Development and implementation of a novel split-wise model to predict the cutting forces in milling of Al2024 for minimum error

Accurate prediction of cutting force is essential not only for estimating power and torque but also for precise chatter prediction, where even the derivative of the cutting force function is crucial. The traditional cutting force model does not consider the runout, and the enhanced models that consider it are often difficult to be established due to the need of physical runout measurements. This study proposes a newly developed split-wise model to predict the cutting forces in Al2024. This model includes the calculation of the cutting force considering individual teeth which leads to the determination of 6 force coefficients of different values per tooth. The experiments were conducted on milling Al2024 for two set of experiments ( \(V_{fz}\) $V_{\mathit{fz}}$ = 375–675 m/min, \(a_e\) $a_e$ = 4–12 mm, \(a_p\) $a_p$ = 0.5–1 mm, D =16 mm) and ( \(V_{fz}\) $V_{\mathit{fz}}$ = 220–440 m/min, \(a_e\) $a_e$ = 0.5–1 mm, \(a_p\) $a_p$ = 0.5–1 mm, D =2 mm). For the first set, the comparative error determined from the split-wise and classic models is 5.6% and 7.8%, respectively. For the second set, the error is 11% and 15.7%, respectively. Therefore, the split-wise cutting force model is capable of adapting the runout and consequently improving the prediction of the cutting force with both large and small tools operations. Additionally, the split-wise may find applications in advanced manufacturing technologies allowing industries to enhanced productivity and quality.