Optimization of 5-axis milling processes using process models

Productivity and part quality are extremely important for all machining operations, but particularly for 5-axis milling where the machine tool cost is relatively higher, and most parts have complex geometries and high quality requirements with tight tolerances. 5- axis milling, presents additional challenges in modeling due to more complex tool and workpiece interface geometry, and process mechanics. In this paper, modeling and optimization of 5-axis processes with cutting strategy selection are presented. The developed process models are used for cutting force predictions using a part-tool interface identification method which is also presented. Based on the model predictions and simulations, best cutting conditions are identified. Also, for finish process of a complex surface, machining time is estimated using three machining strategy alternatives. Results are demonstrated by example applications, and verified by experiments.