Abstract
Increasing attention has been devoted in recent years to in situ sensing and monitoring of the electron beam melting process, ranging from seminal methods based on infrared imaging to novel methods based on backscattered electron detection. However, the range of available in situ monitoring capabilities and solutions is still quite limited compared to the wide number of studies and industrial toolkits in laser-based additive manufacturing processes. Some methods that are already industrially available in laser powder bed fusion systems, such as in situ detection of recoating errors, have not yet been investigated and tested in electron beam melting. Motivated by the attempt to fill this gap, we present a novel in situ monitoring methodology that can be easily implemented in industrial electron beam melting machines. The method is aimed at identifying local inhomogeneity and irregularities in the powder bed by means of layerwise image acquisition and processing, with no external illumination source apart from the light emitted by the hot material underneath the currently recoated layer. The results show that the proposed approach is suitable to detect powder bed anomalies, while also highlighting the link between the severity of in situ detected errors and the severity of resulting defects in the additively manufactured part.
Highlights
The quality and performance of high-value-added parts produced via powder bed fusion (PBF) processes, either laser- or electron beam-based, are known to be affected by a large variety of factors
Our study presents an automated powder bed monitoring methodology applicable to EB-PBF, which relies on a camera and no external illumination source
Powder bed inhomogeneity is known to be a primary source of errors and defects in PBF processes, as it directly influences the volumetric energy density provided to the material with consequent local variations in the melting and solidification mechanisms
Summary
The quality and performance of high-value-added parts produced via powder bed fusion (PBF) processes, either laser- or electron beam-based, are known to be affected by a large variety of factors. Several sources of poor quality can be predicted and tackled by properly selecting, controlling, and optimizing powder properties, process parameters, build design choices, and machine calibration settings. A whole body of scientific literature and industrial research has been devoted to in situ measurement and monitoring methods suitable to detect the onset of process defects and the origination of unstable process conditions, exploiting sensor data acquired during the process. One category of methods involves the in situ measurement and characterization of layer properties, exploiting so-called “powder bed cameras”, i.e., off-axially mounted cameras that acquire one or more pictures on a layer-by-layer basis. Images acquired after the melting phase, once the solidification of the scanned area has occurred, may be used for different aims, such as detecting undesired surface irregularities in the solidified layers, as possible sources of internal and surface defects [6,7,8,9,10], or signaling possible deviations with respect to the nominal shape in the layer, as evidence of geometrical errors [11,12,13,14,15]
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