Abstract
The work reviewed here an overview of the current investigates about the machining of Aluminum metal matrix composite (MMC) which is major concern now a day’s industry. There is an increase demand of the development of advanced metals for many industrial applications, to complete such demands metal matrix composites are the right solution. Metal Matrix Composites (MMCs) have higher strength to weight ratio and their properties may be tailored as per the industrial requirements. The main purpose of machining is to produce a product of desired shape and size with specific quality and surface finish by removing a material in the shape of chips and it is affected by cutting parameters like feed rate and depth of cut also the selection of cutting tool plays a major role. However, MMC’s are highly abrasive and tools can wear rapidly, machining of these materials attracted researchers and industrial community a lot. So various tooling systems like Carbides, either plain or coated for tool of milling, drilling, and non-traditional methods of machining are also use to achieve the high durability, dimensional tolerances, functional requirements and surface quality of such materials after machining of MMCs. After machining analysis of the experimental data collected from various combination of analysis, methods are to be uses as ANN artificial neural network, analysis of variance (ANOVA) and TELBO techniques and Multilayer perceptron model will be constructed. On completion of the test, the techniques are to be used in authenticate the result found and to expect the behavior of the system.
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