Optimization Of Machining Particulate Metal Matrix Composites

Present generation of recreation, manufacturing and transport industries amongothers require improved performance to meet the expected targets. As technologicaladvancement expands at a geometrical progression there is need to produce productsthat match this shifting development. Such development cannot be met by monolithicalloys that have previously been used in the industry for some specialized applications.Metal matrix composites present attractive properties such as high specific strength,wear resistance and stiffness coupled with the ability to operate at elevatedtemperatures and compete with super-alloys, ceramics, and redesigned steel. However,their machining presents a significant challenge since a number of reinforcementmaterials are harder than commonly used high-speed steel and carbide tools. Thereinforcement causes rapid abrasive tool wear which impinges its wide applicationdue to poor machinability and consequent high machining costs.The main objective of this research is to find optimum cutting conditions formachining particulate MMCs. In this research both modeling and experimentaltechniques were used to arrive at the optimum conditions, which include cutting speed,feed rate, depth of cut, and tool material. The study also looked into surface finish,machining forces, dimensional accuracy, profile fractal dimension, and chip formation.This led to developing a model for the optimization of machining condition.Machining investigations were carried out using Al2124SiCp (45%wt) MMC wherethe reinforcement particles size ranged between5and8μm. The material used for thetest was in the form of a bar31.8mm in diameter and78.0mm in length. This materialwas selected due to its relatively low machinability anticipating larger differentiationsin quality characteristics.The machining of the MMC was performed at four different cutting speeds of40,60,80, and100m/min. The feed rates were0.025,0.05,0.1,0.15and0.2mm/revwhile depths of cut were0.1,0.2and0.3mm. The lathe used for the turning test wasHigh Precision Lathe Model No: CG6125C with a span radius of250mm and lengthof500mm. Modeling of optimization was carried out using Response surfacemethodology and Taguchi approach to predict a number of aspects in machinability ofAl2124SiCp (45%wt) MMC namely, profile fractal dimension, diameter error,circularity and surface roughness. Finite Element Modeling was also carried out usingThirdwave AdvantEdge simulation software to model chip formation and machiningforces of Al2124SiCp (45%wt) MMC as an Equivalent Homogeneous Material. Results reveal that Thirdwave AdvantEdge simulation on chip formation andmachining forces agreed strongly with experimental findings. The variation inmagnitude of the machining forces were attributed to machining conditions andenvironment that could not be controlled hence a higher value of experimental forcewas recorded as compared to simulated machining force. On response surfaceoptimization modeling the predicted and experimental values on profile fractaldimension, surface roughness, diameter error and circularity showed a high degree ofcorrelation. It was observed that it was not possible to optimize all the responsessimultaneously due to the complexity involved. To achieve high profile fractaldimension values the best combination was cutting speed80m/min and use of PCDtool at depth of cut0.1mm and feed rate0.1mm/rev. On tool wear PCD tool showedthe best results at all cutting parameters. In relation to surface roughness PCD toolsshowed profound performance where improvement was observed with increase inmachining speed. On dimensional accuracy it was observed that PCD tool performedbetter by giving low diameter and circularity values. On combined responseoptimization, the parameters selected were depth of cut0.1mm, feed rate0.1232mm/rev, cutting speed71.5152m/min and PCD cutting tool. Verificationresults showed good relationship between predicted and experimental results.For further research the researcher suggests analysis of profile fractal dimensionin relation to ultrasonic vibration assisted machining (UVAM) in machining MMCs.This would shed more light and the surface topography of surfaces produced throughUVAM. Assesment of dimensional accuracy components as cylindricity andcircularity of tappered work. Further modeling in optimization of cutting componentsfor MMCs having varying amount of reinforcement to achieve optimal machiningparameters.