SciTransfer
AGILE · Project

AI-Driven Flexible Production Systems for Energy-Intensive Heavy Industries

manufacturingPilotedTRL 7

Imagine a factory that can change its own setup like a Lego set to handle different materials or energy prices on the fly. It uses smart AI agents that act like a digital brain to coordinate machines and save energy. This helps heavy plants stop wasting heat and switch to green power without shutting down for weeks.

By the numbers
24
consortium partners
10
participating countries
46%
industry ratio in consortium
7
target TRL level
The business problem

What needed solving

Energy-intensive industries struggle with rigid production lines that cannot adapt quickly to changing energy prices, raw material quality, or market demand, leading to waste and high emissions.

The solution

What was built

A system of AI agents and digital twins that orchestrate modular equipment, including low-temperature electrolysis and waste heat recovery systems.

Audience

Who needs this

Copper recycling plantsIndustrial ceramics manufacturersWastewater treatment operatorsGreen hydrogen producers
Business applications

Who can put this to work

Metal Recycling
enterprise
Target: Copper smelting and processing plant

If you are a copper processor dealing with high energy costs and rigid production lines — this project developed melting-free roll bonding that allows for greener and more flexible copper recycling.

Ceramics
mid-size
Target: Industrial ceramics manufacturer

If you are a ceramics producer dealing with volatile feedstock and high emissions — this project developed an agentic AI system that optimizes production scheduling and energy management to reduce GHG emissions.

Water Management
any
Target: Industrial wastewater treatment facility

If you are a utility provider dealing with inefficient water cleaning processes — this project developed digital twins and real-time monitoring to improve resource efficiency and energy savings.

Frequently asked

Quick answers

What is the cost or pricing for implementing these AI tools?

Based on available project data, specific pricing or implementation costs are not provided as this is a research and innovation action.

At what industrial scale is the technology being tested?

The solutions are being validated through pilot-scale demonstrations reaching TRL7 in copper, ceramics, and wastewater sectors.

How is the IP and licensing handled for the AI agents?

Based on available project data, the specific IP and licensing terms are not disclosed in the project summary.

How does this integrate with existing factory hardware?

It uses a modular, interoperable digital architecture based on Asset Administration Shells and IIoT-enabled digital twins to connect with physical assets.

What is the timeline for the rollout of these technologies?

The project runs from September 1, 2026, to August 31, 2030.

Consortium

Who built it

The project features a strong industrial base with 11 companies (46% of the 24 partners), ensuring that the AI tools are built for real-world application. With 7 research centers and 6 universities across 10 European countries, the group balances deep academic knowledge in electrolysis and ceramics with practical SME and enterprise deployment capabilities.

How to reach the team

Contact ASOCIACION DE INVESTIGACION METALURGICA DEL NOROESTE in Spain

Next steps

Talk to the team behind this work.

Contact us to identify the specific AI-agentic tools available for your production line.

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