Trial-and-error prototyping is the current method used by industry to select process parameters. This method is expensive, and it often leads to sub-optimal parameter choices. For these reasons, and because of increasing international competition, U.S. industries are beginning to investigate more sophisticated approaches to the design and optimization of manufacturing processes. A necessary step towards improved process control is the development of better models of these operations. While considerable progress has been made in the development of predictive models for low-strain-rate processes, there is currently a need for improved predictive capabilities for high-rate processes.

In this talk, a survey will be given of some work in progress at NIST on the application of nonlinear dynamics to the modeling and simulation of two high-speed machining operations that are currently of considerable interest in industrial applications: high-speed turning and milling of metals. Unlike more conventional machining operations, which can be considered to be quasi-static, these more modern manufacturing processes are dynamic, and there are significant nonlinear effects which lead to complicated process dynamics.