Mathematical model to predict tool wear on the machining of glass fibre reinforced plastic composites

Glass fibre reinforced polymer (GFRP) composite materials are replacing traditional engineering materials owing to its properties. Accordingly, the need for accurate machining of composites has increased enormously. During machining, the reduction of tool wear is an important aspect. In the present work, a mathematical model has been developed to predict the tool wear on the machining of GFRP composites using regression analysis and analysis of variance (ANOVA) in order to study the main and interaction effects of machining parameters, viz., cutting speed, feed rate, depth of cut and work piece fibre orientation angle. The adequacy of the developed model is verified by using coefficient of determination and residual analysis. This model can be effectively used to predict the tool wear on machining GFRP components within the ranges of variables studied. The influences of different parameters in machining GFRP composite have been analysed in detail.