Adaptive support vector regression analysis of closed-loop inspection accuracy

Abstract

This study investigates how closed-loop measurement error in CNC milling relates to two different inspection techniques. The on-line inspection of machining accuracy using a spindle probe has an inherent shortcoming because the same machine that produced the parts is used for inspection. In order to use the spindle probe measurement as a means of correcting deviations in machining, the magnitude of measurement errors needs to be quantified. The empirical verification was made by conducting three sets of cutting experiments at the state-of-the-art Cincinnati Arrow Vertical Machining Center. Three different material types and parameter settings were selected to simulate a diverse cutting condition. During the cutting, the cutting force and spindle vibration sensor signals were collected and a tool wear was recorded using a computer vision system. The bore tolerance was gauged by a spindle probe as well as a coordinate measuring machine. The difference between the two measurements was defined as a closed-loop measurement error and adaptive support vector regression analysis was used to predict these bore difference at various values of the explanatory variables. The results show the potential of improving production efficiency and part quality.