Geometric and Dimensional Imprecisions Classification and Form Prediction in 3D Concrete Printing

3D concrete printing (3DCP) is rapidly advancing as an innovative construction method, yet achieving high dimensional and geometric accuracy remains a significant challenge. This study introduces a predictive modeling framework designed to forecast the main geometric deviations observed in 3DCP, namely planar, lateral, and vertical inaccuracies. Building on insights from 27 referenced studies, deviation sources are classified and expressed through mathematical transformation equations. The framework couples these equations with CAD-generated geometries to reconstruct the expected as-printed form before fabrication. Validation using a circular printed wall demonstrates the model’s ability to predict typical distortions and quantify their magnitude, particularly those arising from slicing artifacts, material shrinkage, and interlayer deformation. By relating deviation prediction to parameter optimization, the study outlines corrective strategies such as adaptive slicing, variable-nozzle control, and targeted reinforcement. The proposed approach provides a systematic pathway for improving geometric precision and advancing 3DCP toward reliable full-scale construction.