This project describes research that will lead to the commercialization of the Tool Dashboard, a new technique for pre-process milling parameter selection. In this approach, dynamic models of the cutting tool and holder will be analytically coupled to spindle-machine measurements to predict the tool point dynamics. Given this information, stability lobe diagrams, which display stable and unstable cutting zones as a function of the axial depth of cut and spindle speed, will be constructed. This information will then be used to develop the user-friendly Tool Dashboard interface for parameter selection. By removing the current necessity for a separate measurement of each tool-holder-spindle-machine assembly, the requirements for significant measurement time, specialized measurement equipment, and trained personnel will be eliminated. This method leads to a commercially-viable approach where the spindle-machine dynamics are identified once, archived, and then used to predict the tool point dynamics for any tool-holder combination (analogous to the Human Genome Project that mapped the genes responsible for characteristics of the body). By this approach, users without measurement capabilities or knowledge of structural dynamics/chatter theory can take advantage of the substantial productivity increases and "first part correct" fabrication made possible through pre-process consideration of the milling process dynamics.
Keywords: Milling, Dynamics, Chatter, Stability, Prediction, Receptance, Frequency Response
