A novel approach for real-time prediction and prevention of tool chipping in intermittent turning machining

Abstract An integrated tool condition monitoring system, based on a novel signal processing approach, for online prediction and prevention of tool chipping in intermittent turning is presented. It identifies the unstable crack propagation features of the prefailure phase, independent of the cutting parameters and workpiece material. A correlation between the chipping size and these features was developed for decision making, to protect machined surfaces. Experimental validation results confirmed the accuracy of the proposed system. The time required for signal processing, decision making and communication with the machine controller allows stopping the operation before part damage. No such system is presently available.