Manufacturing QC Visual Inspection

Business Challenge

Manufacturing lines struggle with manual defect detection — slow, error-prone, and costly — while quality teams lack real-time visibility into production anomalies.

Our Solution

Automated visual inspection system using deep learning (YOLO + ResNet) to detect surface defects in real time, reducing false negatives by 94% and cutting QC labor costs by 60%.

CV Inspection Pipeline

• Image Capture — HD cameras @ 60fps
• Preprocessing — noise reduction, normalization
• Defect Detection — YOLOv8 inference <12ms/frame
• Result Output — dashboard alert + auto-reject

Tech Stack

• Python
• PyTorch
• YOLOv8
• OpenCV
• NVIDIA Triton Inference Server
• FastAPI
• Docker
• AWS S3