How to guide automation when traditional machine vision falls short

IONA drives high accuracy when local datum structures do not exist

The need for automation in demanding applications is rapidly growing, and so is the demand for real-time data for in-process control and verification, as well as validation of digital assets, such as digital twins and offline simulations.

The use of robots, even when combined with traditional machine vision, cannot always keep up with these demands. Often, this is because the machine vision is mounted to the robot itself, and is only able to provide local alignment without context of the broader datum structure or environment.

Moreover, machine vision systems usually require highly skilled labour for both their commissioning and operation. This dependence on specialised expertise acts as a barrier to seamless integration and often hinders the widespread adoption of machine vision in industrial settings.

IONA is a metrology guidance system that has been designed from the ground up to solve many of typical pitfalls of machine vision systems whilst enabling process improvements across many applications.

This article is going to delve into these issues in more detail and outline how IONA solves them.