Experimental Data-Driven Framework for Quality Control of 3D-Printed Concrete Permanent Formworks

As an emerging structural system, 3D-printed concrete permanent formwork (3DPF) eliminates the need for formwork removal and enables the realization of complex geometries. However, clearly defined quality control standards tailored to the unique characteristics of 3DPF are still lacking. This paper proposes an experimental data-based framework to integrate quality control considerations into both the design and manufacturing stages. The proposed framework comprises systematic experimental procedures to evaluate parameters such as the fresh and hardened material properties, printing parameters, and geometric constraints, and organizes the results into structured data categories. The collected data were subsequently embedded into a Design for Additive Manufacturing (DfAM) decision-making algorithm, which supports manufacturability evaluations, including additional layers for milling, plastic collapse prediction, maximum printable dimensions, and first-layer deformation near sharp corners. An equivalent strength factor was introduced as a quality control reference during printing, providing a consistent basis for evaluating structural performance using the strength ratio between the printed and cast specimens. Moreover, an exponential relationship was identified between the corner angle and first layer width, enabling the quantification of layer deformation near sharp corners. Finally, the proposed framework enables unified quality control across the materials, equipment, and design of the 3DPF and its manufacturing system.