Implemented defect detection on production lines using convolutional neural networks to identify microscopic flaws in electronic components with 99.2% accuracy.
Electronics manufacturer needed to detect microscopic defects in components at production speed, requiring precision beyond human capability.
Deployed CNN-based computer vision system for real-time defect detection, processing 1,000 units per minute with sub-micron precision.
Achieved 99.2% defect detection accuracy while reducing quality control costs by 60% and eliminating defective products reaching customers.