Clusaga promotes the YIELDCAN 5.0 project, focused on increasing the productive performance and the final quality of products in the canning sector: canned fish and shellfish.

Submitted by Roberto Alonso on 15 July 2022

cans-139340_960_720

The Galicia Food & Drink Cluster (Clusaga) leads the national collaborative project YIELDCAN 5.0, which has been selected in the first call of 2022 of the national support programme for clusters AEI (Agrupaciones Empresariales Innovadoras), convened by the Spanish Ministry of Industry, Commerce and Tourism.

The YIELDCAN 5.0 project, "Development and validation of massive data processing techniques in the optimization of production processes, sustainability and the quality of the final product in the canned fish sector", has the general objective of increasing the productive performance and the final quality of products in the canning sector: canned fish and shellfish.

This project aims to obtain the development and validation of a massive data monitoring and analysis platform in the final stages of the manufacturing and packaging process, since they are the stages most susceptible to optimization from the point of view of reducing losses and improving of quality.

YIELDCAN 5.0 is carried out by a consortium coordinated by Clusaga, which integrates two SMEs from the canning sector (Palacio de Oriente and Real Conservera), a large company in the sector canner (Conservas Rianxeira) and two technological entities (ANFACO-CECOPESCA and TripleAlpha Innovation).

YIELDCAN 5.0's objectives

  • Studying the potential impact of different critical process variables on business KPIs and select those key factors to increase the reduction of waste, as well as their final quality.
  • Defining the BATs (Best Avaliable Technologies) that allow monitoring the selected variables and automate the collection of data necessary for their management in real time at a low cost. In this sense, we have three manufacturing environments with different technological intensity.
  • Developing new ways of data management, data analysis (using ML techniques) and data visualization that allow production managers and managers to optimize decision-making
Cluster organisation
Share this Article