Prediction of Cutting Forces in Hard Turning Process Using Machine Learning Methods: A Case Study-Reference-Cited by-同舟云学术

Prediction of Cutting Forces in Hard Turning Process Using Machine Learning Methods: A Case Study

Published:2023-08-07 Issue: Volume: Page:
ISSN:1059-9495
Container-title:Journal of Materials Engineering and Performance
language:en
Short-container-title:J. of Materi Eng and Perform

Author:

Makhfi Souâd^ORCID,Dorbane Abdelhakim^ORCID,Harrou Fouzi^ORCID,Sun Ying^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://link.springer.com/content/pdf/10.1007/s11665-023-08555-4.pdf

Reference48 articles.

1. S.K.S.R. Schmid, Manufacturing Engineering and Technology. J. Mater. Process. Technol. (2013).

2. S. Makhfi, K. Haddouche, A. Bourdim, and M. Habak, Modeling of Machining Force in Hard Turning Process, Mech. Kauno Technol. Univ., 2018, 24(3), p 367–375.

3. M.W. Azizi, O. Keblouti, L. Boulanouar, and M.A. Yallese, Design Optimization in Hard Turning of E19 Alloy Steel by Analysing Surface Roughness, Tool Vibration and Productivity, Struct. Eng. Mech., 2020, 73(5), p 501–513.

4. S. Roy, R. Kumar, A.K. Sahoo, A. Pandey, and A. Panda, Investigation on Hard Turning Temperature under a Novel Pulsating MQL Environment: An Experimental and Modelling Approach, Mech. Ind., 2020, 21(6), p 605.

5. A. Chavan and V. Sargade, Surface Integrity of AISI 52100 Steel during Hard Turning in Different Near-Dry Environments, Adv. Mater. Sci. Eng., 2020, 2020, p 1.

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