OPTINVAS Project
Artificial intelligence applied to quality and packaging processes
What does the project consist of?
OPTINVAS consists of the creation of a pilot machine vision inspection system to verify the individual quality of a pack of sliced ham in order to extract qualitative parameters from it and correlate them with production parameters in order to improve the process by means of traceability. It is planned to set up the INNDEO & INSPECTRA artificial vision technological system to test it in a pilot scale environment in the Espuña and Cañigueral companies.
The inspection to be carried out by the equipment will be done through artificial vision technologies, and will allow the capture and processing of a very large number of images in very short periods of time. Once the images have been captured, further processing will be carried out using artificial vision software designed ad-hoc for each quality procedure and for each product.
It is also planned to develop a configuration tool for the inspection software that will allow the production companies themselves to configure the inspection parameters when they change packaging, so that the inspection programmes can be adapted as a tailor-made suit for each packaging and each product.
This solution solves a need for automation for producers of sliced ham by automating the packing process, since it is essential to automate the process of inspecting the packs. This task is carried out manually due to the low effectiveness of existing automated solutions on the market.
what is its main objective?
The main objective of this project is to investigate an innovative and technological solution in the process of detecting contamination and defects in food industry packaging. Specifically, the aim is to establish an artificial vision system to automate the quality inspection process in sliced ham packaging, testing a new quality inspection system by artificial vision at the end of the line that will allow quality inspection. In this way, innovative sanitisation processes in the food industry will be strengthened.
Participants
With the support of:
