Machine Vision

The industrial problem

An inconsistent image cannot support a consistent inspection. Glare, motion blur, changing backgrounds and part position can overwhelm even a well-designed algorithm.

The solution approach

Engineer the image-acquisition conditions before choosing the inspection method. Use rules-based vision for stable features and evaluate AI when appearance variation makes fixed rules unreliable.

Reference architecture

Illustrative sequence. Interfaces and timing are specified for the actual equipment and process.

Typical applications

• Automated quality inspection and presence checks
• Surface defect detection and object classification
• OCR / code reading and label verification
• Measurement and metrology with calibration
• Camera-based sorting and position detection

Expected business value

Repeatable inspection criteria and records that support root-cause analysis. Measurement uncertainty and error rates need validation on representative parts.

What needs validation

• Evaluate lighting, lens, field of view and exposure at the intended line speed.
• Test good, defective and borderline samples separately.
• Measure repeatability and calibration stability where dimensional results matter.