Soft Modeling Approach in Predicting Surface Roughness, Temperature, Cutting Forces in Hard Turning Process Using Artificial Neural Network: An Empirical Study-Reference-Cited by-同舟云学术

Soft Modeling Approach in Predicting Surface Roughness, Temperature, Cutting Forces in Hard Turning Process Using Artificial Neural Network: An Empirical Study

Published:2019 Issue: Volume: Page:206-215
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Gupta Navriti^ORCID,Agrawal A. K.,Walia R. S.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-1384-8_17

Reference16 articles.

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3. Kaladhar, M.: Evaluation of hard coating materials performance on machinability issues and MRR during turning operations. Measurement 135, 493–502 (2019)

4. Aydın, M., Karakuzu, C., Uçar, M., Cengiz, A., Çavuşlu, M.A.: Prediction of SR and cutting zone temperature in dry turning process of AISI 304 stainless steel using ANFIS with Particle Swarm Optimization learning. Int. J. Adv. Manuf. Technol. 67, 957–967 (2013)

5. Oktem, H., Erzurumlu, T., Erzincanli, F.: Prediction of minimum surface roughness in end milling mold parts using NN and GA. Mater. Des. 27(9), 735–744 (2006)

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