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Data driven method for predicting the effect of process parameters on the fatigue response of additive manufactured AlSi10Mg parts

Alberto Ciampaglia, Andrea Tridello, Davide Salvatore Paolino, Filippo Berto

2023International Journal of Fatigue66 citationsDOI

Topics & Concepts

InterpretabilityProcess (computing)Artificial neural networkManufacturing processMaterials scienceComputer scienceProcess engineeringEngineeringMachine learningComposite materialOperating systemAdditive Manufacturing Materials and ProcessesAdditive Manufacturing and 3D Printing TechnologiesWelding Techniques and Residual Stresses
Data driven method for predicting the effect of process parameters on the fatigue response of additive manufactured AlSi10Mg parts | Litcius