This article investigates the optimization of dry sliding performances on the aluminum hybrid metal matrix composites using gray relational analysis in the Taguchi method. Different loads, sliding speeds and varying percentage of molybdenum disulfide are selected as control factors. The multiple responses to evaluate the dry sliding performances are specific wear rate and coefficient of friction. Using a pin-on-disk apparatus, the volume loss and frictional force are measured. Based on gray relational analysis, the optimum level parameters for specific wear rate and coefficient of friction have been identified. An L27 orthogonal array was employed for the experimental design. Analysis of Variance (ANOVA) had given the impact of individual factors and interactions on the specific wear rate as well as the coefficient of friction. The results indicated that the three test parameters had a significant role in controlling the friction and wear behavior of composites. Interaction of the control factors showed the sizable influence on tribological performance. Using Scanning Electron Microscopy (SEM) the wear surface morphology and wear mechanism of the composites have been investigated.

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Metal-matrix composites (MMCs) are attracting considerable interest worldwide because of their superior mechanical and tribological properties. This study describes multifactor-based experiments that were applied to research and investigation on dry sliding wear system of stir cast Al-Si10Mg matrix alloy with 5 and 10 wt% alumina-reinforced MMCs. The effects of parameters like load, sliding speed, percentage of alumina on the dry sliding wear, and friction coefficient of aluminum MMCs using Taguchi’s method are reported. An orthogonal array (L27) and analysis of variance were used to investigate the influence of parameters like normal load, sliding speed, and reinforcement percentage and their interactions on dry sliding wear and friction coefficient of the composites. The major objective was to investigate the parameter that significantly affects the dry sliding wear and friction coefficient. The results show that friction coefficient and wear rate were highly influenced by load, sliding speed, and percentage of alumina whereas the interactions between these parameters, show only a minor influence in MMCs. The worn surfaces of the pins were then analyzed by scanning electron microscopy to study the wear mechanism and to correlate them with wear test results.

Purpose -The purpose of this research paper is to find the optimum parameters, namely, the sliding speed, applied load and percentage of silicon carbide particles (SiCp), under which AlSi10Mg/SiCp composites experience minimum wear. Design/methodology/approach -Wear rate (WR) of AlSi10Mg, AlSi10Mg/10SiC and AlSi10Mg/20SiC was measured using pin-on-disk equipment according to ASTM G99 standards. Response surface method was used to design the experiments, model and analyze the tribological behaviour. Tests were conducted as per Box-Beheken design of experiments. The wear mechanisms were observed using scanning electron microscope. Genetic algorithm was used to find the optimum parameters for minimum WR. Findings -Wear mechanisms underwent changes with variation in applied load, sliding speed and per cent SiCp. An optimum wear condition was obtained when the process parameters, namely, the sliding speed, applied load and percentage of SiCp, were at 4 m/s, 10 N and 20 per cent, respectively. Combined GA-RSM approach was successfully used to predict the minimum WR condition of AlSi10Mg/SiCp composites with an accuracy of 94 per cent. Originality/value -The tribological behaviour of AlSi10Mg/SiCp composites has been investigated in detail. A statistical WR model is proposed. This paper provides an optimum condition to design the tribo contact between steel and AlSi10Mg/SiCp composites.

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