Yes, at CIRCE, we have not resisted trying out ChatGPT, that AI-based tool that’s revolutionizing the internet. Because, what better way to inquire about artificial intelligence than asking an artificial intelligence itself?

Within the realm of artificial intelligence, computer vision holds great potential for the industry, making it possible to develop automated solutions for critical phases in production processes, such as quality control, equipment monitoring for fault detection, and image analysis.

Can you imagine a technology capable of intelligently obtaining, processing, and interpreting images? Something like ChatGPT, but applied to the visual domain. In this way, the industry can analyze and decode information gathered during production processes to make informed decisions and take appropriate actions through automated procedures.


But what does ChatGPT say about the most promising applications of computer vision in the industry?

Here is what it has to say:

And is it profitable for the industry?

To understand it, computer vision solutions are tools that, like ChatGPT, are based on artificial intelligence and can observe, process captured information, and intelligently act in an automated manner.

But how do we gauge the value that technology can bring to the industry? One of the most promising applications is quality control of any product, especially those involving production processes with high economic costs for modifications.

In this regard, computer vision applications can be used for everyday issues like ensuring product uniformity – whether a bottle contains the same amount of liquid, if a piece is positioned the same as others on the conveyor belt – detecting minor defects, or even for product inspections involving color changes.



Color matching, a solution enabling the detection of imperceptible changes

In this case, color matching proves useful, a solution capable of detecting imperceptible changes in product color. Understanding the value this tool can offer to the industry might be easier with knowledge of a real case executed by CIRCE in the automotive sector.

One of the significant challenges in the automotive industry is detecting imperceptible bodywork flaws that signify quality defects in the final product, necessitating redoing the manufacturing or painting process, incurring substantial costs.

Can you spot the difference between these two metal sheets?

You likely can not perceive that each of these sheets has a different shade. However, the computer vision-based solution developed by CIRCE provides a clear diagnosis:

The process devised thus far involves detecting shade differences through cameras and models that, once deployed on the production floor, do not interfere with the production process and assist plant managers in identifying and rectifying these issues, ensuring a high product quality standard for their customers.

Do you need to ensure your quality controls are accurate and think these solutions could benefit your industry?

Share your challenge with us.