Progress on Predictive Performance of Metal Cutting by Machining Processes – Study Case: Turning Operations through Controlled-Contact

Abstract

Studies on the development of models for the predictive performance of metal cutting by machining processes, initiated by CIRP, are currently ongoing at several research centers worldwide. This paper describes the successful outcomes achieved from primary research on the development of the ORTHO-OB CHATTER computer program, which enables data-driven predictive performance analysis of metal cutting by turning operations. Since data are critical to proper description of models, the work involved, gathering, generating and developing necessary support structured data that can be computationally applied through situated single- and multiple- input search queries, to predict generated forces, stresses, temperatures, strain rates, tool wear, possibility of fracture and tool life, stability and economic costs in lathe metal cutting involving any selected workpiece and tool materials combinations as a recommendation system to aid decision making. The paper also discusses predicting metal cutting operations under uncertainty by analyzing and identifying patterns and trends in data through mechanistic reasoning, providing a quick aid to help machinists select the correct size tools, cutting conditions, and make energy-saving decisions for a machining task. Validation shows errors in cutting force predictions by mechanistic reasoning of most material classes tested are within the range of zero to five percent.