Nozzle Pressure Defect Detection in Extrusion-Based Bio 3D Printing Using Video-Based Motion Estimation

喷嘴 挤压 计算机科学 3D打印 运动估计 运动(物理) 材料科学 计算机视觉 工程类 机械工程 复合材料
作者
Md Anisur Rahman,Md Abdullah Hil Kafi Khan,Jin‐Ki Kim
出处
期刊:ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
标识
DOI:10.1115/smasis2024-140392
摘要

Abstract The emergence of bio-additive manufacturing marks a crucial advancement in the field of biomedical engineering. For successful biomedical applications including bioprinted organ transplants, ensuring the quality of printed structures poses a significant challenge. Among the major challenges encountered in ensuring the structural integrity of bioprinting, nozzle clogging stands out as one of the frequent concerns in the process. It disrupts the uniform distribution of extrusion pressure, leading to the formation of defective structures. This study focused on detecting defects arising from the irregularities in extrusion pressure. To address this concern, a video-based motion estimation technique, which emerged as a novel non-contact and non-destructive technique for assessing bio 3D printed structures, is employed in this research. While other advancements, including contact-based and laser-based approaches, may offer limited performance due to the soft, lightweight, and translucent nature of bioconstructs. In this study, defective and non-defective ear models are additively manufactured by an extrusion-based bioprinter with pneumatic dispensing. Extrusion pressure was strategically controlled to introduce defective bioprints similar to those caused by nozzle malfunctions. The vibration characteristics of the ear structures are captured by a high-speed camera and analyzed using phase-based motion estimation approaches. In addition to ambient excitations from the printing process, acoustic excitations from a subwoofer are employed to assess its impact on print quality. The increase in extrusion pressure, simulating clogged nozzle issues, resulted in significant changes in the vibration characteristics, including shifts in the resonance frequencies. By monitoring these modal property changes, defective bioconstructs could be reliably determined. These findings suggest that the proposed approach could effectively verify the structural integrity of additively manufactured bioconstructs. Implementing this method along with the real time defect detection technique will significantly enhance the structural integrity of additively manufactured bioconstructs and ultimately improve the production of healthy artificial organs, potentially saving countless lives.
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