2023
DOI: 10.1080/00325899.2023.2191236
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Rheological characterisation of water atomised tool steel powders developed for laser powder bed fusion by supervised and unsupervised machine learning

Abstract: Metal powders developed for additive manufacturing processes need to achieve specific flow characteristics to be considered suitable. However, for the relationship between powder flow and the morphological characteristics of individual particles can be difficult to establish. In this context, artificial intelligence appears to be the perfect tool to clarify the imprecision surrounding this type of interaction. The work summarised in this manuscript first uses a neural network architecture (Mask R-CNN) allowing… Show more

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