Semiconductor / Chips · APPLICATION SCENARIO

Wafer Surface Particle & Scratch Classification

During packaging, particles and scratches on the wafer surface vary widely in form — a frequent source of yield-affecting defects.

Scenario · Wafer Surface: Scratches / Particles / Chipping

Wafer Surface Particle & Scratch Classification

Challenge & Solution

Wafer Surface Particle & Scratch Classification

ChallengeTraditional inspection missed up to 3% of defects with a 20% false-positive rate, and every changeover required 30+ minutes of manual tuning.

SolutionVision foundation model plus APDT positive/few-shot learning: 1–20 good samples enable zero-code modeling in 5 minutes.

99.2%Detection rate
-85%False positive rate
<0.8%Missed detection rate
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This article was generated by AI. Customer cases are simulated scenarios based on real product capabilities and figures are illustrative; see product pages for official benchmarks.

FAQ

What's the biggest challenge in Wafer Surface Particle & Scratch Classification?

Traditional inspection missed up to 3% of defects with a 20% false-positive rate, and every changeover required 30+ minutes of manual tuning.

How does DaoAI solve this?

Vision foundation model plus APDT positive/few-shot learning: 1–20 good samples enable zero-code modeling in 5 minutes.

What results can this deliver?

In real production deployments, Detection rate reaches 99.2%, False positive rate reaches -85%, and Missed detection rate reaches <0.8% (case studies are simulated scenarios based on real product capabilities; see product pages for official benchmarks).

How much does Wafer Surface Particle &amp; Scratch Classification typically cost?

Wafer Surface Particle &amp; Scratch Classification pricing depends on production-line scale, number of inspection points, and deployment mode (cloud/edge/on-premise); configurations vary significantly by customer, so we don't publish a fixed price list. Book a demo for a quote and implementation timeline tailored to your setup.