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Additive manufacturing (AM) of metals and in particular laser powder bed fusion (LPBF) enables a degree of freedom in design unparalleled by conventional subtractive methods. To ensure that the designed precision is matched by the produced LPBF parts, a full understanding of the interaction between the laser and the feedstock powder is needed. It has been shown that the laser also melts subjacent layers of material underneath. This effect plays a key role when designing small cavities or overhanging structures, because, in these cases, the material underneath is feed-stock powder. In this study, we quantify the extension of the melt pool during laser illumination of powder layers and the defect spatial distribution in a cylindrical specimen. During the LPBF process, several layers were intentionally not exposed to the laser beam at various locations, while the build process was monitored by thermography and optical tomography. The cylinder was finally scanned by X-ray computed tomography (XCT). To correlate the positions of the unmolten layers in the part, a staircase was manufactured around the cylinder for easier registration. The results show that healing among layers occurs if a scan strategy is applied, where the orientation of the hatches is changed for each subsequent layer. They also show that small pores and surface roughness of solidified material below a thick layer of unmolten material (>200 µm) serve as seeding points for larger voids. The orientation of the first two layers fully exposed after a thick layer of unmolten powder shapes the orientation of these voids, created by a lack of fusion.
In this chapter, the current state-of-the-art of in situ monitoring and in situ NDE methods in additive manufacturing is summarized. The focus is set on methods, which are suitable for making statements about the quality and usability of a component currently being manufactured. This includes methods which can be used to determine state properties like temperature or density, other physical properties like electrical or thermal conductivity, the microstructure, the chemical composition, the actual geometry, or which enable the direct detection of defects like cracks, voids, delaminations, or inclusions. Thus, optical, thermographic, acoustic, and electromagnetic methods, as well as methods being suitable for investigating particle and fume emission are presented. The requirements of in situ monitoring methods with a focus on thermographic methods are discussed by considering different additive manufacturing processes like laser powder bed fusion (PBF-LB/M) and direct energy deposition (DED-LB/M). Examples of the successful implementation and applications of such monitoring methods at BAM are given. The in situ monitoring and NDE methods are compared against post-process NDE methods. The advantages and challenges of in situ methods concerning real-time data analysis and the application of AI algorithms are addressed and discussed.
Laser powder bed fusion is used to create near net shape metal parts with a high degree of freedom in geometry design. When it comes to the production of safety critical components, a strict quality assurance is mandatory. An alternative to cost-intensive non-destructive testing of the produced parts is the utilization of in-situ process monitoring techniques. The formation of defects is linked to deviations of the local thermal history of the part from standard conditions. Therefore, one of the most promising monitoring techniques in additive manufacturing is thermography. In this study, features extracted from thermographic data are utilized to investigate the thermal history of cylindrical metal parts. The influence of process parameters, part geometry and scan strategy on the local heat distribution and on the resulting part porosity are presented. The suitability of the extracted features for in-situ process monitoring is discussed.
The quality of additively manufactured components is significantly influenced by the process parameters used during production. Thus, sensors and measuring systems are already commercially available for process monitoring, at least in metal-based additive manufacturing. However, it is not yet possible to detect defects and inhomogeneities directly or indirectly during the building process. The aim of the project ProMoAM is to develop spectroscopic and non-destructive testing methods for the in-situ evaluation of the quality of additively manufactured metal components in laser- or arc-based AM processes. In addition to passive and active methods of thermography, this includes optical tomography, optical emission spectroscopy, eddy current testing, laminography (radiography), X-ray backscattering, particle emission spectroscopy and photoacoustic methods.
Due to the rapid thermal cycles involved in additive manufacturing of metals, high internal stresses and peculiar microstructures occur, which influence the parts mechanical properties. To systematically examine their formation, in-process measurements of the temperature are needed. Since the part emissivity is strongly inhomogeneous and rapidly changing in the process, the applicability of thermography for the determination of thermodynamic temperatures is limited. Measuring the thermal radiation in different wavelengths simultaneously, temperature and emissivity can be separated. Here, we present results of a preliminary study using multispectral thermography to obtain real temperatures and emissivities in directed energy deposition (DED) processes.