The Innovation Action project “EnerMan” introduces an energy sustainability management system in order to achieve a holistic and data-based view of the energy efficiency, energy use and consumption within factories.
Industrial production in Europe consumes large amounts of energy (27.8% of the total energy consumption in Germany, 21% in France) and therefore constitutes a key target for energy sustainability. However, current manufacturing optimization approaches through control automation closed loops are focused primarily on reliability, production efficiency, product quality but not on energy consumption optimization as part of a holistic energy sustainability approach. Factories of the Future need to restate the approach they have on using energy and move from purely energy optimization model to an energy sustainability model that has a holistic view on energy consumption.
EnerMan envisions the factory as a living organism that can manage its energy consumption in an autonomous way. To this end, it will create an energy sustainability management framework collecting data from the factory and holistically process them to create dedicated energy sustainability metrics. These values will be used to predict energy trends using industrial processes, equipment, and energy cost models. An autonomous, intelligent decision support engine will be developed that will evaluate the predicted trends and access if they match predefined energy consumption sustainability Key Performance Indicators (KPIs). If the KPIs are not met, EnerMan will suggest and implement changes in energy affected production lines control processes: an energy aware flexible control loop on various factory processes will be deployed.
The EnerMan administrators will be able to use the above mechanisms in order to identify how future changes in the production lines can impact energy sustainability using the EnerMan prediction engine (based on digital twins) to visualize possible sustainability results when in-factory changes are made in equipment, production line.
The EnerMan digital twin will predict the economic cost of the consumed energy based on the collected and predicted Energy Peak load tariff, Renewable Energy System self-production, the variations in demand response, possible virtual generation, and prosumer aggregation.
The project’s results will contribute to the reduction of the energy consumption for the improved production process of at least 25% and the life Cycle Cost at least 15%, will improve the environmental performance of the involved products and will develop standardised European energy-efficient best practices to overcome the barriers limiting their application in the manufacturing sectors.
The ENERMAN consortium consists of 22 partners from 10 different countries, led by the FIAT Research Centre. The KIOS Research and Innovation Center of Excellence at the University of Cyprus participates actively in this project and will conduct innovation activities in the areas of intelligence decision support systems and modelling, as well as industrial control systems.
Project’s website: https://enerman-h2020.eu/
The project has received funding from the European Union’s Horizon 2020 Research and Innovation program under Grant Agreement No 958478
