Research on the Prediction Model of Milling Force and Temperature for High-Speed Milling of NAK80 Die Steel by Ultrasonic Atomization Micro-Lubrication Combined With Uniform Method and Back Propagation Neural Network-Reference-Cited by-同舟云学术

Research on the Prediction Model of Milling Force and Temperature for High-Speed Milling of NAK80 Die Steel by Ultrasonic Atomization Micro-Lubrication Combined With Uniform Method and Back Propagation Neural Network

Published:2022-11-03 Issue: Volume: Page:
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Container-title:2022 International Conference on Fuzzy Theory and Its Applications (iFUZZY)
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Author:

Huang Wei-Tai¹,Shih Po-Hsun¹,Lin Yi-Cheng¹,Tsai Jinn-Tsong²,Chou Jyh-Horng³

Affiliation:

1. National Pingtung University of Science and Technology,Department of Mechanical Engineering,Pingtung 911,Taiwan, ROC

2. National Pingtung University,Department of Computer Science and Artificial Intelligence,Pingtung 900,Taiwan, ROC

3. Feng Chia University,Department of Mechanical and Computer-Aided Engineering,Taichung 407,Taiwan, ROC

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9985216/9985217/09985233.pdf?arnumber=9985233

Reference20 articles.

1. Optimization of machining parameters on temperature rise in end milling of Al 6063 using response surface methodology and genetic algorithm

2. Mathematical Modelling and Optimization of Cutting Force, Tool Wear and Surface Roughness by Using Artificial Neural Network and Response Surface Methodology in Milling of Ti-6242S

3. Effect of turning parameters in cylindricity and circularity for o1 steel using ANN;jeffrey;Materials Today Proceedings,0

4. Performance evaluation of MQL with AL2O3 mixed nanofluids prepared at different concentrations in milling of Hastelloy C276 alloy;günan;Journal of Materials Research and Technology,2020

5. Artificial neural network (ANN) modelling for the thermal performance of bio fluids