Image Texture Description, Surface-Grains Structure Morphology and Prediction of Wear Parameters for Mg/B4C Composites Using Response Surface Methodology

M. Navaneetha Krishnan; S. Suresh; S. C. Vettivel; C. Emmy Prema; J. Arun; P. Thirunamakodi

doi:10.1007/s12540-021-01042-2

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자료유형: 학술저널

저자정보: M. Navaneetha Krishnan (Amrita College of Engineering and Technology) S. Suresh (University College of Engineering) S. C. Vettivel (Chandigarh College of Engineering and Technology) C. Emmy Prema (Bethlahem Institute of Engineering) J. Arun (Marian Engineering College) P. Thirunamakodi (Universal College of Engineering and Technology)

저널정보: 대한금속·재료학회 Metals and Materials International Metals and Materials International Vol.28 No.5

발행연도: 2022.5

수록면: 1,195 - 1,214 (20page)

DOI: 10.1007/s12540-021-01042-2

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The different percentages of boron carbide (B4C) reinforced Magnesium metal matrix composites were processed usingPowder Metallurgy method. The characterizations are performed by Scanning Electronic Microscope (SEM), X-ray Diffractionpattern, Electron Backscattered Diffraction, and Energy Dispersive Spectrum. The texture analysis of the composites isconducted via an image processing method. Wear tests are executed in the dry sliding state under ambient room conditions. The three levels Box-Behnken design of Response Surface Methodology has been selected to create the mathematical modelsfor the three variables (weight percentage of B4C,sliding velocity, and load) to predict the responses namely specific wearrate (SWR) and coefficient of friction (COF). The developed model is validated and analyzed through the Analysis of variance(ANOVA). This model has a 95% efficient confidence to forecast the COF and SWR. The worn surface features areextracted and analyzed through an image processing technique. The roughness measurement of the worn surfaces is executedvia Atomic Force Microscopy analysis.

#Mg/B4C composite · Powder metallurgy · EBSD · Wear · RSM · Box-behnken design · ANOVA · AFM

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