Knowledge-based approach for improvement of CNC part programs

Abstract

In typical computer numerical control (CNC) machining processes, a CNC program specifies machining parameters and geometrical data. Part programmers usually write CNC programs based on their experience and perception. Because humans may not be able to sense physical quantities with high accuracy, modern CNC machines are equipped with a variety of sensors to indicate machining conditions. However, modern sensing systems and human expertise are separated in most existing systems. Run-time information does not contribute to CNC program quality. An attempt is made to illustrate the structure for coordinating sensing data and expert knowledge to tune the CNC program. The tuning process is done through both knowledge reasoning and mathematical processing. Simulation demonstrates convergent results of tuned feed rate under the tool deflection constraint.