Surface roughness modeling in face milling of metal matrix composites by fuzzy subtractive clustering method

G. Balaganesan, L. Vijayaraghavan

Abstract

A fuzzy modeling approach is presented in this paper for the prediction of surface roughness (Ra) in face milling of Metal Matrix Composites (MMC). This study deals with the experimental results obtained during face milling of MMC Al/SiC, 15% volume fraction by using face milling cutter with K10 grade insert. The data used for the training and checking of the model performance were obtained from experiments conducted on a vertical milling machine. The model uses the cutting speed, depth of cut and the feed as input data and the surface roughness as the output data. The process of model building is carried out by using subtractive clustering in both the input and output spaces. A minimum error model is obtained through exhaustive search of the clustering parameters. The fuzzy model obtained is capable of predicting the surface quality for a given set of inputs (the cutting speed, depth of cut and the cutting feed). This model is verified experimentally using different sets of inputs.

Keywords

Surface roughness; face milling; metal matrix composites; fuzzy subtractive clustering

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DOI

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IMEKO TC

TC14 - Measurement of Geometrical Quantities

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