Modelling fatigue life prediction of additively manufactured Ti-6Al-4V samples using machine learning approach

Jan Horňas,Jiří Běhal,Petr Homola,Sascha Senck,Martin Holzleitner,Norica Godja,Zsolt Pásztor,Bálint Hegedüs,Radek Doubrava,Roman Růžek,Lucie Petrusová

International Journal of Fatigue（2023）

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摘要

•ML framework for fatigue life prediction of AM Ti-6Al-4V samples is proposed.•ANN, RFR and SVR models are used for fatigue life prediction.•Spearman’s rank correlation test is applied to identify insensitive features.•The LOOCV technique is employed in the optimization of the ML models.

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关键词

Selective laser melting (SLM), Ti-6Al-4V, Micro-computed tomography (mu CT), Fatigue life prediction, Machine learning (ML)

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