Sanezoo Catalog

 Visual quality control • 3d picking & feeding • Robotic inspection

Surface Pore Detection

AI-Powered Inspection of Machined Surfaces for Micro-Defects

Overview

This neural network uses artificial intelligence to detect pores and surface defects on machined parts. High-resolution images are divided into multiple inspection zones and analyzed by a neural network trained specifically for surface imperfection detection.

Why It Matters

Microscopic pores can compromise the integrity, hygiene, or functionality of parts, especially in sectors where flawless surfaces are critical. Manual inspection is time-consuming and prone to errors; automated AI-based analysis ensures speed, precision, and consistent quality.

Where It’s Used

  • Healthcare / Medical
  • Chemical Production
  • Food and Beverage
  • Biolabs
  • Automotive
  • Aerospace

Capabilities

  • AI-powered defect detection
  • Detection of surface pores on machined parts
  • Supports multi-zone inspection from a single image
  • Adjustable sensitivity and defect thresholds
  • High accuracy, low false alarm rate

High-Precision Identification of Porosity on Critical Surfaces

Microscopic Void Analysis on Machined Surfaces

This view shows a surface containing visible
microscopic pores. These discontinuities
are automatically detected and measured.
If their size, count, or density exceeds
tolerances, the part is marked as NOK.

Example Use Case

A manufacturer of medical components uses this neural network to inspect milled surfaces. Each captured image is split into zones, and pores, even as small as a few hundred microns are automatically identified. The system flags only true defects, minimizing false positives and reducing manual rework.