test and test equipment july 2011 san francisco, california dave armstrong itrs 2011 test and test...
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Test and Test Equipment July 2011
San Francisco, CaliforniaDave Armstrong
ITRS 2011 Test and Test Equipment – San Francisco, CA
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2011 Test TeamAkitoshi NishimuraAmit MajumdarAnne GattikerAtul GoelBill PriceBurnie WestCalvin CheungChris Portelli-HaleDave ArmstrongDennis ContiErik VolkerinkFrancois-Fabien FerhaniFrank PoehlHirofumi TsuboshitaHiroki IkedaHisao HoribeBrion Keller Nilanjan 'Mukherjee'Rohit Kapur
Sanjiv TanejaSatoru TakedaSejang OhShawn FetterolfShoji IwasakiStefan EichenbergerSteve ComenSteve TildenSteven SlupskyTakairo NagataTakuya KobayashiTetsuo TadaUlrich SchoettmerWendy ChenYasuo SatoYervant ZorianYi Cai
Jerry McbrideJody Van HornKazumi HatayamaKen LanierKen TaokaKen-ichi AnzouKhushru ChhorMasaaki NambaMasahiro KanaseMichio MaekawaMike BienekMike Peng LiMike RodgersPaul RoddyPeter MaxwellPhil NighPrasad MantriRene SegersRob AitkenRoger Barth
ITRS 2011 Test and Test Equipment – San Francisco, CA
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2011 Changes
• New Section on 3D Device Test Challenges• Updated Adaptive Testing section• Logic / DFT
– Major re-write of this section thanks to the addition of some new team members representing the major three EDA vendorsr
• Numerous other changes to specialty devices info.• Test Cost
– Test cost survey completed that quantifies industry view
• Other updates will be published for the Logic, Consumer/SOC, RF, ad Analog section.
ITRS 2011 Test and Test Equipment San Francisco, CA
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Test Cost Components
NRE•DFT design and validation•Test development
Device•Die area increase•Yield loss
UntestedUnits
Work Cell•Building•People•Consumables•DUT Interface•Test Equipment•Handling Tools•Factory Automation
Good Units
Reject Units
FalsePassUnits
False Fail Units
Previous DataMore challenges in the future
ITRS 2011 Test and Test Equipment – San Francisco, CA
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Test Cost Components
NRE•DFT design and validation•Test development
Device•Die area increase•Yield loss
UntestedUnits Test Cell
Good UnitsReject Units
FalsePassUnits
False Fail Units
3D Technology AddMany Challenges
ProbablyGood Units
ProbablyGood Units
NRE•DFT design and validation•Test development
NRE•DFT design and validation•Test development
NRE•DFT design and validation•Test development
ProbablyGood Units
Test Cell
Rejected Units
Pass/Fail
Good Die in a Failing Stack
SmartManufacturing
ITRS 2011 Test and Test Equipment – San Francisco, CA
Wafer ProbeWafer Probe
Final TestFinal Test
Burn-inBurn-in
Stack / Card / Stack / Card / System TestSystem Test
• Fab data• Design data• Business data• Customer specs
“RT A/O” stands for “Real-Time Analysis &
Optimization”
ETestETestOptical InspectionOptical Inspection
Other inline dataOther inline dataAssembly/Build DataAssembly/Build Data
FABFAB
Field OperationField Operation
RT A/OPTAD
“PTAD” is “Post-Test Analysis & Dispositioning” PTAD
PTAD
PTAD
PTAD
Databases & Automated Databases & Automated Data AnalysisData Analysis
(This may include multiple databases. ‘Analysis’ includes
capabilities like post-test statistical analysis, dynamic routings and
feedforward data.)
Databases & Automated Databases & Automated Data AnalysisData Analysis
(This may include multiple databases. ‘Analysis’ includes
capabilities like post-test statistical analysis, dynamic routings and
feedforward data.)
Assembly Assembly OperationsOperations
(This includes test operations at any
level of assembly.)
RT A/O
RT A/O
RT A/O
Adaptive Test FlowAdaptive Test Flow
Unchanged
Revised
New
Drop
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2011 Drivers
• Device trends– Increasing device interface bandwidth and data rates– Increasing device integration (SoC, SiP, MCP, 3D packaging)– Integration of emerging and non-digital CMOS technologies– Complex package electrical and mechanical characteristics– Device characteristics beyond the deterministic stimulus/response model– 3 Dimensional silicon - multi-die and Multi-layer– Multiple Power modes and Multiple time domains– Fault Tolerant architectures and protocols
• Test process complexity– Device customization / configuration during the test process– “Distributed test” to maintain cost scaling– Feedback data for tuning manufacturing– Adaptive test and Feedback data– Higher Order Dimensionality of test conditions– Concurrent test within a DUT– Maintaining unit level test traceability
ITRS 2011 Test and Test Equipment – San Francisco, CA
2011 Drivers (2)• Economic Scaling of Test
– Physical and economic limits of packaged test parallelism– Test data volume and feedback data volume– Effective limit for speed difference of HVM ATE versus DUT– Managing interface hardware and (test) socket costs– Trade-off between the cost of test and the cost of quality– Balancing General Purpose Equipment vs. Multiple Insertions for System Test
and BIST
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UnchangedRevised
NewDrop
ITRS 2011 Test and Test Equipment – San Francisco, CA
2011 Difficult Challenges• Cost of Test and Overall Equipment Efficiency
– Progress made in terms of test time, capital cost, multisite test– Continued innovation in DFT, Concurrent Test, Balancing DPM vs. Cost– Gains in some cases are now limited by Overall Equipment Efficiency
• Test Development as a Gate to Volume Production (Time to Market)
– Increasing device complexity driving more complex test development.– Complexity also driven by the diversity of different types of device interfaces on a single
chip.
