Authors:
Satish Kumar, P. Paramasivan, Saly Jaber
Addresses:
Department of Mechanical Engineering, Chandigarh Group of Colleges, Mohali, Punjab, India. Department of Research and Development, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Analytical Chemistry, Saint Joseph University, Beirut, Beirut Governorate, Lebanon.
Abstract:
The goal of the current study is to conduct microstructural analysis and processing of various weight percentages of Al2O3 particle-reinforced Al matrix composite produced by liquid metallurgy stir casting. The field of interest is to establish a generalized correlation between process parameters, reinforcement weight percentage, and the resulting microstructural features and mechanical properties. Composites 0 wt%, 3 wt%, 6 wt%, 9 wt%, and 12 wt% weight percentage Al2O3 have been produced. Microstructure was aptly characterized by Scanning Electron Microscopy (SEM) for qualitative data of particle distribution, porosity, and interface integrity, supported by Energy Dispersive X-ray Spectroscopy (EDS) for elemental analysis. Quantitative data were obtained using ImageJ software to characterize defects (porosity) and particle agglomeration (agglomeration index). Vickers hardness and wear rate were quantitatively evaluated as mechanical properties. The model is derived from a test dataset of 453 samples and scales process inputs (e.g., stirring rate, wt% Al2O3) to quantitative responses (e.g., hardness, porosity %). Calculations using mathematics were performed with MATLAB, and ANOVA tables of the correlation matrices were calculated. The result is always that, as Al2O3 particle levels increase, hardness increases, but at the cost of a preposterous rise in porosity and particle agglomeration, necessitating a drastic compromise in handling.
Keywords: Aluminum Matrix Composites (AMC’s); Quantitative Data; Mathematical Calculations; Mechanical Properties; Scanning Electron Microscopy; Microstructural Analysis.
Received on: 17/07/2024, Revised on: 27/08/2024, Accepted on: 01/12/2024, Published on: 12/09/2025
DOI: 10.64091/ATIAS.2025.000241
AVE Trends in Intelligent Applied Sciences, 2025 Vol. 1 No. 3 , Pages: 117–126