Aluminum-based metal matrix composites (AMCs) play a vital role for potential applications in aerospace and automotive industries. This paper explores the experimental analysis of a composite with aluminum LM4 alloy as the matrix and tungsten carbide (WC) as the reinforcement material. The composite specimens were fabricated by the stir casting process. The reinforced ratios of 5, 10 and 15 wt.% of WC particulates were stirred in molten aluminum LM4 alloy (AALM4). Once the composite is solidified, the specimens are prepared to the required ASTM dimensions and tested for various mechanical properties such as tensile strength, impact strength and hardness. Moreover, the tribological behavior of the composite was studied using the pin-on-disc wear test apparatus. X-ray diffraction (XRD) analysis was conducted to analyze the various elements present in the composites. Finally, the scanning electron microscope (SEM) analysis reveals the uniform distribution of WC particles in Aluminum LM4 alloy matrix. The improvement in mechanical properties – hardness, impact strength and tensile strength – was achieved for the increase in the addition of wt.% of WC particles in the LM4 matrix. The decrease in mass loss was observed for the composite containing 15 wt.% of WC during the wear test among the various composites tested.

In the present communication an effective parametric analysis on the mechanical properties (tensile and flexural strength) of bagasse fiber-reinforced vinyl ester (BFRVE) composites were conducted, and then the fabrication process parameters were optimized by using Taguchi and analysis of variance techniques. Composites plates were fabricated by Taguchi’s L₁₈ experimental design as the function of process parameters such as fiber length, fiber content, fiber diameter, sodium hydroxide concentration and sodium hydroxide treatment duration. The optimum process parameters to obtain the maximum strength values were identified using signal-to-noise ratio calculations. Then, the results were analyzed to know the percentage contribution of each fabrication process parameter on the tensile and the flexural strength using analysis of variance. A multivariable non-linear regression model was developed to predict the strength values and compared with experimental strength values. The developed models were validated by 10 additional experimental results using the mean absolute percentage error (MAPE). The results reveal that the fiber content (40 wt%) is the most significant factor influencing the tensile and flexural strength. An acceptable level of mean absolute percentage errors (8.57% for tensile strength and 9.13% for flexural strength) was obtained in both cases. Finally, the results indicate that this model can be used efficiently for prediction of tensile and flexural strength of BFRVE composites without any further experiments.

Silicon nitride (Si3N4) is a widely used reinforcement material to improve the mechanical properties of the aluminium matrix composites. Aluminium alloy (AA 6063) matrix composite was produced with different wt. % of Si3N4 content through stir casting route. L27 orthogonal array was used to conduct the wear test in Pin-on-disc apparatus. The wear parameters were optimized by S/N ratio and ANOVA analysis. SEM images of the composites show the uniform distribution of Si3N4 particles in AA6063 matrix and its composition was confirmed by EDS analysis. As a result, the minimum wear rate was obtained for the composite contains 10 wt. % Si3N4, load of 29.43 N, sliding distance of 1500 m and the sliding velocity of 3 m/s. ANOVA result reveals that, the weight percentage of reinforcement has the higher percentage of contribution to influence the wear rate of the composite. The confirmation test was conducted and the results are well agreed with optimized parameters.