Parametric analysis on drilling of aluminium alloy hybrid composites reinforced with SIC/WC

Parametric analysis on drilling of aluminium alloy hybrid composites reinforced with SIC/WC S Senthil Babu http://orcid.org/0000-0003-4300-2164 C Dhanasekaran G Anbuchezhiyan http://orcid.org/0000-0001-7346-8876 Kumaran Palani http://orcid.org/0000-0002-7978-1617 Abstract

Aluminium alloy (Al7075) based hybrid metal matrix composites reinforced with Silicon carbide (SiC) and Tungsten carbide (WC), at 5 wt% each are considered for this investigation, which are developed by stir casting methodology. Material characteristic analysis both at micro and macro (Tensile strength and micro hardness) level were performed. This investigation is further progressed with drilling of the composites using titanium aluminium nitride coated carbide drill (5mm diameter) for varied point angle, feed rate and drill speed. The responses such as thrust force, surface roughness and roundness error were investigated by adopting Response Surface Methodology (RSM). Multiple linear regression (MLR) is developed along with Artificial Neural Networks (ANN) model for predicting the outputs. Scanning Electron Microscope (SEM) image reveals the uniform distribution of ceramic particles in matrix which ascertains enhanced mechanical properties. The parameters such as feed rate and point angle are found to have significant influence during drilling process. The roundness error is found higher with higher point angle which is due to the wider cutting edges in the drill bit. For unconstrained multi-objective optimization, the optimal condition obtained are 128°- point angle, 0.05 mm rev −1 feed rate and 1000 rpm drill speed. For constrained optimization (roundness error ≤0.05 mm), optimal conditions are 118° point angle, 0.05 mm rev −1 feed rate and 1000 rpm drill speed.
06 01 2022 06 01 2022 025036 http://dx.doi.org/10.1088/crossmark-policy iopscience.iop.org Parametric analysis on drilling of aluminium alloy hybrid composites reinforced with SIC/WC Engineering Research Express paper © 2022 The Author(s). Published by IOP Publishing Ltd 2022-03-22 2022-05-16 2022-06-01 http://creativecommons.org/licenses/by/4.0/ https://iopscience.iop.org/info/page/text-and-data-mining 10.1088/2631-8695/ac7038 https://iopscience.iop.org/article/10.1088/2631-8695/ac7038 https://iopscience.iop.org/article/10.1088/2631-8695/ac7038/pdf https://iopscience.iop.org/article/10.1088/2631-8695/ac7038/pdf https://iopscience.iop.org/article/10.1088/2631-8695/ac7038/pdf https://iopscience.iop.org/article/10.1088/2631-8695/ac7038/pdf https://iopscience.iop.org/article/10.1088/2631-8695/ac7038 https://iopscience.iop.org/article/10.1088/2631-8695/ac7038/pdf https://iopscience.iop.org/article/10.1088/2631-8695/ac7038 https://iopscience.iop.org/article/10.1088/2631-8695/ac7038/pdf TOJSAT Hayajneh 1 18 2011 Modeling the drilling process of some Al-Mg-Cu alloys and Al-Mg-Cu/SiC composites using artificial neural network Procedia Materials Science Gowda 10.1016/j.mspro.2014.07.208 6 1780 2014 Estimation of circularity, cylindricity and surface roughness in drilling Al-Si3N4 metal matrix composites using artificial neural network Journal of Minerals and Materials Characterization and Engineering Mayyas 10.4236/jmmce.2012.1110108 11 1039 2012 Modeling the drilling process of aluminum composites using multiple regression analysis and artificial neural networks Indian Journal of Science and Technology Babu 8 1 2015 Prediction of surface roughness in drilling of Al 7075/10%-SiCp composite under MQL condition using fuzzy logic Transactions of Nonferrous Metals Society of China Taskesen 10.1016/S1003-6326(13)62764-8 23 2524 2013 Analysis and optimization of drilling parameters for tool wear and hole dimensional accuracy in B4C reinforced Al-alloy Transactions of Nonferrous Metals Society of China Rajmohan 10.1016/S1003-6326(11)61317-4 22 1286 2012 Optimization of machining parameters in drilling hybrid aluminium metal matrix composites J. 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