An approach to improving production tests for large scale IC production

2. Design to Target
Datasheet Specifications
Ownership : IC Design and
Verification Team
ATE Testing and
Verification
Ownership : Test Team
Data generated: 140K data points
(1K ICs/month x 140 tests/IC)
Production Testing and
Data Collection
Ownership : Production and QA
Data Generated: 20M data points
(20K ICs/month x 100 tests/IC)

3. Design to Target
Datasheet Specifications
Ownership : IC Design and
Verification Team
ATE Testing and
Verification
Ownership : Test Team
Data generated: 140K data points
(1K ICs/month x 140 tests/IC)
Production Testing and
Data Collection
Ownership : Production and QA
Data Generated: 20M data points
(20K ICs/month x 100 tests/IC)
Pass Fail
Test Outcomes are binary and deterministic
Test thresholds are static and must be
manually adjusted

4. Design Product to Target
Datasheet Specifications
Ownership : IC Design and
Verification Team
ATE Testing and
Verification
Ownership : Test Team
Data generated: 140K data points
(1K ICs/month x 140 tests/IC)
Production Testing and
Data Collection
Ownership : Production and QA
Data Generated: 20M data points
(20K ICs/month x 100 tests/IC)
Pas
s
Fail
Test Outcomes are binary and deterministic
Test thresholds are static and must be
manually adjusted
In production, where the environment may vary due
several reasons, these static thresholds result in
yield losses which delay product release significantly.
Also results in engineering and marketing time and
resources to firefight customer issues

5. Feed production data
back to test environment
Train ML models with
production data to
account for variability
Dynamically adjust production
thresholds based on predicted
production environment
variability
Detrend data using difference
in differences to detect true
product failures
Back test model across multiple
environments to discern
sources of false failures

6. Test Passes
Test Fails
Test
Environmental
variables
Design variables Test outcomes
Dependent variable (binary)Independent variables
Environment settings
Equipment configs
ATE variability
Calibration routines
Design constraints
Process variations
System variables
Fixed
Threshold

7. Test Passes
Test Fails
Test Environmental
variables
Design variables Test outcomes
Dependent variable (binary)Independent variables
Environment settings
Equipment configs
ATE variability
Calibration routines
Design constraints
Process variations
System variables
Variable
Threshold