Elastic and plastic fracture metals, polymers, ceramics, composites and biological materials: A. G. Atkins and Y.-W. Mai Ellis Horwood, 1985, 819 pp, £75.00

Abstract

The ability to predict the cutting forces for an arbitrary cutting tool is essential for selecting process parameters that would result in minimum machining damage. This activity is also important for improving existing cutting tool geometries and developing new ones. This work utilizes the mechanistic modeling approach in combination with neural networks data fitting for simulating the cutting forces in the milling of unidirectional carbon fiber-reinforced polymers (UD-CFRP). A method is proposed for predicting the cutting forces for tools of complex geometry by transforming the specific cutting energies from orthogonal cutting to the oblique cutting and accounting for the effects of rake angle and edge radius. It is shown that the method developed is capable of predicting the cutting forces in slot milling of unidirectional composites with a segmented flute cutter and over the entire range of fiber orientations from 0° to 180°. Model predictions were compared with experimental data and were found to be in good agreement. The effect of varying tool geometry on cutting forces was also investigated.