Multi-Criteria Decision Framework for Optimal Robotic System Selection in 3D Concrete Printing

3D Concrete Printing (3DCP) is increasingly used for both on-site building fabrication and off-site production of structural components in controlled environments. The differences between these application contexts pose distinct requirements and constraints for the robotic systems used for material deposition. Selecting an appropriate robotic architecture, therefore, represents a critical design decision that directly influences printing quality and system performance. To address this challenge, this study proposes a multi-criteria decision-making framework for optimal selection of the robotic architecture for a 3DCP system, in accordance with its application requirements and constraints. For this, the method integrates AHP and TOPSIS, and takes into consideration factors such as technical characteristics, operational requirements, and economic costs. To demonstrate the applicability of the method, a case study was conducted to identify the most suitable robotic architecture for a laboratory-scale façade printing 3DCP system. Three robotic configurations were analyzed: a gantry system, an articulated robotic arm, and a parallel delta robot. The results showed that the articulated robotic arm achieves the highest TOPSIS closeness coefficient (CCᵢ = 0.681), outperforming the other two configurations. These findings align with existing façade-oriented 3DCP studies and indicate that articulated robotic arms are well-suited for the fabrication of geometrically complex components with higher surface quality and dimensional accuracy. The results show that the proposed framework enables transparent, application-driven decisions during early-stage robotic system design for 3DCP.