Abstract
Application of reinforced composite material enhanced in recent days compared to earlier conventional material due to its specific strength, high hardness, less weight, and better wear performance capacity. This paper deals with the wear resistance behaviour of different weight percentages of SiC particles dispersed aluminium matrix composites fabricated by stir casting. Scanning Electron Microscope (SEM) analysis revealed that uniform distribution of SiC particulates throughout the aluminium matrix. Wear analysis of formed composite was evaluated by using Taguchi L16 orthogonal array to minimize the total number of experimental runs. In order to obtain an efficient wear rate, four major factors such as reinforcement quantity (3, 5, 7 and 9%), applied load (10, 20, 30 and 40 N), sliding velocity (0.5, 1, 1.5 and 2 m/s) and sliding distance (500, 1000, 1500 and 2000 m) were varied four various levels. Analysis of Variance (ANOVA) result revealed that the probability value of the applied load was lesser than 0.05 that expressed the factor of significance. In this work, maximum Grey Relational Grade (GRG) and Grey Fuzzy Grade (GFG) results are observed 0.798 and 0.772 respectively to optimized factors of 9 wt.% SiC reinforcement, 10 N applied load, 2 m/s sliding velocity and 500 m sliding distance. It is concluded that the grey-fuzzy approach significantly strengthens the decision making of tribological behaviour instead of a simple grey relational grade.
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Authors wish to thank CIC of Tripura University for SEM analysis.
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Abhijit Bhowmik carried out casting and wear test of aluminium matrix composite. Suman Dey optimized output data that collected from pin on disc wear test. Dipankar Dey carried out the data analysis and drafted the manuscript. Ajay Biswas prepared the introduction part and microstructure evaluation. All authors read and approved the final manuscript for publication.
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Bhowmik, A., Dey, S., Dey, D. et al. Dry Sliding Wear Performance of Al7075/SiC Composites by Applying Grey-Fuzzy Approach. Silicon 13, 3665–3680 (2021). https://doi.org/10.1007/s12633-020-00930-3
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DOI: https://doi.org/10.1007/s12633-020-00930-3