Wafer defect map & binning
Detect, locate, size, and bin defects across a wafer into a spatial map.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Results
Each measurement below comes from your own images, tied back to the annotated frame it came from, so results stay comparable across samples, locations, and conditions.
µm or count
Defect count
Size and shape measured for every detected object, then summarized across the population.
Example, not a claimed result
In your report: Per-object table, size distribution, and summary percentiles.
per area
Wafer map
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
class
Defect class bins
Each detected feature assigned to a class using the agreed rule set, shown on the image.
In your report: Per-feature class, counts by class, and annotated overlays.
µm or count
Size distribution
Size and shape measured for every detected object, then summarized across the population.
In your report: Per-object table, size distribution, and summary percentiles.
per area
Cluster / signature flags
Findings placed in sample coordinates to reveal spatial patterns and local density.
Example, not a claimed result
In your report: Coordinate-referenced map, regional density, and representative images.
Built around your image set
Use the calibrated images your team already collects, together with the locations you need to compare.
Each report includes
The artifacts your team receives, ready for review and archive.
Annotated image set
Original images with regions of interest, measurement points, masks, and finding overlays.
Measurement table
Location-indexed values, units, distributions, and QC flags in a structured export.
Method record
Calibration evidence, analysis settings, version history, and validation summary.
Confidence in every resultTraceable measurements, reviewed against your agreed reference method.
- Traceable scale
- The report records the image scale, calibration evidence, and a method-specific expanded measurement uncertainty. It does not use one product-wide accuracy number.
- Reference comparison
- The configured method is compared with your accepted reference method or reviewed annotations, and reports bias by measurement range and image condition.
- Detection performance
- Detections are evaluated against reviewed reference regions with precision, recall, and segmentation overlap, separated by the conditions that affect performance.
- Repeatability
- The locked protocol is rerun on the same inputs and on a defined repeat set. The review records variation from image acquisition, sampling, and analysis separately where possible.
What this result does not establish: Detects and classifies defects visible in the images provided. Killer-versus-nuisance calls depend on your device rules and should be confirmed against electrical test.
The measurement, today
Defects are reviewed one image at a time and tallied on a sheet. Spatial signatures such as edge rings, radial scratches, and cluster hot spots only emerge when someone plots them by hand.
What it costs
The pattern of defects across a wafer points at the tool that caused them. Without a fast map, a drifting chamber keeps printing scrap while review works through a backlog.
From image to reviewed result
- 1
Scan the wafer
Tile optical or SEM images across the wafer surface.
- 2
Detect and size
Every defect is segmented, located, and measured.
- 3
Bin by class
Defects are sorted into classes such as particle, scratch, and pattern defect.
- 4
Map and flag
Defects are plotted to wafer coordinates and spatial signatures are flagged.
Not sure this is the right measurement?
Send a representative image and your measurement goal. A ConductVision scientist will confirm whether this is the right fit, or point you to the closer workflow, before you commit to a quote.
Related applications
Semiconductor defect patterns
Classify wafer-map patterns and quantify defect clusters and densities.
Critical dimension (CD) metrology
Line width, space, and via diameter measured from top-down images, with per-feature tables.
Photoresist pattern defects
Detect resist pattern collapse, bridging, footing, and scumming after develop.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
