A Novel Fluid–Structure Interaction (FSI) Modeling Approach to Predict the Temperature Distribution in Single-Point Cutting Tool for Condition Monitoring During Turning Process

In the present work, a robust fluid–structure interaction (FSI) modeling approach for the prediction of cutting tool insert temperature in CNC turning is introduced. A single-wired thermocouple is utilized to gauge the tooltip temperature in the turning operation. Both the hypothetical and experimental results are obtained with various parametric inputs. The ANSYS R19.2 software is used to recreate the simulation environment. The simulation is performed in the ambient temperature underlying the tool insert temperature generated internally. To verify the built-up temperature model, a physical turning test is conveyed out. With diverse cutting boundaries, both the simulated models utilizing the proposed diagnostic analytical model and turning experiments are conveyed, and the two outcomes showed comparable results. The FSI is studied under various environments by changing the discrete phase and injection velocity for condition monitoring. The monitoring system designed is experimentally verified with the simulation results performed in the ANSYS R19.2 software. The approach showed empowering results by diminishing errors to a relative error of 2.15  ±  0.5% between the estimations of test results. The developed condition monitoring system is then integrated with the artificial intelligence system for real-time prediction of tool wear status with an overall accuracy of 86.23%.