Wafer edge, bow & warp inspection
Locate edge chips and measure image-derived edge geometry before handling, lithography, or packaging.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Image: Illustrative rendering (AI-generated, gpt-image-2), not a photograph of a specific wafer
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.
per area
Edge-chip map
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.
nm or µm
Chip length & depth proxy
Perpendicular distance between the defined boundaries at each accepted measurement point.
Example, not a claimed result
In your report: Per-point values with median, spread, minimum, maximum, and location.
per area
Edge exclusion zone
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
per area
Bow / warp profile
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: Reports geometry from calibrated image or profilometry inputs. Use your qualified tool and site method for any handling, process, or acceptance limit.
The measurement, today
Edge damage and wafer geometry are often logged as separate pass/fail checks. The image evidence is not consistently retained, and a small edge chip can be missed until a handling or coating issue appears.
What it costs
Edge defects can seed breakage, handling failures, and exclusion-zone losses. Geometry trends are more useful when tied back to the actual wafer image and lot.
From image to reviewed result
- 1
Image the edge
Capture the edge and exclusion zone with your edge-inspection or optical-profilometry system.
- 2
Register the wafer
Align the edge image set to wafer coordinates so each finding keeps its angular location.
- 3
Measure findings
Segment chips and visible edge damage, then calculate the configured bow or warp profile from the supplied geometry images.
- 4
Export the record
Deliver an image-linked defect list and geometry summary for review.
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
Silicon ingot & wafer quality
Review crystal-origin defects, surface particles, and saw damage before wafers enter the process flow.
Wafer defect map & binning
Detect, locate, size, and bin defects across a wafer into a spatial map.
CMP scratch & planarization inspection
Locate scratches, residual particles, dishing, and erosion signatures after chemical mechanical planarization.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
