Role of enhanced surface grain refinement and hardness improvement induced by the combined effect of friction stir processing and ultrasonic impact treatment on slurry abrasive wear performance of silicon carbide particle reinforced A356 composites

In this study, the slurry abrasive wear behavior of silicon carbide particle reinforced A356 composite alloy was investigated after the different surface mechanical attrition treatments. It is known that the aluminum matrix composites produced by the stir casting method have some deficiencies (e.g unfavorable microstructure formation, particle clustering, porosity formation, etc.). These kinds of drawbacks of the composites adversely affect the surface mechanical properties of materials such as wear resistance. For this purpose, the surface properties of the silicon carbide reinforced A356 matrix composites fabricated through the stir casting method were improved by using friction stir processing (FSP) and ultrasonic impact treatment (UIT) in the study. The results indicated that a remarkable increase was observed in the hardness and wear resistance of the cast composite via FSP and ultrasonic impact treatment following friction stir processing (FSP+UIT). The hardness of the stir zone after FSP and FSP+UIT was determined as 82.7+-2 HV and 101.9 +-3 HV0.2, respectively. The stir zone showed a similar tendency also in slurry abrasive wear resistance. FSP increased the wear resistance in the stir zone at the rate of 33.9% while it was determined as 35.5% for FSP+UIT. The microstructural modification of the cast composite that occurred after FSP was clearly demonstrated via optical microscope and scanning electron microscopy (SEM) examinations. Enhanced grain refinement after FSP+UIT was indicated especially by X-ray diffraction analysis (XRD). According to the findings, it was observed that the application of ultrasonic impact treatment following the friction stir processing can be used to obtain an enhanced microstructure and extra hardness increment in the surface of the SiC reinforced A356 alloy, thus resulting in slurry abrasive wear resistance increment.

An analytical model for force prediction in micromilling silicon carbide particle–reinforced aluminum matrix composites

In micromilling the silicon carbide particle–reinforced aluminum matrix composites, cutting forces can provide a better insight of the cutting mechanism. In this article, an analytical model for force prediction in micromilling composites is developed considering the size effect of the matrix. In modeling, for the matrix, the cutting area is divided into shearing area and plowing area and the removal forces are established considering chip formation and edge forces; for the particle, the removal forces are established based on Griffith fracture theory. The model is verified by micromilling experiments. The influences of the process parameters (milling width, milling depth, and feed per tooth) on the milling force were studied. It shows that the maximum milling force increased with the increase in the feed per tooth and the milling depth and increases first and then stabilizes with the increase in milling width; the average milling force increases with the increase in the three parameters. In addition, the contribution of the particle fracture force is analyzed, and it is found that the contribution of the particle fracture force is affected by the feed per tooth, which basically accounts for about 23% of the maximum milling force and accounts for 23%–30% of the average milling force.

Effect of Hybrid Ultrasonic and Mechanical Stirring on the Distribution of m-SiCp in A356 Alloy

The present study details the micro-scale silicon carbide particle (m-SiCp) homogeneous distribution in an A356 alloy through hybrid ultrasonic-stirring melt treatment under different operation conditions. Ultrasonically excited fluids were studied by particle image velocimetry to estimate the efficiency of the acoustic streaming in different distances to the sonotrode. Distinct particle approaches to introduce the melt and stirring techniques were performed to determine a successful route to promote a homogenous distribution of reinforcement particles. Results showed that the addition of m-SiCp in the semisolid state significantly improved particle wettability, preventing rapid sedimentation. The combination of ultrasonic induced streaming and mechanical stirring is an effective tool for the homogeneous distribution of m-SiCp along the casting specimen.

Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process

The advanced manufacturing and machining techniques are adopting a population-based metaheuristic algorithm for production, predicting and decision-making. Using the same approach, this paper deals with the application of bees algorithm and differential evolution to forecast the optimal parametric values aiming to obtain maximum material removal rate during electrochemical discharge machining of silicon carbide particle/glass fiber–reinforced polymer matrix composite. The bees algorithm follows swarm-based approach, while differential evolution works on a population-based approach. The experimental design was prepared on the basis of Taguchi’s methodology using an L16 orthogonal array. For the experimental analysis, the main variables in the process, that is, electrolyte concentration (g/L), inter-electrode gap (mm), duty factor and voltage (volts), were selected as main input parameters, and material removal rate (mg/min) was adjudged as output quality characteristic. A comparative investigation reveals that the maximum material removal rate was obtained by the parametric value proposed by differential evolution that follows the bees algorithm and Taguchi’s methodology. Furthermore, the results prove that the differential evolution algorithm has better collective assessment capability with a rapid converging rate.