This study addresses the challenge of modeling flank wear impact on cutting forces in metal cutting. Accurate models are crucial for simulating the cutting process, optimizing insert geometry and monitoring machine tools. The objective is to develop an extended Kienzle-Sağlam force model that considers tool rake angle, uncut chip thickness and tool flank wear. Experimental tests involve orthogonal turning with coated inserts, cutting force measurements with a dynamometer and flank wear progression monitored using an optical measuring robot. By integrating measured cutting forces and flank wear progression, the study extends the mechanistic cutting force model, with flank wear as an input parameter. The proposed model is validated against force measurements, using commercial cutting tools in longitudinal turning conditions. The findings of this study suggest that the developed cutting force model effectively captures the effects of the considered input parameters and accounts for different stages of tool wear. The results also show that the tool flank wear significantly affects the radial and feed force components, which is an important finding potentially affecting the prediction capabilities in future generations of sensor-embedded cutting tools, aiming at tool life monitoring, prediction of tool deflection and cutting process stability.

Sensor-equipped metal cutting tools are one of the branches of Industry 4.0. A particularly interesting application for the sensors is to estimate the cutting forces for ensuring efficient machining and process monitoring. However, due to the extreme pressure and temperature in the cutting zone during machining, sensors such as strain sensors and accelerometers need to be placed away from the cutting zone. The signals measured by the sensors are filtered by the mechanical properties of the cutting tool, making accurate estimation of the cutting forces challenging. This paper presents a method to calculate the residues and poles describing strain-force transfer functions of a cantilever beam with multiple modes, representing a simplified model of a cutting tool. The model is then used in conjunction with inverse filtering to estimate the input force from recorded strain, incorporating the static and dynamic properties of the system. The suggested approach is demonstrated both in simulations and experimental tests with promising results. © 2024 Proceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics. All rights reserved.