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The purpose of the present study is to analyze the wear behavior of developed aluminum hybrid composites under high-stress conditions through developed power law and quadratic equations.

The abrasive wear behavior of Al–Mg–Si (Al 6082) alloy reinforced with hard silicon carbide (SiC) and soft graphite (Gr) particulates fabricated by stir casting route was studied at loads of 5-15 N, sliding distance of 75 m and abrasive grit size of 100-200 μm. The power law and quadratic equations were developed to understand the wear behavior with respect to the load applied and the abrasive grit size. The worn surfaces of the test specimens and grit papers were examined under scanning electron microscope.

The density and hardness of the hybrid composites decreased when compared to Al–SiC composites, whereas the wear properties improved because of the presence of Gr. There was further improvement in the wear properties of the materials because of T6 heat treatment. The change in abrasive wear mechanism was observed at a grit size of 125 μm when traversed from alloy to hybrid composite as indicated in terms of exponents in the power law equation. The worn surfaces of hybrid composite pins were comparable with those of alloy pins.

In the automobile sector, components like cylinder liner, piston, crankshafts, brake drums, etc. also undergo abrasive wear along with sliding against the counter surface in working conditions.

The results prove that better wear resistance was obtained under the abrasion condition.

Aluminium is the most preferred material in engineering structural components because of its excellent properties. Furthermore, the properties of aluminium may be enhanced through metal matrix composites and an in-depth investigation on the evolved properties is needed in view of metallurgical, mechanical and tribological aspects. The purpose of this study is to explore the effect of TiC addition on the tribological behavior of aluminium composites.

Aluminium metal matrix composites at different weight percentage of titanium carbide were produced through powder metallurgy. Produced composites were subjected to sliding wear test under dry condition through Taguchi’s L9 orthogonal design.

Optimal process condition to achieve the minimum wear rate was identified though the main effect plot. Sliding velocity was identified as the most dominating factor in the wear resistance.

The production of components with improved properties is promoted efficiently and economically by synthesizing the composite via powder metallurgy.

Though the investigations on the wear behavior of aluminium composites are analyzed, reinforcement types and the mode of fabrication have their significance in the metallurgical and mechanical properties. Thus, the produced component needs an in-detail study on the property evolution.

Aluminium and its alloys are the most preferred material in aerospace and automotive industries because of their high strength-to-weight ratio. However, these alloys are found to be low wear resistance. Hence, the incorporation of ceramic particles with the aluminium alloy may be enhanced the mechanical and tribological properties. The purpose of this study is to optimize the specific wear rate and friction coefficient of titanium dioxide (TiO₂) reinforced AA7075 matrix composites. The four wear control factors are considered, i.e. reinforcement (Wt.%), applied load (N), sliding velocity (m/s) and sliding distance (m).

The composites were fabricated through stir casting route with varying weight percentages (0, 5, 10 and 15 Wt.%) of TiO₂ particulates. The mechanical properties of the composites were studied. The specific wear rate and friction coefficient of the newly prepared composites was determined by using a pin-on-disc apparatus under dry sliding conditions. Experiments were planned as per Taguchi’s L16 orthogonal design. Signal-to-noise ratio analysis was used to find the optimal combination of parameters.

The mechanical properties such as yield strength, tensile strength and hardness of the composites significantly improved with the addition of TiO₂ particles. The analysis of variance result shows that the applied load and reinforcement Wt.% are the most influencing parameters on specific wear rate and friction coefficient during dry sliding conditions. The scanning electron microscope morphology of the worn surface shows that TiO₂ particles protect the matrix from more removal of material at all conditions.

This paper provides a solution for optimal parameters on specific wear rate and friction coefficient of aluminium matrix composites (AMCs) using Taguchi methodology. The obtained results are useful in improving the wear resistance of the AA7075-TiO₂ composites.

The fiber orientation is considered one of the important parameters that have an effect on the characteristics of composites. This paper aims to investigate the effect of fiber orientation on the abrasive wear of the glass-epoxy (G-E) composites with different silicon carbide (SiC) filler weights (Wt.%).

The wear rate of glass fiber reinforced with angle-ply 0º, ±45º and 90º is discussed. The G-E composites with different weights of SiC filler at angle ±45º are considered. Hand lay-up technique was adopted for specimen preparation. The influence of effective parameters such as filler Wt. %, normal load, abrasive size and abrading distance on the wear rate was presented and discussed.

Experimental tests including pin on disk, micro-hardness and scanning electron microscope were carried out to investigate the composite characteristics.

The experimental results showed that the resistance wear was superior in case of ±45º fiber orientations. A validation of the experimental results using Taguchi approach to verify the optimal wear rate parameters was presented.

The purpose of the paper is to study the dry sliding wear behavior of as-cast and heat-treated zinc-aluminum (ZA-27) alloy, reinforced with silicon carbide and graphite particles.

The alloy and composite samples were prepared with stir casting technique. Heat treatment was carried out for samples at a temperature of 370°C followed by quenching in water at room temperature. Subsequently, the heat-treated samples were aged at 180°C and quenched in water at room temperature. The wear tests were carried using pin-on-disc apparatus at room temperature at different applied loads, sliding speed and sliding distance.

The wear volume loss of as-cast samples was more compared with heat treated samples. Composites exhibited improved wear resistance than base alloy.

Hybrid metal matrix composites with heat treatment has exhibited superior wear behavior in dry sliding conditions.

Since, wear is the one of the most commonly encountered industrial problems leading to frequent replacement of components there is a need to develop metal matrix composites (MMCs) for achieving better wear properties. The purpose of this paper is to fabricate aluminum MMCs to improve the dry sliding wear characteristics. An effective multi-response optimization approach called the principal component analysis (PCA) was used to identify the sets of optimal parameters in dry sliding wear process.

