| Abstract
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2819 |
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The Milling Dynamics “Super Diagram”: Combining Stability, Surface Location Error, Tool Wear, and Uncertainty |
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Applications of Precision Engineering in Manufacturing |
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| Content |
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Results were presented at the 2008 annual meeting that described a new diagram for parameter selection in milling. It separated stable and unstable (chatter) cutting zones and identified regions of large surface location error (due to forced vibrations) within the spindle speed-axial depth of cut domain using a gray scale approach. In the final diagram, only stable cutting conditions that yielded parts with acceptable (user-specified) accuracy were shown as white. All other zones were penalized and shaded according to the selected gray scale. This data representation builds on the well known stability lobe diagram to add important information at the process planning stage.
In new work, tool wear is also included as a process limitation. Two approaches are taken to incorporate the effects of tool wear. In a first analysis, the familiar Taylor-type tool life model is implemented to identifying regions of the spindle speed-axial depth of cut domain as feasible or infeasible based on a comparison of the time to machine the selected part to the tool life. For spindle speed-axial depth of cut combinations where the machining time exceeds the tool life, the area is deemed infeasible and again penalized using the gray scale approach. Similar to the previous results, only white regions identify acceptable cutting zones.
In a second analysis, an alternative to the Taylor-type tool life approach is applied. Rather than relying on the size of tool wear features, such as flank or crater wear, to estimate the tool life, the cutting force is monitored as a function of machining time. In this way, time-dependent cutting force coefficients are determined experimentally. The end of tool life is selected as a percentage increase in force level (e.g., the tool is discarded when the force doubles). In this way, the stability limit and surface location error values can be determined using the worn tool cutting force model to indicate the process performance under actual conditions.
Finally, it is recognized that due to errors in input data and process models, the predicted process limitations (stability, surface location error, and tool life) may also have errors. Therefore, user-specified safety margins are implemented to revise the final feasible (white) zone in the super diagram. These safety margins capture the user’s beliefs regarding how close (in spindle speed and axial depth) he/she is willing to operate relative to the predicted limits. In a final analysis, cost minimization is completed to select the best operating conditions for a given tool-material combination including the safety margins.
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