MAKE | Supply Chain Analytics
Computer Vision for defect detection
Machine Learning in Quality Control applies AI algorithms to monitor, analyze, and improve product quality in manufacturing.
Higher standard of product quality through precise AI-driven inspections.
Reduce costs from defects, recalls, and manual inspection labor.
Streamline quality control for faster production cycles.
Precise positioning for pick & place
Identify irregularities in products
Automated inspection on production lines
Check color, size, integrity
Large-scale label verification
PPE compliance & hazard detection
Convolutional Neural Networks designed to quickly and accurately find problems in microchips using sound wave images.
This ML application is more efficient and accurate than previous methods, representing a significant step in using advanced technology for quality assurance.
Automatically identify defects from product images
Localize defects by distinguishing parts within images
Anomaly detection via reconstruction errors
Leverage pre-trained models with limited data
% failing quality standards
ML model precision in identifying defects
Products meeting criteria without rework