ITEA Research Project (2017 - 2020)
Smart Prognosis of Energy with Allocation of Resources
A pan-European research consortium of 22 partners from five countries, pioneering a flexible optimisation platform for energy efficiency across industrial production processes.
About the Project
Redefining Industrial Energy Optimisation
The SPEAR project brought together academic institutions, industrial players, and technology firms from Germany, Portugal, Spain, Sweden, and Turkey to tackle one of the manufacturing sector's most persistent challenges: understanding and reducing energy consumption within complex production environments. Running from September 2017 to September 2020 under the ITEA programme, the initiative set out to develop a versatile optimisation platform capable of delivering measurable improvements across a wide range of industrial settings.
Rather than relying on simplified estimates or isolated monitoring, the project employed a distinctive methodology. By leveraging real device-provided simulation models and pairing them with advanced optimisation algorithms, the consortium created digital representations of production systems that could accurately forecast energy usage. These digital twins and digital shadows operated in parallel with actual plant equipment, enabling continuous validation and refinement of energy predictions.
The results proved the concept's commercial viability. Through smart source selection, adaptive process parameters, and peak load reduction, consortium partners achieved energy cost reductions of roughly 10% in tested scenarios. One automotive partner reported a 12% drop in overall energy consumption, while a forging company registered an 8% improvement. These outcomes earned the project the Eureka Innovation Award 2022 in the "Best Sustainability Innovation" category.
Energy Modelling
The platform uses component-level behavioural models to represent the energy characteristics of each element within a production system, ensuring highly accurate consumption forecasts.
Simulation Environment
Low-cost embedded hardware runs parallel simulations in real time, creating a digital shadow of the production line that updates continuously with live measurement data.
Optimisation Algorithms
An extensible library of optimisation methods analyses forecast data and identifies opportunities for load shifting, peak reduction, and process-level efficiency gains.
Project Goals
What the Consortium Set Out to Achieve
Extensible Optimisation Platform
The project aimed to deliver a cloud-capable and locally deployable platform that production engineers could use to analyse, simulate, and optimise the energy footprint of their facilities without requiring specialist modelling expertise.
Cross-Sector Applicability
Instead of targeting a single vertical, the consortium designed the platform to support diverse application domains: from common manufacturing plants and production lines to buildings, hybrid drives, and renewable energy installations.
Open Standards and Interoperability
Integration with the Functional Mock-up Interface (FMI) standard was a priority, enabling seamless exchange of component models between different simulation tools and making the platform accessible to a broad ecosystem of engineering software.
Real-World Validation
The project validated its approach through concrete use cases at partner facilities, including automotive body manufacturing lines, forging plants, and bakery production environments, proving the concept across varied industrial contexts.
Research Structure
Work Packages at a Glance
The project was organised into seven interconnected work packages, each addressing a critical layer of the optimisation stack.
Configuration Assistance
Requirements analysis and system specification for the optimisation platform.
Energy Models
Development, distribution, and scaling of energy behavioural models.
Simulation Environment
Efficient real-time energy simulation on embedded hardware.
Algorithm Library
Extensible library of optimisation algorithms for diverse industrial scenarios.
Platform Implementation
Web-based interfaces and integration endpoints for the optimisation platform.
Data Acquisition
Real machine data connectors and signal processing infrastructure.
Ability Connector
Bridging simulation outputs with physical production system feedback.
Recognition
Eureka Innovation Award 2022
The SPEAR consortium received the Eureka Innovation Award for "Best Sustainability Innovation" at the 2022 Global Innovation Summit in Estoril, Portugal, recognising the project's contribution to industrial energy reduction and the transition toward greener production.
Learn MoreConsortium
Partners Across Europe
Bringing together 22 organisations from Germany, Portugal, Spain, Sweden, and Turkey.
Latest News
From the SPEAR Consortium
SPEAR Wins Eureka Innovation Award for Sustainability
In June 2022, the SPEAR consortium was honoured with the Eureka Innovation Award in the "Best Sustainability Innovation" category at the Global Innovation Summit in Estoril, Portugal. The award, presented by the ITEA programme, recognised the project's measurable contributions to energy efficiency in industrial production. It was a milestone that validated three years of collaborative research across five European countries.
Continue reading →How Open Standards Drive Industrial Simulation Forward
Industrial simulation has long been fragmented by proprietary tool ecosystems. Engineers working on a production line might need a dedicated tool for mechanical simulation, another for electrical behaviour, and yet another for thermal analysis, with no easy way to combine their outputs. The Functional Mock-up Interface (FMI) addresses this challenge by defining a standardised container format for exchanging dynamic simulation models between tools. Within the SPEAR project, FMI served as the backbone for energy model distribution and integration.
Continue reading →Digital Twins for Energy-Efficient Manufacturing
The concept of the digital twin has become one of the defining ideas of modern manufacturing. By creating a virtual replica of a physical production system, engineers can monitor, analyse, and optimise operations without disrupting the real process. When combined with energy modelling, digital twins offer a powerful mechanism for identifying and eliminating waste. Swedish innovation agency Vinnova supported the Swedish contributions to the SPEAR project, which explored precisely this intersection of digital twin technology and energy optimisation.
Continue reading →Virtual Commissioning and the Path to Industry 4.0
Commissioning a new production line is traditionally one of the most time-consuming and costly phases of industrial plant development. Engineers must verify that every component behaves correctly, that control logic executes as intended, and that the complete system meets throughput and quality targets. Virtual commissioning offers an alternative by shifting much of this verification into a simulated environment.
Continue reading →Renewable Energy Integration in Production Scheduling
As the share of renewable sources in Europe's electricity mix continues to grow, manufacturers face both an opportunity and a challenge. Solar and wind generation introduce variability into the grid: electricity prices fluctuate throughout the day based on supply conditions, and the carbon intensity of available power shifts hour by hour. For energy-intensive production facilities, aligning operations with these fluctuations can yield significant cost savings and emissions reductions.
Continue reading →