High accuracy and machining capability are the main requirements for metal cutting operations, and high cutting speed and feed rate increase the quality of machining parts, machining accuracy and metal removal per unit time. However, tool life and material removal rates are contradictory because of higher tool temperature, accelerated wear, shorter tool life, and lower machining efficiency with increasing tool replacement time and replacement rate.
Since both material removal rate and tool life are related to cutting conditions, it is necessary to choose appropriate cutting conditions.
Ham Kum Chol, a section head at the Faculty of Mechanical Science and Technology, developed an optimization model with maximum tool wear life at constant metal removal rate (efficiency) per unit time and proposed a method of optimizing the cutting conditions affecting tool life.
The tool wear model was constructed as a polynomial regression model from the simulation data using Deform3D finite element software, and the optimization solution was performed by MATLAB’s fmincon function.
The proposed method was applied to the cutting of high-temperature alloy Ti6A14V as a machining objective, which showed improved machining accuracy and machining time of center machine.
The proposed method can be applied to the selection of cutting conditions for maximizing tool life when machining various hard-working materials.
If more information is needed, please refer to his paper “Optimization of Cutting Parameters in Milling Based on Model of Tool Wear” in “Proceedings of KUTIC-2025”.
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