Semiconductor Wafer Test Data with TofuPilot

Semiconductor testing happens in two stages: wafer-level testing (CP, circuit probe) and final test (FT, packaged parts). Each stage generates massive datasets. TofuPilot stores per-die and per-part test results with full measurement data, enabling yield analysis, bin mapping, and lot traceability.

Semiconductor Test Flow

Wafer Fab → Wafer Test (CP) → Packaging → Final Test (FT) → Binning → Ship
                 ↓                              ↓
            TofuPilot                       TofuPilot
         (per-die data)                 (per-part data)

Wafer Test (Circuit Probe)

Probes contact each die on the wafer. Tests include:

Test	What it checks
Continuity/opens	Bond pad connectivity
Leakage	Junction and oxide integrity
Parametric	Vth, Idsat, Rds(on), timing
Functional	Basic digital/analog operation

Final Test (FT)

After packaging, full parametric and functional testing at speed.

Test	What it checks
DC parametric	Input/output levels, power consumption
AC parametric	Speed, setup/hold times, rise/fall times
Functional	Full device operation at target frequency
Burn-in (optional)	Infant mortality screening

Logging Wafer Test Data

Per-Die Results

wafer_test.py

from tofupilot import TofuPilotClient

client = TofuPilotClient()

def log_die_test(wafer_id, die_x, die_y, measurements, bin_code):
    """Log test results for a single die."""
    die_id = f"{wafer_id}-X{die_x}Y{die_y}"

    steps = [{
        "name": "Parametric",
        "step_type": "measurement",
        "status": bin_code == 1,  # Bin 1 = good die
        "measurements": [
            {"name": "vth_mv", "value": measurements["vth"], "unit": "mV", "limit_low": 350, "limit_high": 450},
            {"name": "idsat_ua_um", "value": measurements["idsat"], "unit": "uA/um", "limit_low": 500, "limit_high": 700},
            {"name": "ioff_pa_um", "value": measurements["ioff"], "unit": "pA/um", "limit_high": 100},
            {"name": "rdson_mohm", "value": measurements["rdson"], "unit": "mohm", "limit_high": 50},
        ],
    }]

    client.create_run(
        procedure_id="WAFER-CP-TEST",
        unit_under_test={
            "serial_number": die_id,
            "part_number": "IC-POWER-MGMT-V3",
        },
        run_passed=bin_code == 1,
        steps=steps,
    )

# Test all dies on a wafer
wafer_id = "LOT2025A-W07"
for x in range(20):
    for y in range(20):
        meas = probe_die(x, y)
        bin_code = classify_die(meas)
        log_die_test(wafer_id, x, y, meas, bin_code)

Wafer-Level Summary

After testing all dies, upload a wafer summary.

wafer_summary.py

# Wafer-level summary
total_dies = 400
good_dies = 352
yield_pct = good_dies / total_dies * 100

client.create_run(
    procedure_id="WAFER-CP-SUMMARY",
    unit_under_test={
        "serial_number": "LOT2025A-W07",
        "part_number": "IC-POWER-MGMT-V3",
    },
    run_passed=yield_pct > 80,
    steps=[{
        "name": "Wafer Summary",
        "step_type": "measurement",
        "status": yield_pct > 80,
        "measurements": [
            {"name": "total_dies", "value": total_dies, "unit": "count"},
            {"name": "good_dies", "value": good_dies, "unit": "count"},
            {"name": "cp_yield_pct", "value": yield_pct, "unit": "%", "limit_low": 80},
            {"name": "bin1_count", "value": 352, "unit": "count"},
            {"name": "bin2_count", "value": 30, "unit": "count"},
            {"name": "bin3_count", "value": 18, "unit": "count"},
        ],
    }],
)

Bin Mapping

Binning assigns each die or part to a category based on test results. Common bin structure:

Bin	Meaning	Typical criteria
1	Good, full spec	All parametrics within spec
2	Good, derated	Parametrics within wider limits
3	Functional fail	Failed functional test
4	Parametric fail	One or more parametric out of spec
5	Continuity fail	Open or short detected
6	Leakage fail	Excessive junction leakage

Track bin distributions in TofuPilot across wafers, lots, and time periods.

Yield Analysis

Wafer-to-Wafer Yield

Compare CP yield across wafers in a lot.

Wafer	Total dies	Good (Bin 1)	Yield
W01	400	360	90.0%
W02	400	355	88.8%
W03	400	312	78.0%
W04	400	358	89.5%

W03 has significantly lower yield. Investigate wafer-level process issues (particle count, lithography focus, etch uniformity).

Lot-to-Lot Yield

Track yield across production lots to monitor fab process stability.

lot_yield_tracking.py

from tofupilot import TofuPilotClient

client = TofuPilotClient()

# Get all wafer summary runs
runs = client.get_runs(
    procedure_id="WAFER-CP-SUMMARY",
    limit=100,
)

# Group by lot and calculate average yield
lot_yields = {}
for run in runs:
    serial = run["unit_under_test"]["serial_number"]
    lot = serial.split("-W")[0]  # Extract lot ID
    for step in run.get("steps", []):
        for m in step.get("measurements", []):
            if m["name"] == "cp_yield_pct":
                if lot not in lot_yields:
                    lot_yields[lot] = []
                lot_yields[lot].append(m["value"])

for lot, yields in sorted(lot_yields.items()):
    avg = sum(yields) / len(yields)
    print(f"{lot}: {avg:.1f}% avg yield ({len(yields)} wafers)")

CP to FT Yield Correlation

Track yield at both test stages to find packaging-related issues.

Lot	CP Yield	FT Yield	FT/CP Loss
LOT2025A	89.2%	87.1%	2.1%
LOT2025B	91.0%	88.5%	2.5%
LOT2025C	90.5%	82.3%	8.2%

LOT2025C shows excessive CP-to-FT yield loss (8.2% vs. typical 2-3%). This points to a packaging issue: wire bond failures, die attach problems, or moisture sensitivity during assembly.

Parametric Distribution Monitoring

Track critical parametric distributions across production to catch process drift.

Key parameters to monitor:

Parameter	Why it matters
Vth (threshold voltage)	Shifts indicate gate oxide or implant dose issues
Idsat (saturation current)	Indicates transistor drive strength
Ioff (off-state leakage)	Affects standby power, process control indicator
Rdson (on-resistance)	Critical for power devices
Timing margins	Speed grading, binning into speed grades

TofuPilot's measurement histograms show the distribution of each parameter across all tested dies. A bimodal distribution suggests two different process conditions. A shifting mean suggests process drift.

Traceability from Part to Wafer

When a packaged part fails in the field, trace back:

Part serial number → packaging lot
Packaging lot → wafer ID
Wafer ID → die position (X, Y)
Die position → original CP test data

All of this data lives in TofuPilot, linked by serial numbers. Was the die marginal at wafer test? Was it a Bin 2 (derated) part sold as Bin 1? The data answers these questions.

Semiconductor Wafer Test Data with TofuPilot