INDUSTRY

Semiconductor / chips

From wafer to advanced packaging — micron-level device-appearance and character inspection.

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Wafer, advanced-packaging, device-appearance and OCR inspection.

Automatic defect classification post-AOI: missed-detection rate <2%, manual re-review cut by 90%, throughput up 30%.
Post-bonding defect detection: 98% combined detection rate, 2x faster inspection cadence, missed detections near zero.
Fast coverage of rare defect types: learns new defect types quickly — >96% detection with false calls around just 0.2%.
End-to-end back-end coverage: one AI vision stack spans wafer, advanced packaging, die placement and character OCR.

Recommended systems: 3D AI AOI · AOI software

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APPLICATION SCENARIOS

6 real-world scenarios, one at a time

Character & Mark Recognition

Chip Laser-Marking Character Inspection

Laser-marked characters carry critical model and batch-tracing information — the first line of defense for product traceability.

Die Attach Shift

Die Attach Void Detection

Voids from the die-attach process affect a chip's heat dissipation and electrical performance — a key risk point for packaging reliability.

Lithography & Development Defects

Lithography Pattern Defect Detection

Broken lines, shorts, and foreign-particle adhesion in lithography patterns directly affect chip yield.

Package Cracks & Delamination

Semiconductor Package Crack Detection

Cracks on the surface and edges of a package body can affect a chip's electrical performance and, in severe cases, cause outright failure.

Wafer Surface: Scratches / Particles / Chipping

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.

Wire Bonding / Gold Wire Inspection

Post-Wire-Bond Inspection

Wire bond quality directly affects chip electrical connection reliability and heat dissipation.

Case studies

Semiconductor / chips · wafer to package

From wafer auto-classification to wire-bond and advanced packaging — overkill goes down and defect escapes go to zero.

Scene · wafer ADC

A wafer fab · post-AOI auto defect classification

ChallengeConventional AOI overkill exceeds 20%; cleanroom re-judging is manual, scrapping good dies and inflating labour cost.

SolutionAI-ADC sorts true defects from nuisance; 3D AI-AOI plus the world model generalises across many defect classes.

<2%Overkill

−90%Man-to-machine

+30%Throughput

Scene · post wire-bond

A packaging house · post-bond inspection

ChallengeBond defects such as depressed wires cause major downstream failures if they escape; manual re-judging is low-throughput.

SolutionAI defect classification runs at the edge inside the AI-AOI machine, replacing image-by-image manual review.

98%Accuracy

×2Throughput

→0Escape rate

Scene · rare defects, few-shot

An advanced-packaging plant · covering rare defects fast

ChallengeAdvanced packaging keeps spawning new defect types; none have enough samples and traditional CNNs struggle to cover them.

SolutionAPDT positive-sample learning plus the DaoAI World model generalises to rare defects from only a handful of samples.

✓Few-shot

>96%Classification

~0.2%Escape rate

Cases are anonymised industry scenarios; the figures are typical ranges achievable with WeLinkirt DaoAI solutions.

In-depth cases · IN-DEPTH

Semiconductor / Chips · in-depth cases

Each case breaks down the path to deployment in a real scenario — industry context, pain points, the DaoAI solution and the results.

Semiconductor · 2026-06-16

Post-AOI Wafer Defect Auto-Classification: From Manual Review to AI-ADC

A wafer fab relied on manual AOI review with an overkill rate above 20%. With DaoAI AI-ADC, overkill dropped below 2%, review headcount fell 90%, and line throughput rose 30%.

Semiconductor chip laboratory inspection

Semiconductor · 2026-06-14

Post-Wire-Bond Inspection: Defect Models Pushed to the AI-AOI Edge

A packaging plant relied on manual visual inspection for post-bond defects like sagging wires, with occasional escapes. DaoAI embedded the defect model into the AI-AOI edge device: 98% accuracy, doubled throughput, near-zero escapes.

Semiconductor · 2026-06-12

Rare Defects in Advanced Packaging: Few-Shot APDT Positive-Sample Learning

At an advanced packaging plant, new-process defect samples were too scarce for conventional supervised models. DaoAI combined APDT positive-sample learning with world-model generalization: rare-defect classification above 96%, escapes around 0.2%.

