Powder Bed Fusion via Machine Learning-Enabled Approaches

نویسندگان

چکیده

Powder bed fusion (PBF) applies to various metallic materials used in the metal printing process of building a wide range complex parts compared other AM technologies. PBF has several variants such as DMLS (direct laser sintering), EBM (electron beam melting), SHS (selective heat SLM and SLS sintering). For reach its maximum potential, machine learning (ML) algorithms are with suitable achieve goals cost-effectively. Various applications neural networks, including ANNs, CNNs, RNNs, popular techniques KNN, SVM, GP were reviewed, future challenges discussed. Some special-purpose listed follows: GAN, SeDANN, SCNN, K-means, PCA, etc. This review presents evolution, current status, challenges, prospects these technologies terms material, features, parameters, applications, advantages, disadvantages, etc., explain their significance provide an in-depth understanding same.

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ژورنال

عنوان ژورنال: Complexity

سال: 2023

ISSN: ['1099-0526', '1076-2787']

DOI: https://doi.org/10.1155/2023/9481790