PCB Defect Detector

Overview

PCB Defect Detector is an AI-powered quality control system designed to automatically detect defects on printed circuit boards (PCBs). Using advanced computer vision and deep learning techniques, it identifies manufacturing defects with high accuracy, reducing manual inspection time and improving production quality.

The Problem

Manual PCB inspection is:

• Time-consuming: Human inspectors can only check a limited number of boards per hour
• Error-prone: Fatigue leads to missed defects, especially for small components
• Expensive: Requires trained personnel and slows down production
• Inconsistent: Quality varies between inspectors and shifts

The Solution

PCB Defect Detector automates the inspection process using AI:

• Real-time Detection: Analyze PCB images in milliseconds
• High Accuracy: Deep learning models trained on thousands of defect samples
• Multiple Defect Types: Detects solder bridges, missing components, misalignment, and more
• Easy Integration: REST API for seamless integration with production lines

Defect Types Detected

1. Solder Bridges: Unwanted connections between pads
2. Missing Components: Empty pads where components should be placed
3. Misaligned Components: Components not properly centered on pads
4. Tombstoning: Components standing on one end
5. Cold Solder Joints: Poor solder connections
6. Scratches & Damage: Physical damage to the PCB surface

Technology Stack

• Deep Learning: TensorFlow / PyTorch
• Computer Vision: OpenCV
• Backend: Python, FastAPI
• Model Architecture: YOLO / ResNet for object detection
• Training Data: Custom dataset with augmentation

How It Works

1. Image Capture: High-resolution camera captures PCB image
2. Preprocessing: Image normalization and enhancement
3. Detection: AI model analyzes the image for defects
4. Classification: Each defect is categorized by type and severity
5. Reporting: Results sent to quality control dashboard

Performance Metrics

Metric	Value
Accuracy	>95%
Processing Time	<100ms per board
False Positive Rate	<2%
Defect Types	6+ categories

Use Cases

• Electronics Manufacturing: Automated quality control on production lines
• PCB Prototyping: Quick validation of prototype boards
• Repair Services: Identify issues in faulty boards
• Education: Teaching tool for electronics students