Machine Tool Genome Project

The objective of this research is to enable pre-process milling parameter selection for"first part correct"production. In the proposed solution the Receptance Coupling Substructure Analysis (RCSA) approach will be used to couple the measured spindle-machine dynamics to models of the tool and holder and predict the assembly"s dynamic response. Given this information, frequency/time-domain algorithms are applied to select feasible spindle speed-depth of cut pairs that enable first part correct production. The development of an automated artifact will be coupled with this technology to speed measurement and data transmission of spindle-machine receptances for evaluation of machine productivity and repeatability. Given the tool point response, the process stability and surface location error (part errors caused by forced vibrations) will be determined to separate feasible and infeasible zones within the spindle speed-axial depth of cut domain. Once acceptable combinations are determined, they will be presented in a new user-friendly format, the Tool Dashboard, similar to an automotive dashboard display. Tool Dashboards will be customized for various applications to analyze the effect of different process parameter combinations on vibration behavior (chatter sensitivity and surface location error) and energy consumption.