IC Yield, Reliability and Prognostic using Nanoscale Test...
Transcript of IC Yield, Reliability and Prognostic using Nanoscale Test...
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IC Yield, Reliability and Prognostic using Nanoscale
Test Structures
Hans ManhaeveCEO
Q-Star [email protected]
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Overview
• Setting the scene• Yield: the past, today & tomorrow• Yield & Reliability: The need for Prognostics• Concept of Prognostics• Prognostics and Yield• Conclusions
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The Changing LandscapeSource: Intel
1K4K
64K256K
1M
16M4M
64M
40048080
808680286
i386™i486™
Pentium®Pentium® II
Pentium® III
256M 512M
Pentium® 4Itanium™
1G 2G 4G
128M
MemoryMicroprocessor
1965 Actual Data
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
16K
1975 ProjectionMOS Arrays
TransistorsPer Die
108
107
106
105
104
103
102
101
100
109
1010
Moore’s OriginalPrediction!
40+ Years of Moore’s Law
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The Changing LandscapeInnovation Enabled Technology Pipeline
Tri-Gate
S
G
D
III-V
S
Carbon Nanotube FET
50 nm35 nm
SiGe S/DStrained Silicon
SiGe S/D2nd generation
Strained Silicon
20 nm 10 nm
5 nm
Nanowire
Metal Gate
High-k
High-kMetal gate
Source: Intel
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The Changing Landscape
Changing Shape of Defects
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The Changing LandscapeDealing with variance and fluctuations
Parameters change across dies and across wafer
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The Need for Test
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The Need for Test
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The Need for Test
• But we still need to test every single transistor
• Test is an important factor of IC manufacturing costs (15 50 ….%)
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Find The Defect
Badwater, Death Valley‐85.5m (‐282ft)
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Find the Defect
Butler, ITC07Madge, ITC04
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Yield – From Past to Present• Yield has a simple definition
• Challenge lies in separating “good” from “bad”
chipstotalchipsgoodYield =
x x
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Yield - Ambiguity
GEORGE THOROGOOD
BAD TO THE BONE
partsallfailuresItypeescapestestpartsgoodYieldMeasured −+
=
Competing definitions of “good”Ideal: works in customer’s application→Can’t measure this until it’s too late!
Is high leakage from a defect or fast transistors?Most chips work at 0.7V, this one doesn’tHow complete are these tests?
Eventually need to agree on “passes the tests we apply”Result: Test can’t be ignored when discussing yield!
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Yield – From Past to PresentHistorically, testing was functional
Does the device do what it is supposed to?Function primarily defined logicallyYield related to function
Next, structural tests were developedIs every circuit structure (e.g. gate) present and working?Coverage metrics are logical (stuck-at fault coverage)Yield related to structure
Defect-oriented testing starts with defectsWhat could go wrong with this device?If it went wrong, what would change about the device?Any measurable behavior could be affected, not just function→ timing, current, voltage, temperature dependence
Yield related to absence of defects
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Yield & ReliabilitySemiconductor evolution enables further integration
Transistors are nearly for freeNew processes are used for mass production long before they are mature
Systematic and random defectsReliability concerns
Increasing device complexityThe “embedded” worldAnalog – Digital – Memory – Software
Market demands for cheaper and better electronicsMarket demands for RELIABLE electronics
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Yield & Reliability• Lifetime reliability becomes a serious concern
Useful life
Failu
re ra
te
Infantmortality
180nm130nm90nm
~ 7 year[T. M. Mak]
< 7 year ~ 10 year
Time
WearoutFailure mechanisms
ElectromigrationNBTITDDB
Reliability-related factors
TemperatureSupply voltageFrequency
