ABSTRACT
Mixing time is a critical parameter in printcrete (3D printed concrete), directly influencing mixture homogeneity and printability, which in turn govern construction efficiency and overall cost. This study proposes a computational framework for determining the optimal mixing time based on a non-contact monitoring system. The homogeneity was quantitatively characterized by analyzing surface texture images, from which a texture index was computed as the standard deviation of grayscale values to evaluate degree of homogeneity. Simultaneously, printability was assessed via rheological properties, with key parameters derived through a linear calibration model linking mixer torque to offline rheometric data. By integrating target thresholds for both homogeneity and rheological performance, the optimal mixing time was identified using a non-contact monitoring system. The proposed method was applied to a printcrete mixture incorporating a polycarboxylate ether superplasticizer and an aluminum sulfate-based accelerator. Results demonstrate that the approach reliably determines stage-specific mixing times, ensuring consistent printability and mechanical performance.
