Cutting Tool Remaining Useful Life During Turning of Metal Matrix Composites

In this paper, the conditional reliability function and the Remaining Useful Life (RUL) of a cutting tool are estimated as a function of the current condition's states. RUL is estimated based on the available information obtained from condition monitoring. The cutting forces' measurements define the states, and are considered as the monitoring signals that offer diagnosis of the tool wear state. The cutting tool is used under constant machining parameters, namely the cutting speed, the feed rate, and the depth of cut. Experimental data is collected during turning titanium metal matrix composites (TiMMCs) which are a new generation of materials and have proven to be viable in aerospace application. Two modeling tools are used to model the tool's reliability and hazard functions; The Proportional Hazards Model (PHM), which is a statistical tool that uses EXAKT software, and the Logical Analysis of Data (LAD), which is a machine learning tool that uses cbmLAD software. A comparison between the two approaches is given. The results are presented, and the practical use of these results is discussed. The Remaining Useful Life (RUL) of a cutting tool during turning TiMMCs, and its conditional reliability function are estimated as functions of the current condition's states.