Fatigue of laser powder-bed fusion additive manufactured Ti-6Al-4V in presence of process-induced porosity defects

Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modeling

“…There are many defects in AM metals, and the cracks usually initiate from the critical defects. [189][190][191] Based on this consideration, the defect-based fracture mechanics methods have been successfully employed to predict the fatigue life of AM materials and achieved good results. 37,46,55,[191][192][193][194][195][196][197][198] Many fatigue crack propagation models have been adopted to predict the fatigue life of AM metals.…”

“…There are many defects in AM metals, and the cracks usually initiate from the critical defects 189–191 . Based on this consideration, the defect‐based fracture mechanics methods have been successfully employed to predict the fatigue life of AM materials and achieved good results 37,46,55,191–198 …”

Laser-induced breakdown spectroscopy and stoichiometry to identify various types of defects in metal-additive manufacturing parts

“…8 Also, holes in parts may be the starting point of failure, which can reduce the fatigue life of samples. 9 Due to the inhomogeneity of the metal structure and obvious anisotropy, 10 the structure and defect characteristics of metal AM components are also different from those of traditional process parts; while the main defect types and distribution characteristics are similar to those of traditional parts. The differences can be large, and it is not a suitable strategy to simply copy the traditional parts detection method, which also creates a major difficulty in the quality control of metal AM parts.…”