Disruptive technology: from "human eye limit" to "quantum-level insight"
Nano-level defects are nowhere to hide
Using multi-spectral fusion technology, it can identify "ghost defects" such as 2μm invisible pinholes in lithium battery diaphragms and 0.5° angle deviation of chip solder joints, which is 100 times more sensitive than traditional optical detection (actual data of a Top3 power battery factory)
Ultra-high-speed decision engine
The self-developed FPGA+GPU heterogeneous computing architecture completes 128-layer convolutional neural network reasoning within 3 milliseconds, and the production line detection speed exceeds 120 meters/minute, saving 90% of the sampling downtime for continuous production of automotive steel plates
Zero-sample cold start
Based on the virtual defect amplification technology of generative adversarial network (GAN), without the need for massive defective product training data, the launch cycle of new product category models is compressed from 3 months to 72 hours
Landing crit: "killer application" in the trillion-dollar track
New energy field
In the seventh-generation production line of CATL, the system captures the 0.08mm tab folding defect , avoiding a single potential loss of more than 200 million yuan
The accuracy rate of photovoltaic EL crack detection is 99.998%, and 3,000 hours of rework time are reduced for each GW of production capacity
Precision electronic manufacturing
The detection misjudgment rate of iPhone camera modules has dropped from 3% to 0.005%, and the Apple supply chain yield assessment compliance rate has increased by 40%
Samsung Semiconductor has achieved fully automatic grading of 12-inch wafers, reducing labor costs by 70%
Breakthrough in heavy industry
China Commercial Aircraft Corporation C919 fuselage rivet AI quality inspection system, with a detection speed 200 times faster than manual inspection and a fatigue damage recognition rate of 100%
Ecological game: cracking the "impossible triangle" of large-scale deployment
Computing power cost cliff
Through model distillation technology, 200 layers of ResNet are compressed to a 5-layer lightweight network, and the edge device deployment cost is reduced by 80%
Adversarial sample attack and defense
Introducing the blockchain-based federated learning mechanism for defective samples to prevent false detection vulnerabilities caused by malicious attacks, and pass ISO/IEC 15408 safety certification
Cross-border knowledge transfer
Automobile steel plate detection model quickly adapts to photovoltaic glass scenarios, and customers' secondary development costs are reduced by 95%
Conclusion:
When 0.001% is no longer a number, but the cornerstone of the reconstruction of trust in the manufacturing industry, deep visual quality inspection is setting off a "zero defect revolution". Those companies that first deployed the "defect hunter" system have seized the decisive high ground at the nano level in this global quality war.
