Poster + Presentation + Paper
22 March 2021 In situ structural validation of components manufactured using fused filament fabrication
Author Affiliations +
Conference Poster
Abstract
Improvements to processes and materials have led to increased additive manufacturing capabilities using the fused filament fabrication method in terms of speed, quality, and repeatability. However, there are significant challenges in guaranteeing the desired output quality due to uncertainties inherent to the printing process. These include uncertainties in the quality of raw materials across different batches, fabrication environment (e.g., humidity, temperature), and machine wearing. The widespread adoption of fused filament fabrication for industrial applications faces considerable challenges in reducing part-to-part variations and assuring the mechanical properties of a manufactured component. In this paper, an in situ fault detection platform that considers the structural properties of the printed part is proposed. The presented system uses the optical camera and a deep learning methodology to detect faults online using training sets developed offline. The performance of the system is quantified using a variety of metrics. Computational speed for inference computation, minimum fault-sized detection, and measurement noise in the system are examined in this work.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yanzhou Fu, Austin Downey, Lang Yuan, Yunusa Balogun, and Avery Pratt "In situ structural validation of components manufactured using fused filament fabrication", Proc. SPIE 11592, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XV, 115921E (22 March 2021); https://doi.org/10.1117/12.2581600
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KEYWORDS
Additive manufacturing

Manufacturing

Defect detection

Humidity

Imaging systems

Materials processing

Optics manufacturing

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