A cyber physical system for tool condition monitoring using electrical power and a mechanistic model

Abstract

Tool Condition Monitoring (TCM) systems, which aim to identify tool wear automatically to avoid damage to the machined part, are often not suitable for industrial applications due to: (i) sensing methods which can be expensive and invasive to install and (ii) testing regimes that only evaluate a narrow operating window under controlled conditions. To combat these issues, the research outlined in this paper explores the feasibility of TCM using electrical power consumption of an industrial Computer Numeric Control (CNC) cutting machine in combination with a mechanistic model for end milling operations. End milling of aluminium 6082 was performed over a range of cutting parameters (i.e. spindle speed, feed rate, tool diameter) and repeated with increasing levels of tool wear to ascertain the suitability of this approach. Reasonable correlation between the predicted and observed tool wear was found using the mechanistic model (R2 = 0.801), however variance between the cutting parameters highlights the limitations of the predictions. To combat this variance, an averaging window is taken over the course of a cutting program to reduce the overall error. A concept TCM system is then proposed, utilising cyber-physical models of the milling process to determine the width and depth of cuts for complex geometries which change in real time, with the challenges of implementing such a system discussed.