Digitisation of the agri-food industry for the optimisation of water flows

Implementation period

September 2017 – March 2018

Scope of work

Digital technology


This project has been funded by the national programme for clusters support “Ayudas a Agrupaciones Empresariales Innovadoras” (AEIs).


The agri-food sector is the largest consumer of water in the manufacturing industry, consuming between 8% and 15% in Europe. However, until now, the industry has prioritised optimising other resources that are more costly than water by making technological investments in other areas, such as energy, transport, production processes, etc. However, the management of the water cycle for industrial use in terms of quality control, regulatory compliance, the cost of water at the point of service and environmental responsibility are of concern to the industry.


The project has been carried out in three phases with their corresponding objectives:

  • Analysis of Fribin’s water cycle, including the performance of a hydro-efficiency audit, instrumentation and data capture of water consumption and other variables (humidity, temperature). This phase also made it possible to establish the key indicators (KPIs) as requirements for the water flows analysed in part of the process under study.
  • Process visualisation: using business intelligence tools (Qlik Sense), part of the Fribin production process was analysed, obtaining KPIs, histograms, steam studies and correlations. A set of input parameters (cost, temperature, flow and power) and variables (temperature, steam and production) were selected to establish optimal ranges to maximise KPIs.
  • Prototyping of Big Data Analytics solutions applied to optimise water flows, including data conditioning and transformation; study of time series and identification of patterns to obtain algorithms for predicting the behaviour of water flows.


DIGICAT has successfully tested the use of artificial intelligence to analyse and control processes in the agri-food industry, using a meat company, the Aragonese Fribin, as a case study. The project has also generated the following results;

  • Characterisation of water-consuming processes in the industry, defining the variables and indicators determining the production costs associated with water use.
  • Validation of business intelligence tools and their application for visualising and analysing water-consuming processes in the agri-food industry.
  • Identification of production patterns based on the analysis of time series data and predictive indicators for the behaviour of water flows, testing the use of big data analytics tools in water consumption processes for the first time.