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Yield & ReliabilityFailure Mode Physics System Effect
NBTI (PMOS)
• Negative Vt shift• Slower speed
• Timing Faults in Processors• Resettable – but increasing severity over time
TDDB
Soft Breakdown:• Slower speed• Weakened gate oxide• Increased leakage current
• Increased ESD Vulnerability• Non‐resettable timing faults
Hard Breakdown/Punch‐through • Catastrophic Short
Hot Carrier (NMOS)
• Positive Vt shift• Change in sub‐threshold swing
• Increased Off‐state power• Increased current draw• Decreased data retention time in DRAM
Metal Migration
• Higher resistance in Via connections• Open circuits
• Catastrophic Open
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Yield & Reliability• Semiconductor processing
always yield a distribution of parameter values
• Minimum geometries have larger fluctuations
• Smaller feature size & lower voltages increase the impact of variation of transistor properties on chip performance and yield
• Foundry-supplied Process Design Kit (PDK) may not give sufficiently accurate data for critical design parameters
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Yield & Reliability -- Prognostics
• Ways to address Nanoscale design reliability
• Use additional design margin– Increased power
consumption– Impacts overall
circuit performance
• Use degradation monitors– Realtime operating
embedded sensors– Actual State of Health
for critical paths– Early warning of
impending failure
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Prognostics Concept
Prognostic Cell
Host Circuit
Prognostic cell representation on a wafer (a) and a single die (b)
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Prognostics Concept
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Prognostics Concept
Threshold Trigger Points are selectable
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Use of Prognostics
Prognostic Advantages• Safety benefit if actual
usage is more severe than predicted (see the red region, T1).
• Service life can be extended beyond normal replacement time if the actual usage severity is known (see the green region, T2).
MTBF statistical expected life
T1 T2
CBM enables replacement only upon evidence of need
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PDK vs Prognostics• Process Design Kit (PDK) may not be accurate for
particular batch/wafer/die/package• PDK may not have data for particular application
(e.g., temperature)• PDK may not be representative of particular
biasing schemes (e.g., MOSFET matching differs for strong inversion and subthreshold)
• Data is not placement-specific (directional/wafer angle)
• PDK may not give values to insert into random parameter fluctuation simulations
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Prognostic Advantages
DLPM
Scribe LineTransistor
DLPM: test structure on the host dieo Scribe line transistor requires additional test
fixture
DLPM testing: post‐packagingo Scribe line transistors are lost when wafers
are sliced
DLPM eanbles quick production testo Scribe line transistor requires delicate probe
measurement: inaccurate and time‐consuming
DLPM measures parameters that are useful to the designero Scribe line transistor may not directly
measure important parameters – additional characterization is required
Data is application‐specifico DUTs are extracted from the host designo PDK models may not provide accurate predictions
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Prognostics - Example
PDKChekimbedded in the ADC
Example of GDSII Layout for the Ridgetop 14‐bit Pipeline ADC
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Prognostics - ExampleRbodysh
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
400 450 500 550 600
Rbodysh(Ω/□)
σ
PDKChek1
PDKChek2
PDKChek3
PDKChek4
PDKChek5Scribe‐line
Scribe‐line Test
Scribe-line Process Control Monitor (PCM) structures from foundry may not directly measure important parameters
High performance designs need DLPM results that accurately track critical paths using Host circuits well structures
Scribe‐line results not in tight Host circuit distribution
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Prognostics & Yield
Parameter Extraction
PDKChek Process Variation
PDK, Models, Variation data
Predicted Yield
Measured Yield
Simulation with process variation
Need Improvement?
