This paper presents a five-axis milling force model that can incorporate a variety of cutters and workpiece materials. The mechanistic model uses a discretized cutting edge to calculate an area of intersection which is multiplied by the specific cutting pressure to produce a force output along the primary cartesian coordinate system. By using an analytic description of the cutting edge with a non-specific cutter and workpiece intersection routine, a model was created that can describe a variety of cutting situations. Furthermore, a back propagation neural network is used to calibrate the model, providing robustness and scalability to the calibration process. Testing was performed on 1020 steel using various cutting parameters with a high speed steel two flute cutter and a tungsten carbide insert cutter. Furthermore, both linear cuts and a test die surface yielded good agreement between predicted and measured results.

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