New advances in the machining of hard metals using physics-based modeling

The machining of hard metals historically has been understood to be challenging and costly due to its material properties (such as titanium's low thermal conductivity and high hardness, and nickel's rapid work-hardening and high strength at elevated temperatures) and limited understanding in industry of the physics behind chip formation and material removal. The achievement of meaningful cycle time reductions while maintaining part quality depends on a capability to model the physics of hard metal machining operations. With the help of a validated toolpath 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 machining time. Physics-based modeling technology has been identified as a cost-effective solution for identifying optimum cutting speeds, enabling researchers and manufacturers to increase material removal rates, reduce machining costs, and enhance industry expertise in hard metal machining best practices. This paper presents new advances to physics-based modeling that have been validated using experimental tests and comparisons with finite element milling simulations, used to compare different process parameters and resulting material removal rates, and successfully advance hard metal machining processes.