2022
DOI: 10.1088/2051-672x/ac59d4
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Prediction of dry sliding wear behaviour of China clay particles reinforced AA6082 matrix composites using response surface methodology and analysis of the worn surfaces

Abstract: This research work presents an attempt solemnly carried out to analyze and predict the wear behaviour of the cost-effective China clay particles reinforced AA6082 aluminium alloy composites. The combined effect of the independent variables (mass fraction of the reinforcement, applied load and sliding speed) on the wear loss and coefficient of friction of the composites were studied. The wear tests were conducted using a computerized pin on disc tribometer. For all the experiments the sliding distance was kept … Show more

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Cited by 4 publications
(2 citation statements)
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References 46 publications
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“…Researchers have developed many statistical models in order to optimize the various parameters for tribological performance of the composites. Many modelling techniques recently being used are Response surface methodology (RSM), Artificial Neural Network (ANN), Taguchi for the optimization of parameters for tribological performance of composites with the aid of statistical tools like Python, Minitab, Design of Experiments, Matlab, etc [13][14][15].…”
Section: Introductionmentioning
confidence: 99%
“…Researchers have developed many statistical models in order to optimize the various parameters for tribological performance of the composites. Many modelling techniques recently being used are Response surface methodology (RSM), Artificial Neural Network (ANN), Taguchi for the optimization of parameters for tribological performance of composites with the aid of statistical tools like Python, Minitab, Design of Experiments, Matlab, etc [13][14][15].…”
Section: Introductionmentioning
confidence: 99%
“…Various researchers explored the tribology of Al alloy hybrid composite by applying different statistical methods such as the Taguchi design approach, Factorial design, Regression analysis, Response surface methodology (RSM), and Artificial Neural Network (ANN) [15][16][17][18][19]. The RSM technique is widely used for a system containing multiple variables to optimise wear variables for optimal system performance [20]. Shoufa Liu et al [21] examined wear properties of Al7075/B 4 C-MoS 2 hybrid composite.…”
Section: Introductionmentioning
confidence: 99%