Predictive modeling of machining performance in turning operations

Recent definitions of machining performance have been based on technological machining performance measures such as cutting forces, tool-life/tool-wear, chip-form/chip breakability, surface roughness, etc. However, modeling work on these performance measures has so far been characterized by isolated treatment of each of these measures. The modeling approach followed by the machining research group at the University of Kentucky aims for an integrated predictive modeling methodology for the major technological machining performance measures. Extensive use of analytical, experimental, numerical, and AI-based approaches is made in the development of these predictive models. This paper presents the outline of this modeling effort and reports the progress made to date in implementing it.