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- W4365511067 abstract "Cyber manufacturing service, which connects end users with manufacturers over the internet, is significantly hampered by the lack of an automated part retrieval method. The state-of-the-art is focused on automatic shape retrieval, which does not consider manufacturing process requirements, such as material properties. This paper proposes a manufacturing process-aware part retrieval method using deep unsupervised learning that considers both part shape and material properties. Part retrieval results show that the proposed method yields 93.0% process and function class label matching precision, which outperforms the shape-only part retrieval model and supervised learning models trained with process, function, or both labels." @default.
- W4365511067 created "2023-04-15" @default.
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- W4365511067 date "2023-01-01" @default.
- W4365511067 modified "2023-10-14" @default.
- W4365511067 title "Process-aware part retrieval for cyber manufacturing using unsupervised deep learning" @default.
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- W4365511067 doi "https://doi.org/10.1016/j.cirp.2023.03.020" @default.
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