Project Overview

Automated Defect Classification (ADC) 2.0 project aims to improve the accuracy and efficiency of defect detection across multiple inspection platforms, including ATI Wind, Dragonfly, and Sam Scan. The primary goal is to train advanced ADC models and validate their performance to ensure consistent and reliable defect classification in the production line.

Responsibilities

• Engage with multiple teams and departments (Engineering, IT, QA, SMAI) to gather expertise for model training.
• Use RDAViewer for data verification to ensure the integrity of training datasets.
• Collect and analyze defect data to qualify ADC models according to performance standards.
• Continuously optimize ADC models based on feedback and metrics.
• Ensure seamless integration of ADC models across ATI Wind, Dragonfly, and Sam Scan.
• Provide training sessions for team members on using and interpreting ADC models.
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