Project approved under the AEI 2022 NG grant line.

OPTINVAS consists of machine vision inspection of individual slices of product but also of groups of slices (packages) to verify the quality of both the product and the package. 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 package defects (e.g. poor sealing) can be detected on the same packaging line.

By taking advantage of the fact that 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 package with the specific fat content of each package and thus differentiate those packages with a lower fat content.

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

This solution solves an automation need of the production companies since it allows automating the case packing process, making it essential to automate the container inspection process. Currently, this task is still performed manually due to the low effectiveness of the automated solutions existing so far in the market.

This project will be carried out with the support of: