Combining process dynamics and tool wear in the milling super diagram

This paper describes the milling "super diagram" that incorporates limitations to milling productivity and part quality imposed by stability, surface location error (part errors due to forced vibrations), and tool wear. Combinations of axial depth of cut and spindle speed that offer stable cutting conditions with an acceptable, user-defined surface location error level are identified by a gray-scale color coding scheme. The effect of tool wear is included through the force model coefficients (that relate the cutting force to the chip area) used for process dynamics prediction. Because the force model coefficients vary as a function of the volume of material removed, a unique super diagram is constructed for any user-defined volume of material removed with the selected cutter. For example, preferred operating conditions for a new tool can be compared to those for a worn tool. Additionally, user beliefs about data and model accuracy are applied to identify safety margins relative to the deterministic boundaries in the diagrams. Experimental results are provided for an inserted (carbide) cutter used to machine 1018 steel. The wear behavior is characterized as changes in the force model coefficients as a function of the volume of material removed. The flank wear is also measured using an on-machine microscope (to avoid tool removal from the spindle) and correlated to the force model coefficients. Stability diagrams are developed that correspond to the new and worn tool performance and experimental results are provided to verify changes in the process stability due to tool wear.