Foundry
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Prognostics & Yield - Example
-3
-2
-1
0
1
2
3
-40 -30 -20 -10 0 10 20 30 40σ
ΔVTH(mV)
NMOS (type6) @ PDK1
-3
-2
-1
0
1
2
3
-40 -30 -20 -10 0 10 20 30 40
σ
ΔVTH(mV)
NMOS (type6) @ PDK1
1) Characterize threshold voltage shift in matched pair transistors using PDKChek
2) Characterize yield in flash ADC for given linearity targets (due to comparator offset)
39 dB SINAD yield 90%
45 dB SINAD yield 75%
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Prognostics Solutions Overview
• InstaBIST™ Test Cores– SJ‐BIST BGA Solder Joint Built‐in Test– RingDown™ Power Supply Test– ADC‐BIST Self‐testing Data Converters
• Sentinel Silicon™LibraryReliability/ Prognostics Monitor Cores– TDDB– NBTI– HCI– Metal Migration
• InstaCell™ Mixed Signal Cores– ADC – Analog to Digital Converter– DAC – Digital to Analog Converter– Op Amps and Comparators
• nanoDFM™ Product LineIndependent Foundry Die‐Level Process Monitors– PDKChek® combines
– ∆VT mismatch– ∆I(on) mismatch– ∆R mismatch– ∆C mismatch
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Prognostics Solutions OverviewThird-party
System-level Diagnostic Module(MTBF models)
Hierarchical system modelFailure modes
Constraints
(e.g., safety, reliability, maintainability, cost)
Prognostic sensor attributes- Deployed sensors
(e.g., power supply, interconnect)- Sensor parameters
Prognostic analysis- Precursor signatures
- Remaining Useful Life (RUL)
- State of Health (SOH)
- Enhanced fault dictionary
- Additional graphical displays
Ridgetop Group
Sentinel NetworkTM
Ridgetop interface
Fault coverageDiagnostic metrics
FMEA
Diagnostic test programs
ARULETM Reasoner Calibration
Prognosticcandidates
Prognostic events
Test definition data
SensorsSensors
Hardware MTBF models
Optimization Feedback Loop
Prognostics “wrap around” existing MTBF-based system models
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Conclusions
• Test is critical to identify good and bad devices.
• Although yield has a simple definition, the perspective of yield can be quite different.
• Yields and test are sometimes at odds with each other, but prognostics can help to identify the best compromise.
• Prognostic sensors and test structures are an effective way to assure and improve IC yields.
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About Q-Star Test.• Small Business:
– Incorporated 2000– Headquartered in Brugge, Belgium– DFT & Test solution Industry leader– Prime expert on Current measurement
solutions and test methodologies
• Who We Serve:– Q-Star Test provides innovation in DFT, Test,
Measurement and Prognostics for a wide range of commercial customers.
AutomotiveMedicalTelecommunicationConsumerIndustry PartnersAcademia
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Consulting and Training Services related to Design for Test (DFT) and Test Optimization.Advanced (Current) Measurement Solutions applicable to digital, analog, mixed-signal and RF devices and systemsEngineering Services supporting design, prototyping, validation and test of electronic circuits and systemsTest Engineering Services supporting test program development and test program optimizationElectronic Prognostic Solutions enabling to better monitor healthiness of electronic circuits and systems and to make reliable (remaining) lifetime predictions.
Q-Star Test – Products & Services
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About Q-Star TestMake use of Q-Star’s solutions and :• Reduce your test efforts, test costs and test escape risks• Reduce your production test time without sacrificing quality• Increase your engineering and failure analysis productivity• Improve your product quality and monitor process quality• Extend the use of IDDQ testing into the Deep-Submicron and
Nanotechnology arena• Implement analog IDD, IDDT and ISSQ testing on your
production test floor• Have a guarantee that the device’s operation conditions are
maintained
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About Q-Star TestQ-Star provides solutions to:
– Reduce IC test costs– Improve product quality and reliability– Enable advanced high-speed high-resolution IDDX
test and measurement solutions.
Q-Star’s measurement solutions provide highly repeatable results and allow increased product quality while shortening test time.
Q-Star offers Design for Test (DFT) and test optimization consulting services.
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Q-Star Test MissionOur Mission is:
To help our customers build better electronic products at lower cost
This translates to:
To provide Innovative Solutions Enabling: Test Time (Cost) Reduction and Test Data Quality
Improvement Combined with Product Quality and Reliability Improvement.
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For More Information…Q-Star Test nv
Lieven Bauwensstraat 20B-8200 Brugge, Belgium
Tel: +32 50 319273, Fax: +32 50 312350
USAQ-Star Test / Ridgetop Group Inc.
6595 North Oracle RdTucson, Arizona 85704, USA
Tel: 520-742-3300
[email protected] or [email protected]://www.QStar.be