Advancements in shape-from-focus based profilometry for additive manufacturing metrology
Additive manufacturing (AM) is a rapidly growing field with increasing demands for high precision and accuracy in the production of parts. However, there aren’t many of the existing precise and reliable metrology methods that are also integrated in the AM process for quality monitoring. Shape-from-focus (SFF) profilometry is a promising technique for online monitoring of the AM process, as it can provide high-resolution 3D surface reconstructions of printed parts. However, state-of-the-art implementations of SFF are considered time consuming as the reconstruction of a 3D profile requires the processing of a large number of images (100+). Additionally current implementations require the object to be stationary during a measurement. This does not reconcile with the nature of additive manufacturing where continuous motion of the printed part or print head is required for the manufacturing process. This thesis presents a thorough evaluation of the accuracy and precision of the SFF technique in comparison to traditional metrology methods (Laser triangulation, Structured Light Profilometry, ...). We also propose solutions to overcome the mentioned limitations and adapt the state-of-the-art SFF profilometry method to inline metrology. We show that the measurement accuracy can be improved by using a phase correlation algorithm for data reduction during image processing. Through improvements to the image acquisition we show that the required amount of data for a measurement can be greatly reduced. In addition,we showthat the traditionally stationary measurement method can be converted to a continuous scanning method without a significant loss in measurement quality. With these innovations, we were able to reduce the initial measurement time to fully measure a 100 by 100 mm characterization target from 4250 to 175 seconds. An improvement in measurement duration of 24x. The results of this thesis demonstrate that SFF profilometry can provide fast, highly accurate and precise measurements of the 3D surface of printed parts and is a reliable metrology method for online monitoring of the AM process.
Antwerpen : University of Antwerp, Faculty of Applied Engineering , 2023
iv, 114 p.
Supervisor: Vanlanduit, S. [Supervisor]
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Creation 12.12.2023
Last edited 13.12.2023
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