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Predicting critical machining conditions using time-series imaging and deep learning in slot milling of titanium alloy

Metadaten
Author:Faramarz Hojati, Bahman AzarhoushangORCiDGND
URN:urn:nbn:de:bsz:fn1-opus4-86213
ISBN:978-3-00-073638-4
Parent Title (English):The Upper-Rhine Artificial Intelligence Symposium UR-AI 2022 : AI Applications in Medicine and Manufacturing, 19 October 2022, Villingen-Schwenningen, Germany
Publisher:Furtwangen University
Place of publication:Furtwangen
Document Type:Conference Proceeding
Language:English
Year of Completion:2022
Release Date:2022/10/20
Tag:Artificial intelligence; Convolutional neural network; Edge box; Gramian angular field; Slot-milling
First Page:57
Last Page:63
Open-Access-Status:Open Access
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International