Prediction of spring-back and bend force in air bending of electro-galvanised steel sheets using artificial neural networks-Reference-Cited by-同舟云学术

Prediction of spring-back and bend force in air bending of electro-galvanised steel sheets using artificial neural networks

Published:2014-01 Issue:1 Volume:12 Page:25-37
ISSN:1448-4846
Container-title:Australian Journal of Mechanical Engineering
language:en
Short-container-title:Australian Journal of Mechanical Engineering

Author:

Srinivasan R¹,Vasudevan D²,Padmanabhan P³

Affiliation:

1. Department of Mechanical Engineering, RatnaVel Subramaniam College of Engineering and Technology, Dindigul, Tamil Nadu, India

2. Department of Mechanical Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India

3. Department of Mechanical Engineering, VV College of Engineering, Tisaiyanvilai, Tamilnadu, India

Publisher

Informa UK Limited

Subject

Mechanical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.7158/M12-073.2014.12.1

Reference3 articles.

1. Test Methods for Tension Testing of Metallic Materials

2. Farsi, M. A. & Arezoo, B. 2009, “The determination of spring-back in L bending operation using neural networks”, Proceedings of 5 th International Advanced Technologies Symposium, Turkey.

3. Hagen, M. T., Demuth, H. B. & Beale, M. H. 1996, Neural network design, PWS Publishing Company, Boston.

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial intelligence and its relevance in mechanical engineering from Industry 4.0 perspective;Australian Journal of Mechanical Engineering;2023-08-21

2. Applying a new artificial intelligence algorithm to Optimize technological parameters when polishing K9 optical lens materials by magnetized liquid solution;Australian Journal of Mechanical Engineering;2023-07-25

3. Analysis of spring back behaviour during bending of AISI 1045 sheet metal;Materials Today: Proceedings;2022

4. A Versatile Punch Stroke Correction Model for Trial V-Bending of Sheet Metals Based on Data-Driven Method;Materials;2021-08-24

5. The sustainability of neural network applications within finite element analysis in sheet metal forming: A review;Measurement;2019-05