High-volume data
Semiconductor test can generate large datasets across many devices, parameters and test stages.
Semiconductor Test
Semiconductor Test Data Management
Structure semiconductor test data for yield analysis, binning, failure investigation, reliability and production quality workflows.
What is semiconductor test data management?
Semiconductor test data management structures wafer test, package test, binning, reliability and characterisation data so teams can analyse yield, lots, wafers, devices and failure patterns. It helps connect high-volume test results to production quality and engineering workflows.
Test data management for semiconductor teams
Semiconductor and microelectronics teams generate test data across wafer test, package test, reliability, characterisation, qualification and production workflows.
The value of that data depends on how well it can be connected to yield, binning, lots, wafers, devices, test conditions and quality outcomes.
Common semiconductor test data challenges
Yield and binning complexity
Teams need to understand how test results map to yield, bins, lots, wafers and product performance.
Multi-stage testing
Results may come from wafer sort, final test, reliability testing and characterisation workflows.
Failure analysis context
Failure investigation depends on connecting measurements to product, process, lot, wafer, package and test condition.
Data reuse
Engineering, manufacturing and quality teams may need to use the same test data for different decisions.
Key use cases
Yield analysis
Understand yield patterns across wafers, lots, products and test stages.
Binning analysis
Analyse bin distributions and identify abnormal shifts.
Reliability testing
Connect reliability results to product, lot, condition and test history.
Failure analysis
Trace failures back to measurement, process, lot, wafer or device-level context.
Production quality
Use test data to support release, quality monitoring and customer evidence workflows.
What semiconductor test data should capture
- Product or device ID
- Wafer, lot or batch
- Package or assembly context
- Test stage
- Test program version
- Test conditions
- Measurement values
- Limits
- Bin result
- Pass/fail result
- Timestamp
- Equipment or handler context
- Reliability or qualification context
How Arc helps
Arc helps semiconductor and microelectronics teams structure test data so it can support analysis, traceability and quality workflows.
The focus is on making test data more usable across engineering, production and quality teams.
FAQ
What is semiconductor test data management?
It is the process of structuring, analysing and reusing test data from wafer test, package test, reliability and characterisation workflows.
Why is semiconductor test data difficult to manage?
It can be high-volume, multi-stage and highly dependent on product, lot, wafer, binning and test condition context.
Can test data management help with yield?
Yes. Structured data helps teams analyse yield patterns across lots, wafers, devices and test stages.
What is binning data?
Binning data classifies devices based on test outcomes or performance characteristics.
Who uses semiconductor test data?
Test engineering, product engineering, yield engineering, manufacturing, quality and reliability teams all use semiconductor test data.
Request Access
Bring an example of your current test data workflow and we’ll map where results, failures, limits, traceability and quality evidence are getting lost.
Request Access