• Potential yield losses– Tester inaccuracies (timing, voltage, current, temperature control, etc)– Over testing (e.g., delay faults on non-functional paths)– Mechanical damage during the testing process– Defects in test-only circuitry or spec failures in a test mode e.g., BIST, power, noise– Some IDDQ-only failures– Faulty repairs of normally repairable circuits– Decisions made on overly aggressive statistical post-processing– Multi-die stacks / TSV– Power management issues
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NewDrop
2011 Difficult Challenges (2)
• Detecting Systemic Defects – Testing for local non-uniformities, not just hard defects– Detecting symptoms and effects of line width variations, finite dopant
distributions, systemic process defects
• Screening for reliability– Effectiveness and Implementation of burn-in, IDDQ, and Vstress testing– Screening of multiple power down modes and binning based on power
requirements– Detection of erratic, non deterministic, and intermittent device behavior
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NewDrop
2011 Future Opportunities• Test Program Automation
– Automatic generation of an entire test program.– Tester independent test programming language.– Mixed Signal still a test programming challenge
• Scan Diagnosis in the Presence of Compression
• Simulation and Modeling– Seamless integration of simulation & modeling into the testing process.– A move to a higher level of abstraction with Protocol Aware test resources.– Focused test generation based on layout, modeling, and fed back fabrication
data.
• Convergence of Test and System Reliability Solution– Re-use of test collateral in different environments (ATE, Burn-in, System,
Field)11
UnchangedRevised
NewDrop
ITRS 2011 Test and Test Equipment – San Francisco, CA
Summary• Stacked devices change many things for test.
– The methods and approach seem available.– Considerable work ahead of us to implement.
• Adaptive testing is becoming a standard approach– Significant test data accumulation, distribution, and analysis
challenges.
• Ongoing changes to the RF, Analog, and Specialty devices.
• Many more details to be published in the final document.
Thank You!
Backup
TesterTester
Local DatabaseLocal DatabaseFor real-time data analysis & actions. For real-time data analysis & actions.
Resident on Tester or in Test Cell.Resident on Tester or in Test Cell.Latency: <1 second Retention: “hours”Latency: <1 second Retention: “hours”
Local DatabaseLocal DatabaseFor real-time data analysis & actions. For real-time data analysis & actions.
Resident on Tester or in Test Cell.Resident on Tester or in Test Cell.Latency: <1 second Retention: “hours”Latency: <1 second Retention: “hours”
Adaptive Test Database Architecture ExampleAdaptive Test Database Architecture Example
DatabaseDatabaseData availability for production – lot setup or Data availability for production – lot setup or
dispositioning.dispositioning.Latency: “minutes” Retention: “hours to days”Latency: “minutes” Retention: “hours to days”
DatabaseDatabaseData availability for production – lot setup or Data availability for production – lot setup or
dispositioning.dispositioning.Latency: “minutes” Retention: “hours to days”Latency: “minutes” Retention: “hours to days”
Large DatabaseLarge DatabaseFor long-term storageFor long-term storage
Latency: “minutes”Latency: “minutes”Retention: “months” … with longer-term Retention: “months” … with longer-term
retrieval options. (data is available “forever”)retrieval options. (data is available “forever”)
Large DatabaseLarge DatabaseFor long-term storageFor long-term storage
Latency: “minutes”Latency: “minutes”Retention: “months” … with longer-term Retention: “months” … with longer-term
retrieval options. (data is available “forever”)retrieval options. (data is available “forever”)
World-wide, World-wide, cross-company cross-company
databasesdatabases
3D Device Testing Challenges
• Test Access• Die level Access• Die in Stack Access
• Test Flow/Cost/Resources• Heterogeneous Die in the Stack
• Die in Stack Testing• Die to Die Interactions
• Debug/Diagnosis• DFT• Test data managements, distribution, & security• Power Implications
SOC / Logic Update• Takes the device roadmap data and calculates:
• Fault Expectations both inside and outside the various cores using multiple fault models.
• Required test pattern lengths given five different assumptions:» Flat test patterns» Test implemented taking advantage of the circuit
hierarchy» Tests implemented using compressed flat patterns.» Tests implemented using compressed hierarchal test
patterns.» Using low power scan test approach.
LCD Device Probing Challenge OvercomeNew probe needle arrangement 4 layers + 4 layers = 8 layers
could provide solution for LCD driver probe pad continually narrow down.
Higher Site Count Camera Chips
Chief º
Max º
Max º
Min º
Chief ray
EP
D
D
Tan()= (D/2)/EPD
D=Pupil diameter
F-number = EPD / D
Single site Four sites
MEMs Sensors For Handheld DevicesGyro AccelerometersE-Compass Pressure
Expect a 10% yearly growth