Real-Time Defect Detection

Technology Overview

Machine Vision-Based Inline Quality Control (QC) is an automated machine learning-based vision inspection system. For manufacturing lines, vision inspection system is one of the critical QC tools. It is implemented to screen out defective components and parts to ensure good product quality.

The platform automatically detects complex defects that may not be addressed by traditional machine vision methods.

AI-powered inline QC detects complex defects in real-time, offers seamless AOI integration, visual analytics, and eco-friendly coating with ensuring precision, sustainability, and manufacturing excellence.

Key Features

• Defect Classification

  Real-time quality inspection with an AI-based classification model to determine complex and irregular defects.

• Defect Detection and Analysis

  Real-time quality inspection with an AI-based defect detection to detect defect properties such as location, size and type on visible and non-visible light images.

• Annotation and Training Tool

  The platform comes equipped with capabilities for annotation, model training, evaluation and reporting.

• Third Party Automated Optical Inspection (AOI) Integration

  An interface is provided for third party system integration.

Technology Benefits

• Machine Learning Defect Detection Algorithm

  The machine learning algorithm is customised to generate predictive models. This allows defect classification and detection on complex defects that may not be addressed by classic rule-based algorithms.

• Model Training Visualisation and Reporting

  The platform provides customised model training and evaluation with visualisation and reporting.

Machine Vision-Based Inline Quality Control (QC) is an automated machine learning-based vision inspection system. It provides image analytics and complex defect detection capabilities for inline QC inspection in the manufacturing industry.