In-cut machining cycle times of 50-100 h are common. Achieving meaningful reduction of cycle time while maintaining part quality is predicated upon the ability to model the physics of the machining operations.
Five-axis tool paths can result in thousands of cutter orientations with respect to the workpiece and are often used in the machining of complex monolithic aerospace components. It is a complex and expensive undertaking. Among factors making computational procedures expensive are: defining accurate cutter geometries, including the rake angles, corner radii, and helix angles; calculating surface-surface intersections between workpiece and tool geometries as a function of feeds and speeds; and defining workpiece geometries (of the order of several meters) while resolving chip loads (of the order of a few micrometers).
In addition to complicated tool paths, the machining of titanium alloys and other high-temperature aerospace metals poses additional challenges due to low thermal conductivity, high specific cutting power, and high hardness.
Commercially available verification software products provide methods to optimize the tool paths but do not incorporate material behavior or cutting force prediction. Several empirical models to predict cutting forces in machining processes have been well documented in literature. But these models are not sufficient to simulate the machining of complex aerospace components utilizing five-axis tool paths and predict forces for thousands of cutter locations and dozens of tools in a quick and efficient manner.
However complicated, implementing tool-path analysis into process design can yield a wide range of benefits in many different areas, as researchers from Third Wave have found. With the help of a validated five-axis tool path analysis model that can predict forces at each cutter location, cycle times and scrap can be reduced, and machine breakdown can be avoided, all through off-line analysis. Productivity and process efficiency can be improved through simulation, drastically reducing testing setup and cut time.
Third Wave’s research provides a way to accurately model length scales from chip load (~100 micron), part thickness (~2 mm), and depths of cut (~10 mm) to part dimensions (~10 m). Forces and temperatures are predicted over the entire tool path using analytical and numerical techniques to extend an empirical database to generalized cutting conditions. This semi-empirical model is able to predict torque and cutting forces encountered by the tool for drilling and milling operations. Using the same model, it is also possible to achieve a tangible reduction of cycle time while maintaining part quality.
This article is based on SAE technical paper 2009-01-3131 by S. Garud, T. Marusich, S. Usui, L. Zamorano, and K. Marusich of Third Wave Systems, Inc.