The present work investigates the dry sliding wear behavior of graphite reinforced aluminum composites produced by the molten metal mixing method by means of a pin-on-disc type wear set up. Dry sliding wear tests were carried on graphite reinforced MMCs and its matrix alloy sliding against a steel counter face. Different contact stress, reinforcement percentage, sliding distance and sliding velocity were selected as the control variables and the response selected was wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Optimization of dry sliding performance of the graphite reinforced MMCs was performed using PCA.

Based on the PCA, the optimum level parameters for overall principal component (PC) of WVL and COF have been identified. Moreover, analysis of variance was performed to know the impact of individual factors on overall PC of WVL and COF. The results indicated that the reinforcement percentage was found to be most effective factor among the other control parameters on dry sliding wear followed by sliding distance, sliding velocity and contact stress. Finally the wear surface morphology of the composites has been investigated using scanning electron microscopy.

Various manufacturing techniques are available for processing of MMCs. Each technique has its own advantages and disadvantages. In particular, some techniques are significantly expensive compared to others. Generally the manufacturer prefers the low cost technique. Therefore stir casting technique which was used in this paper for manufacturing of Aluminum MMCs is the best alternative for processing of MMCs in the present commercial sectors. Since the most important criteria of a dry sliding wear behavior is to provide lower WVL and COF, this study has intended to prove the application of PCA technique for solving multi objective optimization problem in wear applications like piston rings, piston rods, cylinder heads and brake rotors, etc.

Application of multi-response optimization technique for evaluation of tribological characteristics for Aluminum MMCs made up of graphite particulates is a first-of-its-kind approach in literature. Hence PCA method can be successfully used for multi-response optimization of dry sliding wear process.

The purpose of this paper is to develop hybrid aluminum metal matrix composite by stir casting process, reinforced with graphite and hard boron carbide particles to enhance the wear resistance. An attempt is made to optimize the wear (weight loss) and coefficient of friction (COF) by considering three factors, i.e. normal load, track diameter and sliding speed which were varied at three different levels.

The effect of graphite and boron carbide on microhardness was studied by adding them in varying percentages. After determining the best combination of hybrid reinforcements, optimization of wear (weight loss) and COF was carried out at various levels of considered factors. Taguchi design of experiments was used using the software “Minitab 16.1”. ANOVA was used to analyze the effect of various parameters on wear and COF. To validate the results, mathematical modeling was carried out in terms of regression equations and results obtained by regression equations.

The results revealed that the lower weight percentage of graphite (3 per cent) and boron carbide (1 per cent) significantly improved microhardness of developed composites. Results of ANOVA revealed that normal load was the main contributing factor for wear and COF. The results obtained by regression equations and confirmatory tests were within the results obtained by ANOVA.

To the best of the author’s knowledge, very less work has been reported on optimization of wear and COF using hybrid reinforcement particles of graphite and boron carbide.

In this study, artificial neural networks (ANNs) are constructed and validated by using the bearing data generated numerically from a thermohydrodynamic (THD) lubrication model. In many tribological simulations, a surrogate model (meta-model) for obtaining a fast solution with sufficient accuracy is highly desired.

The THD model is represented by two coupled partial differential equations, a simplified generalized Reynolds equation, considering the viscosity variation across the film thickness direction and a transient energy equation for the 3-D film temperature distribution. The ANNs tested are having a single- or dual-hidden-layer with two inputs and one output. The root-mean-square error and maximum/minimum absolute errors of validation points, when comparing with the THD solutions, were used to evaluate the prediction accuracy of the ANNs.

It is demonstrated that a properly constructed ANN surrogate model can predict the THD lubrication performance almost instantly with accuracy adequately retained.

This study extends the use of ANNs to the applications other than the analyses dealing with experimental data. A similar procedure can be used to build a surrogate model for computationally intensive tribological models to have fast results. One of such applications is conducting extensive optimum design of tribological components or systems.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2020-0109/

The present research work aims to study the friction coefficient in functionally graded rapid prototyping of Al–Al₂O₃ composite prepared via fused deposition modelling (FDM)-assisted investment casting (IC) process. The optimized settings of the process parameters (namely, filament proportion, volume of FDM pattern, density of FDM pattern, barrel finishing (BF) time, BF media weight and number of IC slurry layers) suggested in the present research work will help fabricate parts possessing higher frictional coefficient.

Initially, melt flow index (MFI) of two different proportions of Nylon6-Al–Al₂O₃ (to be used as an alternative FDM filament material) was tested on the melt flow indexer and matched with MFI of commercially used acrylonitrile–butadiene–styrene filament. After this, the selected proportions of Nylon6-Al–Al₂O₃ were prepared in the form of the FDM filament by using a single screw extruder. Further, this FDM filament has been used for developing sacrificial IC patterns in the existing FDM system which was barely finished to improve their surface finish. Castings developed were tested for their wear resistance properties on a pin-on-disc-type tribo-tester under dry conditions at sliding conditions to check their suitability as a frictional device for industrial applications. In the methodology part, Taguchi L18 orthogonal array was used to study the effect of selected process variables on the coefficient of friction (μ).

It has been found that filament proportion, volume of FDM pattern and density of FDM pattern have significantly affected the μ-values. Further, density of the FDM pattern was found to have 91.62 per cent contribution in obtaining μ-values. Scanning electron micrographs highlighted uniform distribution of Al₂O₃ particles in the Al-matrix at suggested optimized settings.

The present methodology shows the development of a functional graded material that consisted of surface reinforcement with Al₂O₃ particles, which could have applications for manufacturing friction surfaces such as clutch plates, brake drum, etc.

This paper describes the effect of process parameters on wear properties of the Al–Al₂O₃ composite developed as a functionally graded material by the FDM-based pattern in the IC process.