Abstract
Additive manufacturing technologies have the potential to revolutionize the manufacturing industry by making it easier to fabricate complex structures, high value, and low volume parts in various contexts. Bio-additive manufacturing is particularly promising, as it has enabled the 3D printing of human organs. Researchers have made progress by developing novel materials and printing strategies for additively manufacturing complicated mission-critical geometries. On the other hand, assessing the structural integrity of these bio-printed structures has been challenging, as destructive contact-based approaches may interfere with the manufacturing process and affect the original dynamics and quality of the bio-prints, due to the relatively soft and lightweight nature of bio-prints. Furthermore, the repeatability of measurement is significantly dependent on the quality of how the sensor is attached to the part. Non-contact methods, such as laser and X-ray based techniques, can provide measurements without adding mass to the part. However, lasers may produce inaccuracies due to reflection and absorption in translucent materials, which are often found in bio-constructs. Although there have been significant advances in non-contact methods for reliably identifying damages in bio-printed structures, particularly embedded defects, implementing these approaches in a straightforward way has been challenging. To advance the state-of-the-art, this study proposes a novel method that can reliably assess the damage properties without contact by using video-based vibrometry. Vibration signals can provide a comprehensive response of the target structure, including material properties and geometry changes due to embedded defects in bioprinting. By analyzing the phase shift of the pixel intensity in the video, the vibration characteristics that indicate surface and/or embedded defects can be assessed for the entire structure captured in the camera angle, without the need for multiple sensors to be installed on the structure. This research focuses on analyzing the vibration characteristics of a cube that was manufactured by an extrusion-based bio-printer with pneumatic dispensing using sodium alginate based bioink. A high-speed camera and phase-based motion estimation technique are used to obtain experimental data on the vibration characteristics of the cube. Volumetric defects introduced by extrusion pressure irregularity and scaffolds with voids and their severities are identified by monitoring the vibration characteristics. These findings suggest that the proposed method could be utilized to effectively verify the structural integrity of additively manufactured organs during fabrication, which could enhance process optimization and operation safety. Future works include incorporating finite element model to compare its response characteristics for healthy and damaged models with the experimentally obtained results and identifying the detection sensitivity and limit with respect to parameters such as damage type and location.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of ASME 2023 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2023 |
| Publisher | American Society of Mechanical Engineers |
| ISBN (Electronic) | 9780791887523 |
| ISBN (Print) | 9780791887523 |
| DOIs | |
| State | Published - 2023 |
| Event | 16th Annual ASME Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2023 - Austin, United States Duration: Sep 11 2023 → Sep 13 2023 |
Publication series
| Name | ASME 2023 Conference on Smart Materials, Adaptive Structures and Intelligent Systems |
|---|
Conference
| Conference | 16th Annual ASME Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2023 |
|---|---|
| Country/Territory | United States |
| City | Austin |
| Period | 09/11/23 → 09/13/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Scopus Subject Areas
- Artificial Intelligence
- Civil and Structural Engineering
- Mechanics of Materials
Keywords
- 3D bioprinting
- additive manufacturing
- computer vision
- damage detection
- nondestructive evaluation
- phase-based motion estimation
- structural health monitoring
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