Advanced Chip Die Defect Detection with Object Detection AI | ASMPT Case Study

Executive Summary

ASMPT revolutionized semiconductor manufacturing quality control with AI-powered chip die defect detection, achieving 99.5% accuracy and reducing inspection time by 80% through advanced object detection algorithms.

Challenge

ASMPT, a leading semiconductor equipment manufacturer, faced quality control challenges in their wire bonding process. Manual inspection of chip dies for defects was time-consuming, inconsistent, and prone to human error, leading to potential quality issues and increased manufacturing costs.

Solution

We developed a sophisticated computer vision system using state-of-the-art object detection algorithms specifically designed for semiconductor manufacturing:

Technical Implementation

Deep Learning Models: Custom-trained YOLO-based detection models optimized for microscopic defect identification
Data Pipeline: Automated image acquisition and preprocessing pipeline for high-resolution chip die images
Real-time Processing: Edge computing deployment for millisecond-level defect detection
Integration: Seamless integration with existing wire bonding equipment and manufacturing execution systems

Key Features

Multi-class defect detection (scratches, cracks, contamination, misalignment)
Sub-pixel accuracy positioning for precise defect localization
Automated quality reporting and statistical process control
Customizable detection thresholds based on product specifications

Results

The AI-powered defect detection system delivered exceptional results:

99.5% Detection Accuracy: Surpassing human inspection capabilities
80% Reduction in manual inspection time
50% Decrease in false positive rates compared to traditional methods
Real-time Processing: Sub-second detection times enabling inline quality control
ROI Achievement: 8-month payback period through reduced labor costs and improved yield

Technologies Used

Computer Vision: OpenCV, PyTorch
Machine Learning: Custom object detection models, transfer learning
Hardware Integration: Industrial cameras, edge computing devices
Software: Python, C++, REST APIs for system integration

Impact

The successful deployment at ASMPT’s facility demonstrated the transformative power of AI in semiconductor manufacturing, establishing a new standard for automated quality control in the industry.