The unique combinations of properties provided by aluminum and its alloys make aluminum one of the most versatile, economical, and attractive metallic materials for a broad range of uses from soft, highly ductile wrapping foil to the most demanding engineering applications. Aluminum alloys are second only to steels in use as structural metals. In last decade there has been a rapid increase in the utilization of aluminum generally designed for low weight and low costs, which yields the use of hydrodynamic journal bearing in a large number alloy in automobile industries due to high specific strength, high wear resistance, low density, and low coefficient of thermal expansion.

-High speed turning has emerged as a key manufacturing technology in machining of different metals and alloys. Turning at high speed is performed on the order of five to ten times the conventional cutting speed. It is advantageous in many ways like reduction in cutting forces and temperature, low power consumption, improvement in surface finish, high MRR, better dimensional accuracy and better part quality [1, 2]. In order to achieve the quality output, it is necessary to optimize the process parameters (like speed, feed, depth of cut, nose radius) during the high speed machining of alloy. To achieve this goal, the current research work is aimed at optimizing the input parameters of CNC turning. The study applies Taguchi's design of experiment methodology and grey relational analysis to optimize the process parameters in turning aluminum alloy AA7075-T6 material, a high strength aluminum alloy used for aerospace application using coated carbide insert under dry environment condition and having four type insert nose radius such as 0.2, 0.4, 0.8, 1.2 mm. Experiment have been carried out based on L16 standard orthogonal array design with four process parameters namely cutting speed, feed rate , Depth of cut and nose radius for surface roughness and Material removal rate[3, 4].The data was analyzed using Grey Relational Analysis (GRA) coupled with Principal Component Analysis (PCA). Analysis of S/N ratio was done to obtain the optimum combination of input parameters. The Grey Relational Grade (GRG) at optimum setting of the input parameters was obtained by Regression analysis. The experimental results were validated by comparing the experimental value of GRG with that of the predicted value and the comparison shows a good relationship between them.

Abstract-The purpose of this research paper is fabrication of polyetherimid (PEI) reinforced with glass fiber and graphite powder and to study two types of wear (i.e adhesive and abrasive wear) of PEI composites with different percentages of graphite powder. Polyetherimide(PEI) composites with fiber contents 55 wt.% are fabricated using compression molding technique. (ULTEM 1000) in granules form is one of the newest highperformance thermoplastics. Wear behavior of glass fibre reinforced PEI composites with different percentage of graphite powder is observed on pin on disc apparatus at different loads.

The tensile strength of Friction Stir Welded (FSW) joints was significantly affected by welding speed and shoulder diameter whereas welding speed strongly affected percentage elongation. If special focus on friction stir welding (FSW) modelling on the heat generation due to the contact conditions between the FSW tool and the work piece is consideredthenthermo-mechanical conditions during FSW are very different from that registered during welding of metals which leads to completely different material flow mechanisms and weld defect analysis.

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