This paper investigates cutting force in thermal-assisted machining (TAM) by induction heating for SKD11 tool steel which is widely used in the mold industry. Experimental studies were first conducted at room and elevated temperatures to evaluate the effectiveness of the heating process on chip morphology and the cutting forces during the thermal-assisted machining and comparing with conventional machining method. The Taguchi method based on orthogonal array and analysis of variance ANOVA method was then used to design the number of experiments and evaluate the influence of cutting speed, feed rate, cutting depth, and elevated temperature on the cutting force. Study results showed a decrease in the cutting force in the TAM process. The optimal condition of parameters obtained for thermal-assisted machining were cutting speed 280 m/min, feed rate 230 mm/min, cutting depth 0.5 mm and temperature 400 °C. Finally, a proposed equation was established to determine the cutting force that was presented as a function of elevated temperatures when milling SKD11 material. A proposed cutting force model was compared, evaluated and confirmed to be in good agreement with experimental results.
This study proposed an innovative method for improving the prediction of the cutting force (F) and chip shrinkage coefficient (K) for milling of SKD11 alloy steels using simulations and experimental results. Preliminary experimental measurements of the F and K were made for variable cutting speeds and depths, and simulations were then conducted using the Johnson–Cook model. However, significant discrepancies between the experiments and simulations were observed for the F and K. Therefore, an improved method was proposed, utilizing the relationship between simulation/experimental cutting forces and the equivalent fracture strain of simulation elements in the shear zone in the space of the stress triaxiality and equivalent strain. The progression of fracture strain paths according to the stress triaxiality until the desired cutting forces were achieved was utilized for adding new data to the fracture strain locus in the space of the stress triaxiality and equivalent strain. The new fracture strain locus was adopted again, to simulate and predict the F and K at full 2 × 3 levels of cutting speeds and cutting depths, and the results were compared with those of the corresponding experiments. Based on the highest deviations between the simulation and experimental data for the cutting force (5.29%) and chip shrinkage coefficient (5.08%), this study confirmed that the proposed method for determining the new fracture strain locus can improve the prediction of the F and K for milling of SKD11 alloy steels.
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