Project approved under the AEI 2022 NG grant line.

OPTINVAS involves machine vision inspection of individual slices of product but also of groups of slices (packaging) to verify the quality of both the product and the packaging. Machine vision allows the capture and processing of a very large number of images in very short periods of time so that product defects (e.g. excessive fat content) and packaging defects (e.g. poor sealing) can be detected on the same packaging line.

Because machine vision is able to discriminate between lean and fat in the product, one of the objectives of the project is also to study whether it would be possible to label each of the packs with the specific fat content of each pack and thus be able to differentiate those packs with a lower fat content.

In addition, it is planned to develop an inspection software configuration tool that allows the production companies themselves to configure the inspection parameters when they change packaging, so that the inspection programmes can be adapted to perfection for each type of packaging and each product.

This solution solves a need for automation in the production companies, as it allows the case packing process to be automated, making it essential to automate the packaging inspection process. Currently, this task is still carried out manually due to the low effectiveness of the automated solutions available on the market to date.

This project will be carried out with the support of: