CMP scratch & planarization inspection
Locate scratches, residual particles, dishing, and erosion signatures after chemical mechanical planarization.
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
Scratch map
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
µm or count
Particle 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
Dishing / erosion regions
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
% area
Affected-area fraction
Segmented area of the feature divided by the eligible area in the two-dimensional image.
Example, not a claimed result
In your report: Per-field value, size distribution, and the segmentation overlay used.
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: Flags surface features visible to the supplied imaging modality. Dishing, erosion, and film thickness need a calibrated reference method before being used as process-release measurements.
The measurement, today
CMP review is commonly a visual screen followed by manual annotation. Fine scratches and spatial trends can be hard to compare across pads, slurries, and lots.
What it costs
Planarization defects can carry into subsequent patterning and interconnect steps. Image-linked defect classes make a pad or consumable comparison easier to review.
From image to reviewed result
- 1
Load post-CMP images
Upload optical, darkfield, or profilometry images from the wafer locations under review.
- 2
Separate surface features
Detect linear scratches, particle-like features, and regions with a different planarization signature.
- 3
Measure the distribution
Record feature dimensions, affected area, and field or wafer position.
- 4
Review by lot or condition
Export annotated images and summary tables for pad, slurry, and process comparison.
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
Wafer edge, bow & warp inspection
Locate edge chips and measure image-derived edge geometry before handling, lithography, or packaging.
Thin-film step coverage & uniformity
Quantify layer thickness and step coverage across planar and topographic semiconductor features.
Wafer defect map & binning
Detect, locate, size, and bin defects across a wafer into a spatial map.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
