Development of intelligent system to minimize burr formation in face milling

Abstract

The exit burr generated in the face milling operation at the edge of the workpiece usually requires deburring processes to enhance the level of precision of the parts. This paper is to geometrically understand the formation of the exit burr in the face milling operation on the arbitrary shaped workpiece with multiple feature such as hole, spline, and arc so that we can suggest the cutting conditions and tool path to minimize the burr formation on the given workpiece in the early design stage. The burr formation mechanism in each type of burr is classified based on the experimental results. A database is developed to store and predict burr formation results. A Windows based program is developed with the algorithm including three steps, i.e., the feature identification, the cutting condition identification, and the analysis on exit burr formation. We can predict which portion of the workpiece would have the exit burr in advance so that we can manage to find a way to minimize the exit burr formation in an actual cutting. Here, the idea of critical burr length is introduced as a criterion in optimization.