Prediction of cutting depth in abrasive water jet machining of Ti-6AL-4V alloy using back propagation neural networks

Prediction of cutting depth in abrasive water jet machining of Ti-6AL-4V alloy using back propagation neural networks

The current study focusses on developing a back propagation neural network model for depth of cut during the abrasive water jet machining of a Ti-6AL-4V aluminum alloy. The study analyzed depth of cut for five different water jet abrasive parameters namely, water pressure, transverse speed, abrasive...

Full description

Saved in:
Bibliographic Details
Main Authors: Yakub Iqbal Mogul, Ibtisam Mogul, Jaimon Dennis Quadros, Ma Mohin, Abdul Aabid, Muneer Baig, Mohammad Abdul Malik
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
Subjects:
Back propagation neural network
Abrasive water jet machining
Depth of cut
Ti-6AL-4V aluminum alloy
Taguchi-design of experiments
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025005973
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items