A
Yield Modeler
Via-density Product B
Border Size (um) 0% 20% 40% 60% 80% 100% 0.02 0.04 0.06 0.08 Yield Product A Product B
Product A
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Example 2: Optimizing Fill For Performance Example 2: Optimizing Fill For Performance and Yield and Yield
Questions about dummy fill algorithm:
G Which layers? G What pattern? G Should you exclude sections of the design layout?
Approach
G Build vehicle to characterize performance/yield dependencies on
layout choice
G Build yield models G Optimize dummy fill for product chips
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Example 2: Optimizing Fill for Yield and Example 2: Optimizing Fill for Yield and Performance Performance
30 Identical circuits
G Each contains: SRAM, gate
dependent and interconnect dominated logic circuits, and analog blocks
G Each variant is a DOE element
exploring dummy fill, meta/poly OPC, via sizing options Some fill patterns have positive impact
- n yield and
performance for some design blocks
150 160 170 180 190 200 210 220 230 240 250 1 2 3 4 5 Design Blocks Clock Rate A Fill B Fill C Fill
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