Journal of Manufacturing and Materials Processing, Volume 8, Issue 1
2024 February - 42 articles
Cover Story: Multi-Material Jetting yields high precision in additive manufacturing of ceramics and metals, but it poses challenges in the choice of building strategies, as improper droplet overlap affects the process stability. The study addresses classification of process parameterization based on in-line surface measurements on green parts and processing with machine learning methods, in particular convolutional neural networks. Demo parts printed with different overlaps are scanned and labeled. Models with two convolutional layers and a pooling size of (6, 6) yield the best accuracies. Models trained only with images of the first layer obtained validation accuracies of 90%. Consequently, an arbitrary section of the first layer is sufficient to deliver a prediction about the quality of subsequently printed layers. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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