DaoAI World foundation model neural network concept

Semiconductor · 2026-06-10

Advanced Packaging Bump Inspection: 3D AI-AOI Catches Missing Bumps and Bridging at Micron Level

At an advanced packaging plant, micro-bump missing and bridging were hard to separate by 2D grayscale. DaoAI 3D AI-AOI judges bump topography from micron-level height data, sharply improving missing and bridging detection.

Semiconductor · 2026-06-08

Lead Coplanarity and Dicing Chipping: 3D Vision Measures Height Per Lead

At a packaging plant, lead coplanarity and dicing chipping were hard to quantify in 2D. DaoAI 3D vision measures height per lead and checks chipping per edge, cutting both coplanarity escapes and chipping misses.

Semiconductor · 2026-07-05

AI Detection of Sunken Wires after Wire Bonding in Semiconductor Chips

In the semiconductor chip manufacturing process, wire bonding is one of the key processes, and the detection of sunken wires is crucial for ensuring chip

Semiconductor · 2026-07-08

AI Vision Detection of Semiconductor Chip Packaging Cracks Achieves Remarkable Results

In the process of semiconductor chip production, the detection of packaging cracks is crucial. WeLinkirt (DaoAI) provides an efficient solution for the

Semiconductor · 2026-07-06

AI Vision Inspection Results for Bump Missing/Bridge in Semiconductor

In the semiconductor chip manufacturing process, the quality inspection of bumps is crucial. WeLinkirt provides an efficient and precise inspection

Semiconductor · 2026-07-07

AI Vision Inspection Results for Particle and Scratch Classification in Semiconductor Chips

In the semiconductor chip production process, accurate classification and detection of defects such as particles and scratches are crucial

Semiconductor · 2026-07-08

Remarkable Results of AI Vision Inspection for Semiconductor Wafer Map Defect Patterns

In the semiconductor industry, wafer map defect inspection is a crucial step in ensuring product quality

Semiconductor · 2026-07-06

Remarkable Results of AI Vision Inspection for Semiconductor Chip Pin and Dicing Defects

In semiconductor chip production, the inspection of pin and dicing defects is crucial. WeLinkirt (DaoAI) uses advanced AI vision technology to provide an

Semiconductor · 2026-07-07

Local Deployment Solution for Die Attach Void Detection in Semiconductor Industry

In the semiconductor industry, void detection in the die attach process is crucial. WeLinkirt provides a locally deployed detection solution for a leading

Semiconductor · 2026-07-08

New Breakthrough in Semiconductor Chip Laser Marking Character Detection

In semiconductor chip production, the detection of laser - marked characters is crucial. WeLinkirt brings new changes to the industry with advanced

Semiconductor · 2026-07-07

Online 100% Inspection Solution for Semiconductor Wafer Edge Defects

In the semiconductor industry, the inspection of wafer edge defects is crucial. Traditional sampling inspection methods are difficult to meet the

Semiconductor · 2026-07-06

Remarkable Results of AI Vision Inspection for Semiconductor Lithography Pattern Defects

In the semiconductor chip manufacturing process, the inspection of lithography pattern defects is crucial

Semiconductor · 2026-07-05

Rare Defect Few - Sample Detection Solution for Semiconductor Advanced Packaging

In the field of semiconductor advanced packaging, the detection of rare defects with few samples is an industry challenge

Semiconductor · 2026-07-05

Semiconductor Wafer ADC Solution after AOI Inspection

In the semiconductor chip manufacturing process, the quality inspection of wafers is crucial. Accurately classifying defects after AOI inspection is a key

FAQ

Semiconductor / Chip · AI Visual Inspection FAQ

What defects can AI vision detect in semiconductor manufacturing?

These include wafer surface scratches and particles, wire-bond quality, dicing chipping, missing or bridged bumps, coplanarity, and automatic defect classification (ADC) of rare defects. DaoAI stays stable under low-contrast, high-resolution conditions.

Rare defects are hard to collect, how can AI be trained with few samples?

DaoAI supports few-shot and unsupervised anomaly detection, modeling from good units or very few defect samples, and can flag never-before-seen rare defects as anomalies.

Can automatic defect classification (ADC) replace manual review?

Largely, yes. DaoAI ADC auto-classifies and grades defects, sharply reducing manual review so engineers focus only on a few high-risk categories, improving SPC decisions.

High-resolution inspection produces huge data, can it run on-premise to protect process IP?

Yes. DaoAI supports fully on-premise deployment, keeping models and wafer data inside the fab to meet strict process-IP and compliance requirements.