Imagine a giant 3D printer that can build a whole apartment complex using recycled waste instead of traditional cement. It uses a smart digital brain to watch the printing process in real-time and fix mistakes on the fly, like a GPS for construction. This means buildings are designed to use only the exact amount of material needed, cutting down on waste and manual labor.
The construction industry faces a critical shortage of skilled labor and high carbon emissions, while traditional building methods are too slow and wasteful to meet global housing demands.
An AI-driven Digital Twin platform and a Learning-by-Printing methodology for real-time robotic control of 3D concrete printing.
If you are a developer dealing with rising labor costs and housing shortages — this project developed an AI-driven robotic workflow that can reduce construction time by 70% and material costs by 80%. This allows for faster project turnaround and lower capital expenditure per unit.
If you are a manufacturer dealing with high carbon taxes and cement demand rising by 23% by 2050 — this project developed sustainable cementitious materials using recycled granular waste. This enables a 50% reduction in embodied carbon for your product line.
If you are a robotics company dealing with the unpredictability of on-site printing — this project developed Learning-by-Printing (LbP) for real-time prediction and correction. This ensures high accuracy and resilience in complex multi-storey construction environments.
The project aims for an 80% reduction in costs through the use of 3D concrete printing and optimized material use.
Yes, the project specifically targets multi-storey construction using a system-of-systems approach and networked robotics to move beyond small-scale prototypes.
Based on available project data, the project is in the signed phase (starting Oct 2024), and specific licensing terms for the AI-driven Digital Twin platform are not yet disclosed.
It uses a Digital Twin construction information backbone that connects computational design directly to the robotic production system.
The project period runs from 2024-10-01 to 2028-09-30, suggesting that validated results and pilot studies will be available toward the end of this window.
The consortium is well-balanced for technology transfer, consisting of 7 partners across 6 countries. With a 43% industry ratio (3 industrial partners, including 1 SME), there is a strong bridge between the 4 academic institutions and commercial application, ensuring that the AI and robotic developments are grounded in market needs.
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