Real-time splatter tracking in laser powder bed fusion additive manufacturing

Yanzhou Fu; Braden Priddy; Austin R. J. Downey; Lang Yuan

doi:10.1117/12.2658544

25 April 2023 Real-time splatter tracking in laser powder bed fusion additive manufacturing

Yanzhou Fu, Braden Priddy, Austin R. J. Downey, Lang Yuan

Proceedings Volume 12489, NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE; 124890N (2023) https://doi.org/10.1117/12.2658544
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States

Conference Poster

Abstract

In additive manufacturing, laser powder bed fusion (LPBF) has unrivaled strengths due to its design and manufacturing freedom. The in situ validation of additively manufactured components would reduce or entirely remove the need for post-processed non-destructive evaluation. Potentially enabling the direct utilization of components from the print bed. However, typical approaches to in situ monitoring of the LPBF process utilize high-speed thermal and optical cameras coupled with advanced optics to enable co-axial imaging of the weld pool. The amount and quality of the data obtained through these systems necessitate the need for extensive post-processing of data. In contrast, this work provides a low-cost in situ monitoring and real-time computing alternative using industrial cameras and optical filters to track the splatter area of the welding process. To reduce the dimensionality of data retained for a given component, the proposed process tracks the brightness contours of the welding process in real-time and retains only a select number of features. In this introductory work, the prototype system is investigated using a variety of different image processing methods to optimize processing speed (measured in frames per second) versus the size of melting splatter for a test specimen of 10 mm × 10 mm × 5 mm. Defects in the specimen are quantified using computed tomography and linked to information extracted from tracking the splatter-related features in situ. Results show that the speed of the computational system, visibility of splatter, and the accurate translation of splatter brightness to contours with area and locations is critical to functionality. A discussion on the trade-offs between these constraints is provided.

Citation Download Citation

Yanzhou Fu, Braden Priddy, Austin R. J. Downey, and Lang Yuan "Real-time splatter tracking in laser powder bed fusion additive manufacturing", Proc. SPIE 12489, NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE, 124890N (25 April 2023); https://doi.org/10.1117/12.2658544

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