Aluminum matrix composites (AMCs) and hybrid aluminum matrix composites (HAMCs) becomes choice for automobile and aerospace industries due to its tunable mechanical properties such as very high strength to weight ratio, superior wear resistance, greater stiffness, better fatigue resistance, controlled co-efficient of thermal expansion and good stability at elevated temperature. Stir casting is an appropriate method for composite fabrication and widely used industrial fabrication of AMCs and HAMCs due to flexibility, cost-effectiveness and best suitable for mass production. Distribution of the reinforcement particles in the final prepared composite regulates the anticipated properties of AMCs and HAMCs. However, distribution of reinforcements is governed by stirring process parameters. The study of effect of stirring parameters in the particle distribution and optimal selection of these is still a challenge for the ever-growing industries and research. In this chapter accurate and precise attempts were taken to explore the effect of stirring parameters in stir casting process rigorously. Further, Optimal values of stirring parameters were suggested which may be helpful for the researchers for the development of AMCs and HAMCs. This chapter may also provide a better vision towards the selection of stirring parameters for industrial production of AMCs and HAMCs comprising superior mechanical properties.
This work is a novel attempt to identify the optimum process parameters in cold upsetting of Al–TiC metal matrix composites with multiple responses using grey Taguchi approach. The formation of barrel and workability are the important attributes that greatly influence the process of upsetting. Three independently controllable process variables, namely, aspect ratio, friction factor and load, each at four levels are considered to find their optimum levels which yields maximum barrel radius and workability simultaneously. Grey Taguchi analysis has been performed to optimize the levels of input parameters. Both the quality characteristics are improved significantly at the optimal process condition as verified by the confirmation test. The effect of individual process variables on the responses is determined using analysis of variance.
Lightweight and high-wear performance materials are currently in demand for various advanced applications in areas such as aerospace and automobiles. These demands can be achieved by hybrid aluminum matrix composites (HAMCs), as they possess excellent mechanical and tribological properties which can be customized using more than one reinforcement. Boron carbide (8 wt.%) and fly-ash (2 wt.%) reinforced hybrid aluminum 7075 composite was successfully fabricated using a stir-casting route. Wear is a crucible phenomenon that occurs over the interaction of surfaces and affects the performance of the material. To investigate wear behavior of developed HAMC, dry sliding wear tests were conducted based on the central composite design, taking the specific wear rate as a response parameter. Modeling of wear parameters is crucial, as it helps to predict the value of the wear response at the given set of input parameters without performing experimentation. Response surface method (RSM) was used for the modeling of wear parameters to develop an empirical model of specific wear rate in terms of load, sliding speed, and sliding distance. The high value of the coefficient of determination (R 2 = 0.9894) illustrates the goodness of fit of the developed model. Moreover, the optimal condition of wear parameters was determined as 20 N load, 1.5 m/s sliding speed, and 500 m sliding distance; the predicted value of specific wear rate in this set of parameters is 0.2 × 10 −5 mm 3 /N-m. The validation test at optimal conditions was performed and the specific wear rate was found to be 0.205 × 10 −5 mm 3 /N-m, which shows good agreement with the predicted value. The worn-out surface and debris were analyzed using scanning electron microscope (SEM) images and electron dispersive spectrums (EDS) to completely explore the mechanism of wear.
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