In this study, a bottom pouring-type stir casting machine was used to create AZ31 magnesium alloy hybrid nanocomposites with varying weight percentages (0, 3, 5, and 7) of silicon carbide (SiC) and graphite (Gr) particles. Investigations have been made into the mechanical characteristics and microstructural distribution of manufactured hybrid nanocomposites. The outcomes demonstrate that the mechanical characteristics and uniform distribution of SiC and Gr particles are enhanced compared to those of the base alloy. In comparison to monolithic AZ31 alloy, microhardness, ultimate tensile strength (UTS), yield strength (YS), and compressive strength (CS) were raised by about 54%, 68%, 82%, and 107%, respectively. The presence of reinforced particles, the uniform distribution of particles, and the strong interfacial connection between the matrix and reinforcement all contribute to the improvement of mechanical properties. However, the addition of 7 wt. % SiC/Gr showed good mechanical properties compared to the base alloy. The microstructure of nanocomposites was analyzed using a scanning electron microscope (SEM), and particles were described using energy-dispersive spectroscopy (EDS).

In this work, the authors investigate the optimal tribological parameters of Al 7075 composite reinforced with ZrB 2 using Grey Relational Analysis (GRA). Initially, the composite specimens were prepared by the variation of reinforcement 5%, 10% and 15% using stir casting routing method. Further, the developed metal matrix composites are used to measure the wear and frictional properties on pin-on -disc testing apparatus. The input parameters such as, wt% of reinforcement (5%, 10% and 15%), load (4.92N, 9.81N and 14.72N) and the time required for conducting the wear test is (15 min. 30 min and 45 min). A Taguchi L 9 orthogonal array was designed for conducting the number of experiments. Based on the combination of number of experiments wear study has been conducted on the wear testing apparatus. Moreover, GRA was used for obtaining the best optimal input control parameters that gives minimum magnitude of wear and coeffi cient of friction (COF). Finally, the confi rmatory experiments are conducted and verifi ed with the Taguchi grey relational analysis. The results shows that the predicated optimal mean value is almost similar to the experimental value.

A novel approach of Micro-electrochemical Texturing (MET) is a realistic substitute for generating surface textures of machined surface. Several conventional and non-conventional techniques i.e., embossing, sand blasting, pinning, LBM, EDM etc. are available for generating microsurface textures, but creates several problems to generate microtextured surfaces which reduce the quality and lower the productivity. To overcome these limitations, this research proposes a unique microsurface texturing method namely, micro-electrochemical texturing, based on electrochemical reaction. Due to the high flexibility of the micro-electrochemical texturing system, micro-texturing features, surface roughness and its performance can be easily changed by varying the micro-electrochemical parameters. In this research paper, this process is developed to fabricate the microsurface textures on stainless steel specimens economically with less time. The experimental results of surface characteristics generated on workpiece utilizing the developed setup with vertical cross flow electrolyte circulation system in micro-electrochemical texturing method are presented. The effects of duty ratio and voltage on performance criteria i.e., material removal rate (MRR), taper kerf angle and surface roughness are investigated. The obtained overall surface roughness value on the stainless-steel samples machined by micro-electrochemical texturing technique is 0.08μm.

Magnesium-based alloys were more prevalent in automobile applications owing to their mechanical properties, low mass, and density. However, its poor mechanical properties are restricting its applications. Therefore, the present study focuses on improving the mechanical properties of AZ31D alloy by reinforcing silicon carbide (SiC) and graphite (Gr) nanoparticles with weight fractions of 2%, 4%, and 6% using stir-casting technique. The microstructure analysis was performed using a scanning electron microscope. The elemental analysis was confirmed using energy-dispersive spectroscopy, and X-ray diffraction was used to study various phases in the nanocomposites. Further, the mechanical properties, such as microhardness, ultimate tensile strength, yield strength, and compression strength of the nanocomposites, were significantly improved by 53%, 59%, 62%, and 82%, respectively, as compared with base alloy.

This research concentrated on material characteristics such as tensile property (TS) and hardness (HV) for AA-5083 manufactured using the stir casting (SC) process. The reinforcing elements silicon carbide (SiC-7.5%) and flyash (FA-5%) in the form of powders will be added to Al alloy to improve the characteristics of composites. Response surface methodology (RSM) was a scientific technique to make optimizing task at stir casting parameters. As per central composite design (CCD), 20 samples (L1-L20) were fabricated at a variation of factors such as stirrer speed (A) 350-550 rpm, stir time (B) 15-35 min, and stir temperature (C) 750-950°C. The result presented that best TS and HV exhibited at experiments L5 (A2-450 rpm, B1-15min, and C1-750°C) and L6 (A1-350 rpm, B1-15min, and C1-750°C). Design expert software (DES) is one of the optimization tools that employed to determine analysis of variance (ANOVA) and the best optimal parameter levels of SC. ANOVA helped to check contribution of SC factors on TS and HV, and it was noticed that mechanical properties were improved with increasing stir speed and stir time but it was reduced with rising of temperature.