Prediction of cutting forces during turning PA66 GF-30 glass fiber reinforced polyamide by soft computing techniques

Abstract

In the present paper the influence of the main cutting parameters on process performance during longitudinal turning of PA66 GF-30 Glass Fiber Reinforced Polyamide is investigated. The selected cutting parameters are cutting speed and feed-rate whilst depth of cut is kept constant. As outputs (responses), cutting force components Ft, FV and Fr were selected. Test specimens in the form of round bars and cemented carbide cutting tool were used during the experimental process. Fifteen experiments were conducted having all different combinations of cutting parameter values. Analysis of Variance (ANOVA), statistical approaches and soft computing techniques (artificial neural network) were applied in order to formulate stochastic models for relating the responses with main cutting parameters. The results obtained, indicate that the proposed soft computing techniques can be effectively used to predict the cutting force components (Ft, FV and Fr) thus; facilitating decision making during process planning since costly and time-consuming experimentation can be avoided. © (2013) Trans Tech Publications, Switzerland.