Молимо вас користите овај идентификатор за цитирање или овај линк до ове ставке:
https://open.uns.ac.rs/handle/123456789/8784
Назив: | Artificial neural network application for surface roughness prediction when drilling nickel based alloy | Аутори: | Man̂ková I. Vrabe M. Kovac P. |
Датум издавања: | 31-јул-2013 | Часопис: | Manufacturing Technology | Сажетак: | Article deals with design of appropriate artificial neural network for prediction of surface roughness as one of the very important indicators of machined surface quality. The drilling of nickel based super alloy UDIMET 720, was applied as test material. This type of material is most frequently used for jet engines components such as discs etc. Experimental data collected from tests were used as input parameters into neural network to identify the sensitivity among cutting conditions, tool wear and monitoring parameters and surface roughness. Selected parameters were used to design a suitable algorithm for control and monitoring of the drilling process with respect on surface roughness. The accuracy of predicted and measured values are compared and discussed. © 2013 Published by Manufacturing Technology. | URI: | https://open.uns.ac.rs/handle/123456789/8784 | ISSN: | 12132489 |
Налази се у колекцијама: | Naučne i umetničke publikacije |
Приказати целокупан запис ставки
SCOPUSTM
Навођења
10
проверено 22.02.2020.
Преглед/и станица
18
Протекла недеља
9
9
Протекли месец
1
1
проверено 10.05.2024.
Google ScholarTM
Проверите
Ставке на DSpace-у су заштићене ауторским правима, са свим правима задржаним, осим ако није другачије назначено.