High resolution-optical tomography for in-process layerwise monitoring of a laser-powder bed fusion technology
Source abstract
Abstract
With the implementation of Laser Powder Bed Fusion technologies for industrial production, the need for in-process monitoring has emerged to ensure stable conditions and the process to succeed. Indeed, despite significant technological advances, the rejected parts are still too high if compared to the more conventional manufacturing techniques. Several defects are known to affect the process, more likely when complex geometries are fabricated. Among these, the production of inclined thin walls without support structures is still critical and, in most cases, geometric distortions are observed on the overhanging surfaces. In order to overcome the above mentioned problems and improve the quality of these critical structures, an high resolution monitoring system based on Optical Tomography (OT) was proposed, called High Resolution-Optical Tomography (HR-OT). It uses a very high-resolution sensor, operating in the visible spectrum of light, on a large area of the surface layers comprising the entire printing platform. This very recent technique, typically applied for the detection of volumetric defects, such as porosity or lack of fusion, was successfully applied, in this paper, for the detection of geometric distortions, allowing to avoid onerous pre-processing phases in the image processing workflow. Specific geometric indexes were selected as monitoring outputs and were used for the construction of appropriate control charts in order to carry out statistical process monitoring. Finally, an off-line 3D reconstruction, by means of digital close range photogrammetry, was used to verify the effectiveness of the proposed monitoring solution when applied for in-process detection of geometric distortions.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · Welding Techniques and Residual Stresses · Advanced X-ray and CT Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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