Extended octree for cutting force prediction

Prediction of cutting force plays an essentially important role in the selection of optimum cutting parameters and investigation of cutting mechanisms. In this work, an extended octree is presented to represent the workpiece and tool swept volume to acquire the cutting depth and cutting width with high precision so that the cutting forces can be predicted precisely. The algorithm of acquisition of cutting width and cutting depth in flat-end milling is described. A framework of cutting force prediction based on virtual machining was established and a demonstration system was developed consequently. The simulated values of cutting width and cutting depth show good consistency with the theoretically calculated data.