In-process tool-failure detection by means of AR models

The present paper proposes a cutting tool breaking and chipping detection system for continuous and interrupted cutting, based on the analysis of the cutting force componentsFx andFy. A multifactorial experimental design has been carried out, to take account of the variability of the force signal. An adaptive signal processing algorithm is proposed, which detects catastrophic failure when at least one component deviates outside an estimated oscillation band for a time duration longer than a prefixed interval. The algorithm has been implemented on a four-microprocessor transputer board. Several tests confirmed the validity of the approach for detecting breaking and chipping phenomena in a few milliseconds, both in turning and in milling operations.