Analyse the surface quality in the milling process by soft computing approaches-Reference-Cited by-同舟云学术

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Analyse the surface quality in the milling process by soft computing approaches

Published:2022 Issue: Volume:69 Page:1462-1464
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

B Radha Krishnan,Ramesh Vellaichamy,C Mathalai Sundaram,R Theerka Tharisanan,L Madan Ananda Kumar

Publisher

Elsevier BV

Subject

General Medicine

Reference12 articles.

1. Influence of surface roughness in turning process—an analysis using artificial neural network;Radha Krishnan;Trans. Can. Soc. Mech. Eng.,2019

2. Performance analysis of surface roughness modeling using soft computing approaches;krishnan;Appl. Math. Inform. Sci.,2018

3. Prediction of surface roughness (AISI 4140 steel) in cylindrical grinding operation by RSM;Krishnan;Int. J. Res. Develop. Technol.,2018

4. Vision-based surface roughness accuracy prediction in the CNC milling process (Al6061) using ANN;Sanjeevi;Mater. Sci.,2021

5. Optimization of machining parameters in plane surface grinding process by response surface methodology;Sanjeevi;Mater. Today:. Proc.,2021

Cited by 2 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. Establishment of Real-Time Adaptive Control Strategy for Milling Parameters;IEEE Access;2023

2. Kinematics and improved surface roughness model in milling;The International Journal of Advanced Manufacturing Technology;2022-12-28

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