Real-time image-based closed-loop control framework for dimensional accuracy in extrusion-based additive manufacturing for bone tissue scaffold applications

Bone tissue scaffolds fabricated via extrusion-based bioprinting require high dimensional accuracy to ensure functional performance in tissue regeneration. However, process fluctuations caused by material behaviour, extrusion instability, and environmental variations can lead to pore size deviations and reduced fabrication repeatability. This study proposes a real-time image-based closed-loop control framework for improving dimensional accuracy in bioprinting processes. The system integrates inline visual monitoring with adaptive flow control to continuously track pore geometry during fabrication. Image-based analysis is used to compute pore size deviations in real-time, enabling dynamic adjustment of material flow to maintain predefined geometric tolerances. Unlike conventional trial-and-error or offline calibration approaches, the proposed framework autonomously compensates for process deviations during fabrication, reducing material waste and improving process stability. Experimental results demonstrate improved pore size consistency, enhanced dimensional accuracy, and increased reproducibility under varying process conditions. The proposed framework contributes to the development of adaptive and autonomous material extrusion-type bioprinting systems for reliable scaffold fabrication.