High-throughput stochastic tensile performance of additively manufactured stainless steel

Abstract

An adage within the Additive Manufacturing (AM) community is that-complexity is free‖. Complicated geometric features that normally drive manufacturing cost and limit design options are not typically problematic in AM. While geometric complexity is usually viewed from the perspective of part design, this advantage of AM also opens up new options in rapid, efficient material property evaluation and qualification. In the current work, an array of 100 miniature tensile bars are produced and tested for a comparable cost and in comparable time to a few conventional tensile bars. With this technique, it is possible to evaluate the stochastic nature of mechanical behavior. The current study focuses on stochastic yield strength, ultimate strength, and ductility as measured by strain at failure (elongation). However, this method can be used to capture the statistical nature of many mechanical properties including the full stress-strain constitutive response, elastic modulus, work hardening, and fracture toughness. Moreover, the technique could extend to strain-rate and temperature dependent behavior. As a proof of concept, the technique is demonstrated on a precipitation hardened stainless steel alloy, commonly known as 17-4PH, produced by two commercial AM vendors using a laser powder bed fusion process, also commonly known as selective laser melting. Using two different commercial powder bed platforms, the vendors produced material that exhibited slightly lower strength and markedly lower ductility compared to wrought sheet. Moreover, the properties were much less repeatable in the AM materials as analyzed in the context of a Weibull distribution, and the properties did not consistently meet minimum allowable requirements for the alloy as established by AMS. The diminished, stochastic properties were examined in the context of major contributing factors such as surface roughness and internal lack-of-fusion porosity. This high-throughput capability is expected to be useful for follow-on extensive parametric studies of factors that affect the statistical reliability of AM components.

Corroborating tomographic defect metrics with mechanical response in an additively manufactured precipitation-hardened stainless steel

“…Details regarding these matters could provide additional insight into the processing window thereby better informing the true state of the manufactured material. As an example, Energy Dispersive Spectroscopy (EDS) revealed elevated levels of both oxygen and nitrogen in the asbuilt parts along with a few other anomalies 41,42 . Without a clear line of sight to the feedstock material and the layer by layer build strategy, it is unclear whether these elemental and phase composition anomalies were precipitated by the initial powder or occurred as a result of the additive process.…”

“…As mentioned previously, from mechanical testing, yield strength, ultimate strength, elongation to failure and modulus were evaluated and have been documented in detail 41,42 . For the sake of this discussion, the correlation of pre-existing defects with mechanical response will be limited to yield stress as these represented the highest correlations observed.…”

Extreme‐Value Statistics Reveal Rare Failure‐Critical Defects in Additive Manufacturing

“…The microstructure of the heat treated tensile bars, shown in Figure 2, is predominantly martensitic with uniformly distributed equiaxed particles which appear bright in the image. [8] These dispersed particles are associated with the MC-type Nb-rich carbides/carbonitrides expected in 17-4PH. [9,10] Solute homogenization and phase transformations occurring during the solution and age heat treatments results in a microstructure devoid of original solidification features.…”

“…Generally, the microstructure is qualitatively similar to wrought product. [8] X-ray computed tomography was performed with a 1500uA x-ray tube operating at 160 kV to identify and evaluate the global pore character within the tensile bars, as shown in Figure 3. The voxel edge length for the current x-ray tomography setup was 10.2 mm, and therefore smaller voids could not be detected.…”

“…An efficient tensile test method [8] was employed to evaluate the build-to-build (inter-build) and within-build (intra-build) variation of mechanical properties. The tensile test was streamlined for efficiency through three adaptations: (i) drop-in grips to reduce sample loading time, as shown in Figure 1b, (ii) a non-contact virtual extensometer enabled by real-time digital image correlation (DIC), [11] as shown in Figure 1c, and (iii) software-based test automation and posttest data analysis algorithms.…”