Modeling and Predicting Abrasive Wear Behavior of Al–SiCp Composite Using Multi-response Optimization-Based RSM
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In this investigation, different composites of Al–SiCp have been prepared using investment casting route to characterize the tribological properties like abrasive wear and coefficient of friction. The experimental plans are based on central composite design. The effect of process parameters (i.e., applied load, rpm and weight percentage of SiC) on output parameter (i.e., wear rate and coefficient of friction) has been studied. A model based on regression analysis technique has been developed, to predict the response, i.e., wear behavior and coefficient of friction of the metal matrix composites. The adequacy and statistical significance of the developed model have been tested on ANOVA which directly shows the contribution of input parameters on output parameter. Graphical contours are used to study the direct and interaction effects. The finding of results can be concluded as the wear rate diminishes with the increase in % SiCp due to thermal stability of Al matrix which restricts the softening behavior when temperature rises. The coefficient of friction shows an increase in value may be due to resistance of sliding action by ceramic particles in the composite. The ANOVA analysis using multi-response optimization of response surface methodology suggests that the optimum results are achieved with 93.32% desirability level, having 15 wt% of SiCp, 2 kg of load and 300 rpm of minimum wear rate and frictional coefficient.
KeywordsMetal matrix composites (MMC) Abrasive wear Coefficient of friction
The author thanks Director of CSIR-CMERI, Durgapur, for his kind permission to publish this investigation in a reputed journal. The author also likes to thank all staff member of Centre for Advance Materials Processing group. This work is funded by Science and Engineering Research Board (SERB) of Department of Science and Technology (DST), Government of India, New Delhi, for financial support (SB/S3/MMER/0035/2014 dated May 22, 2014).
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