How Machine Vision is applied in manufacturing (YOLOv8)

The obsolete $10,000 dollar paradigm #

Historically, if a plant manager wanted to implement automatic quality control on a production line, the only option was to contact closed providers (like Cognex or Keyence). These companies sell "smart cameras" that cost between $5,000 and $15,000 dollars per inspection point, and require proprietary software that is a nightmare to integrate.

Today, the question is not whether you need machine vision, but how to apply it without breaking the innovation budget. The answer lies in separating hardware from intelligence using [Edge Computing](/glosario#edge%20computing).

Three Real Applications in Manufacturing #

1. Quality Control and Defects (Visual Inspection)

AI models can be trained to detect micro-cracks in glass packaging, poorly closed seals in food, or rust on metal parts. By integrating with the machine's [PLC](/glosario#plc) via Modbus, the iGromi system sends a "Reject" signal to a pneumatic arm to eject the defective product from the conveyor belt in real-time.

2. High-Speed Counting and OEE Calculation

Many older machines do not have output sensors. A camera pointing at the final packaging box can count how many units leave per second with 99.9% accuracy. This information is injected directly into iGromi MES to calculate your [OEE](/glosario#oee) automatically.