Predicting critical machining conditions using time-series imaging and deep learning in slot milling of titanium alloy
Download full text files
Additional Services
Statistics
| Document Type: | Conference Proceeding |
|---|---|
| Author: | Faramarz Hojati, Bahman AzarhoushangORCiDGND |
| URN: | https://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 |
| 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): |  Creative Commons - CC BY - Namensnennung 4.0 International |