This research study is framed with an objective to fabricate AlMMC reinforced with varying percentage of SiC, B4C and Mg and evaluate their strength, quality and metallurgical integrity through destructive and non-destructive tests. The specimens indicate higher strength and bond integrity with increase in B4C percentage. The outcome reveals that this AlMMC is an effective alternative to other materials owing to its cost effectiveness and mechanical strength and stability.

Metal Matrix composites (MMCs) has many excellent engineering properties like good strength to weight ratio, stiffness and increased wear resistance etc., These properties are the main requirements in aerospace, automotive industries and hence the MMCs are extensively used in these industries. This paper presents the detailed experimental study on cutting forces and surface roughness aspects in turning of 5% Graphite reinforced AZ91D Magnesium alloy metal matrix composite (AZ91D Magnesium alloy matrix + 5 % Graphite reinforcement). The stir casting process under inert atmosphere is followed for synthesis of the composite. The turning process is followed using Tungsten carbide cutting tool, in a lathe. The effect of machining parameters viz., cutting speed, feed rate and depth of cut, on the cutting forces and surface roughness (Ra) achieved during the machining are analysed and modelled through the response surface methodology (RSM). Study of effect of machining parameters and their interactions are carried out by using the surface, contour plots of RSM. The experimental result shows that the most significant machining parameter affecting surface roughness and cutting forces is cutting speed. The experimental results and predicted values are observed as in good agreement.

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Metal Matrix composites (MMCs) has many excellent engineering properties like good strength to weight ratio, stiffness and increased wear resistance etc., These properties are the main requirements in aerospace, automotive industries and hence the MMCs are extensively used in these industries. This paper presents the detailed experimental study on cutting forces and surface roughness aspects in turning of 5% Graphite reinforced AZ91D Magnesium alloy metal matrix composite (AZ91D Magnesium alloy matrix + 5 % Graphite reinforcement). The stir casting process under inert atmosphere is followed for synthesis of the composite. The turning process is followed using Tungsten carbide cutting tool, in a lathe. The effect of machining parameters viz., cutting speed, feed rate and depth of cut, on the cutting forces and surface roughness (Ra) achieved during the machining are analysed and modelled through the response surface methodology (RSM). Study of effect of machining parameters and their interactions are carried out by using the surface, contour plots of RSM. The experimental result shows that the most significant machining parameter affecting surface roughness and cutting forces is cutting speed. The experimental results and predicted values are observed as in good agreement.

A fibre extracted from jute is a budding component identified for its potential application in composites. It is imperative to evaluate the parametric and property based features to determine its suitability. In this research study, considering the possible application of the fibre composites, the aptness of these fibres are examined with respect to their physical, mechanical [by layered manufacturing technique(LM)] and thermal properties. This study focuses on evaluating the properties and behaviour of raw Jute fibres and NaOH surface treated fibres. Subsequently, the fibres are subjected to thermo-gravimetry tests. The outcome of the thermal analysis clearly indicates that the temperature peak shifts to a higher region in the treated fibre compared to raw fibre. The overall observation strongly emphasize that the physical properties and the thermal behaviour of jute fibre are enhanced after surface treatments which makes it more feasible for its application in composite structures.

This research study focuses on the objective to establish an analytical model for determining the thermal distribution during friction stir welding (FSW), based on different assumptions of the contact condition between the rotating tool surface and the weld piece. The material flow and heat generation are characterized by the contact conditions at the interface, and are described as sliding, sticking or partial sliding/sticking. The analytical expression for the heat generation is a modification of previous analytical models known from the literature and accounts for both conical surfaces and different contact conditions. Aluminium metal matrix composites and steel 304 (dissimilar material joining) is being used for this study. Three dimensional Finite Element Models have been developed to visualize the temperature distribution across the butt ends of the plates. The results are validated with the experimental results reported in the literature. The result reveals that there exists a good coherence between experimental and simulated results.

Wire Electrical Discharge Machining (WEDM) is widely used for machining conductive materials which are of great importance in several industrial applications. In this work, process variables optimization of Powder Mixed Wire Electrical Discharge Machining (PMWEDM) of AISI 304 stainless steel (SS) is studied using molybdenum wire as the tool material. This work illustrate the implementation of Taguchi technique and Genetic Algorithm (GA) to identify the optimal process variables of WEDM using dielectric medium mixed with Silicon Carbide(SiC) powder. Selection of optimum process variables for obtaining higher cutting efficiency and accuracy is a difficult task in WEDM due to presence of large number of control variables and complicated stochastic process mechanisms. In general, there is no perfect combination that can simultaneously result in both the maximum material removal rate (MRR) and the minimal surface roughness (Rq). The present work attempts to develop an appropriate machining strategy for a maximum process yield. MRR and Rq have been considered as measure of the machining performance with four different control parameters such as pulse on time, pulse off time, current and voltage. Experiments were conducted by Taguchi L18 (21x33) mixed orthogonal array. A multiple linear regression model is developed to relate the input and output variables and GA is used to optimize WEDM process variables. The optimized results for maximum MRR and minimum Rq are compared with and without powder mixed dielectric and confirmation tests were conducted.