Comparative analysis of thrust force, roughness and roundness error in drilling of aluminium composites using RSM, ANN and fuzzy logic

Author:

Babu S. Senthil,Dhanasekaran C.

Publisher

Elsevier BV

Subject

General Medicine

Reference42 articles.

1. Analysis and Optimization of Surface Roughness in GFRP Drilling Through Integration of Taguchi and Response Surface Methodology;Murthy;Res. J. Eng. Sci.,2013

2. Study on Surface Roughness Minimization in turning of DRACS using Surface Roughness Methodology and Taguchi under pressured Steam Jet approach;Raviraj Shetty;ARPN J. Eng. Appl. Sci.,2008

3. Modeling The Drilling Process Of Some Al-Mg-Cu Alloys And Al-Mg-Cu/Sic Composites Using Artificial Neural Network;Hayajneh;J. Sci. Technol.,2011

4. Estimation of circularity, cylindricity and surface roughness in drilling Al-Si3N4 metal matrix composites using artificial neural network, Procedia;Umesh Gowdaa;Mater. Sci.,2014

5. Modeling the Drilling Process of Aluminum Composites Using Multiple Regression Analysis and Artificial Neural Networks;Mayyas;J. Miner. Mater. Characteriz. Eng.,2012

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1. Investigation of mechanical properties, wear behaviour, and hole quality analysis of Al2014-ZrO 2 -Sn composites;Advances in Materials and Processing Technologies;2024-09-04

2. Multivariate modelling of AA6082-T6 drilling performance using RSM, ANN and response optimization;International Journal of Lightweight Materials and Manufacture;2024-07

3. Modeling and surface morphological study in drilling of Al 2024 alloy;Journal of Manufacturing Processes;2024-01

4. The Effects of the Drill Microgeometry on the Induced Thrust Force and Cutting Torque;Lecture Notes on Multidisciplinary Industrial Engineering;2024

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