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The Procunit Blog

Technical writing on machine vision inspection, defect escape rate, false positive analysis, PLC integration, and what it actually takes to train a model on a small defect dataset. Written by quality engineers and ML engineers who work on production lines.

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Worker inspecting parts on a fast production line, illustrating limitations of manual visual inspection

Why Manual Visual Inspection Fails Above 100 Parts Per Minute

The physiological limits of human visual inspection — and what the data says about escape rates on high-speed lines.

Grid of labeled defect image samples for machine learning training data

Training Defect Detection Models with 50 Samples

Why few-shot defect detection works in manufacturing — and how to curate a 50-image set that generalizes.

Close-up of stamped metal part surface showing edge cracks and surface scoring defects under ring illumination

Surface Defect Types in Stamped Metal Components

Edge cracks, burrs, scoring, and dimensional drift — a field reference for quality engineers on stamping lines.

Industrial PLC control cabinet with Ethernet cables and indicator lights in a factory environment

Integrating AI Vision with PLC Reject Systems

Ethernet/IP, Modbus TCP, and discrete I/O — comparing PLC interface methods for AI vision reject signals.

Reject bin on factory floor with good parts incorrectly flagged by automated optical inspection system

The Real Cost of False Positives in Automated Optical Inspection

How every false reject adds cost — rework, operator time, and eroded confidence in your inspection system.

Quality engineer using go/no-go gauges to inspect machined part dimensions

Dimensional Drift Detection vs Go/No-Go Gauges

When inline AI vision outperforms contact gauges — and when it doesn't. A comparison for machined parts.

PCB with wrongly oriented connector highlighted during assembly inspection

Assembly Error Detection: Connector Orientation on PCBs

Connector polarity errors are common and expensive. Here's how AI vision catches them before board test.

Machine vision inspection station with ring light and dome light setups over a conveyor line

Lighting Setup for Machine Vision Inspection Lines

Ring lights, dome lights, dark-field — choosing the right illumination for your defect type and part geometry.

Quality dashboard showing defect escape rate metrics on a factory floor monitor

Measuring Defect Escape Rate in Production

How to calculate escape rate, what sampling strategy to use, and how to benchmark before an AI pilot.

Procunit production line inspection system deployed at a manufacturing facility

Procunit Raises Angel Funding and Shares Product Roadmap

We closed our angel round to accelerate field deployments and build multi-camera support. Here's what's coming.

Scrap bin of defective metal parts beside a production line inspection station

Reducing Scrap Rate with Inline AI Inspection

Scrap rate is a lagging indicator. Inline inspection turns it into a leading one — here's the math.

Industrial camera positioned above cylinder bore opening for internal surface inspection

Camera Placement Geometry for Cylinder Bore Inspection

Field angle, working distance, and coaxial illumination — the geometry of inspecting bores without a vision PhD.

Manufacturing cost analysis data displayed on industrial monitor at factory operations desk

ROI Analysis: AI Visual Inspection in Discrete Manufacturing

A worked example with real cost categories — scrap, rework, warranty, and inspection labor — for a stamping line.

Quality engineering metrics dashboard showing false positive analysis trends over production shifts

FPA Metrics Quality Engineering Teams Should Track

False positive analysis isn't just about the reject rate — it's about understanding model confidence over time.

Wiring harness connector with missing terminal pin visible under inspection lighting

Connector Pin Absence Detection on High-Volume Harness Lines

Missing terminal pins are hard to catch visually at speed. This is how AI handles it at 200+ connectors per minute.