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- Additive manufacturing (10)
- Residual stress (5)
- Synchrotron X-ray diffraction (5)
- Ti-6Al-4V (5)
- Selective laser melting (3)
- Computed tomography (2)
- Heat treatment (2)
- Microscopy (2)
- Porosity (2)
- X-ray computed tomography (2)
Organisationseinheit der BAM
For the first time, X-ray refraction techniques are proven for the identification of void formation in Ti-6Al-4V parts produced by selective laser melting. The topology and volume fraction of pores are measured in samples produced with different laser energy density. Unique X-ray refraction methods identify different kinds of defects, characteristic to the regions below and above the Optimum laser energy density, namely unprocessed powder (unmolten powder particles, balling effect, and Fusion defects) from empty keyhole pores. Furthermore, it is possible to detect small inhomogeneities (voids or cracks) with sizes below the spatial resolution of optical microscopy and X-ray computed tomography.
The contour scan strategies in laser powder bed fusion (LPBF) of Ti-6Al-4V were studied at the coupon level. These scan strategies determined the surface qualities and subsurface residual stresses. The correlations to these properties were identified for an optimization of the LPBF processing. The surface roughness and the residual stresses in build direction were linked: combining high laser power and high scan velocities with at least two contour lines substantially reduced the surface roughness, expressed by the arithmetic mean height, from values as high as 30 μm to 13 μm, while the residual stresses rose from ~340 to about 800 MPa. At this stress level, manufactured rocket fuel injector components evidenced macroscopic cracking. A scan strategy completing the contour region at 100 W and 1050 mm/s is recommended as a compromise between residual stresses (625 MPa) and surface quality (14.2 μm). The LPBF builds were monitored with an in-line twin-photodiode-based melt pool monitoring (MPM) system, which revealed a correlation between the intensity quotient I2/I1, the surface roughness, and the residual stresses. Thus, this MPM system can provide a predictive estimate of the surface quality of the samples and resulting residual stresses in the material generated during LPBF.