Context and Rationale
The construction sector is one of the largest contributors to climate change, responsible for nearly 40% of global energy use and CO2 emissions, with cement accounting for 8%. Cement demand is expected to rise by up to 23% by 2050, while construction and demolition waste already represents about 40% of global solid waste. Without intervention, these trends threaten Europe’s ability to meet EU Green Deal and Fit for 55 targets. Yet this challenge also offers an opportunity. 3D concrete printing (3DCP) provides a radically different construction model, with potential reductions of 60% in material use, 80% in cost, and 70% in construction time. However, adoption remains limited due to gaps in material design, process control, scalability, and environmental integration. A shortage of skilled labour further complicates deployment, heightening the need for integrated robotic fabrication workflows. Current approaches remain fragmented, heavily reliant on trial-and-error and open-loop processes unsuited for industrial-scale impact.
Project Objectives
AM2PM combines material, digital, and robotic innovation to create an AI-driven Digital Twin platform uniting digital manufacturing and robotic construction. Laboratory demonstrators and pilot studies will validate this ecosystem, enabling multi-storey cyber-physical construction workflows. The project aims to set new standards, methods, and materials to accelerate decarbonisation and digitalisation of the AEC sector.
Central to this effort is the development of sustainable cementitious materials using recycled granular waste and locally sourced resources, targeting a 50% reduction in embodied carbon and significantly reduced cement use. In parallel, AM2PM advances computational structural design by integrating buildability, material efficiency, and environmental metrics directly into topology optimisation, generating complex load-bearing components that are both robust and resource-efficient.
To ensure reliability at scale, the project introduces Learning-by-Printing (LbP), an AI-driven methodology for real-time prediction, monitoring, and correction of 3DCP processes. These adaptive models integrate with dynamic Digital Twin systems that coordinate robots, sensors, and construction workflows through continuous bi-directional feedback. This ensures accuracy, adaptability, and resilience in real construction environments. Predictive Life Cycle Assessment (LCA) is embedded from the earliest design stages, enabling environmental impacts to be anticipated and mitigated before fabrication and construction. Together, these innovations define a digital, resource-efficient, and climate-conscious framework for next-generation construction.
Pathway to Impact
AM2PM’s pathway to impact merges technical breakthroughs with system-level transformation across materials science, digital design, robotics, AI, and multi-scale integration. Laboratory demonstrators and pilots will lead to a cyber-physical platform for multistorey building components. Beyond technological achievements, AM2PM will shape new standards and workflows for the AEC sector, embedding predictive LCA, automation, and scalable digital practices into mainstream construction. Aligned with the European Green Deal and the New European Bauhaus, the project couples sustainability with digital and cultural innovation, supporting Europe’s leadership in low-carbon construction technologies.
