AOI System for iPhone MIC Hole Inspection

Small defect detection · Tight tolerance · High precision

Overview

Inspection pipeline targeting mic-hole region defects with tight tolerance requirements. System handles small features and challenging reflections for reliable quality control.

🎯 Small Defects 👁️ AOI Python OpenCV PyTorch

Problem

  • Mic-hole defects are typically very small.
  • Tight tolerance requires high detection precision.
  • Reflective surfaces create challenging conditions.
  • Need for zero false negatives in production.

Solution

  • AOI pipeline optimized for small defect detection.
  • Improved robustness for small features and reflections.
  • High-resolution inspection with precision localization.
  • Validated against stringent Apple quality standards.

My Role

  • Built AOI pipeline for mic-hole defect detection and validation.
  • Improved robustness for small features and reflections.
  • Optimized system for production deployment.

Implementation

Language: Python

Libraries:

OpenCV PyTorch

Results Gallery

Training and evaluation demonstrations are omitted due to data confidentiality.

End Result

  • High-precision mic-hole inspection ready for deployment.
  • Reliable detection of small defects with tight tolerances.
  • Deployed successfully in Apple production line.