Fatigue properties of AlSi10Mg obtained by additive manufacturing: Defect-based modelling and prediction of fatigue strength

Ability to predict the fatigue resistance of parts produced by additive manufacturing (AM) is a very current and frequently relevant open issue. The qualification of AM structural parts often needs a costly and time-consuming series of fatigue tests, on both samples and full-scale parts. Proper control of the AM process allows obtaining comparable and even better fatigue resistance than those obtained with standard manufacturing. Despite this, the experimental results often show a large scatter, mostly due to the presence of defects. In this framework, the present work summarizes the research activity aimed at modelling the high cycle fatigue (HCF) resistance in the presence of defects, focusing on AlSi10Mg produced by selective laser melting. Three batches of samples were investigated by X-ray micro computed tomography and tested under fatigue. A lower bound resistance curve was obtained, which introduced artificial defects of size corresponding to that of the largest occurring defects. The analysis shows that a combination of defect-tolerant design with well-established and newly proposed fracture mechanics methods is the key to expressing the relationship between the fatigue strength and material quality. This is done through suitable statistics of material defects induced by the AM process. The same concepts are then applied in a fatigue crack growth simulation model based on the maximum defect size, for estimating both the life and scatter of the data in the region of elastic material response. Based on this wide activity, it can be concluded that fracture mechanics-based analysis appears to be the tool needed for supporting the application of additive manufacturing to safety-critical components and their qualification. (C) 2017 Elsevier Ltd. All rights reserved.