# Construction of a Cutting-Tool Wear Prediction Model through Ensemble Learning
## 1 Introduction
Therefore, to improve the machinability of SKD11, enhance machining efficiency, and reduce production costs, it is essential to identify optimal process parameters and cutting assistance that can help minimize costs and improve machining efficiency [3]. A literature review on ultrasonic-assisted milling examines the influence of ultrasonic assistance on cutting performance. [PERSON] et al. [4] proposed axial ultrasonic vibration on the rotating mill to conduct experiments on hardened AISI H11 tool steel, using a carbide flat end mill. The experiments involved slot milling under wet cutting conditions with variations in cutting speed, feed rate, and milling depth in both conventional milling and ultrasonic vibration-assisted milling. The study aimed to investigate the effect of ultrasonic-assisted machining on surface roughness, surface topography, and subsurface microhardness. The results indicated that the surface produced by axial ultrasonic-assisted milling was uniform, and the peak-to-peak value remained consistent, thereby enhancing surface finish. Additionally, the study verified the importance of axial ultrasonic vibration on rotary tooling for improving machining surface quality, as this vibration imparts a hammering action on the cutting-tool tip, making the cutting marks left by the teeth flat. Compared to conventional milling, ultrasonic-assisted milling resulted in a significant reduction of surface roughness, Ra, with up to 89.7% improvement. [PERSON] et al. [5] utilized cemented carbide flat end mills to conduct the ultrasonic-assisted end milling of AISI420 mold steel by varying the ultrasonic vibration frequencies and amplitudes, the rake angles and helix angles of the cutting-tool. The study aimed to improve machined surface roughness and cutting-tool wear via the assisted system. In addition, the effects of the input voltage, cutter stretch length, and holding force on the amplitude of the ultrasonic vibration system were also investigated. The results showed that the ultrasonic amplitude increased with increasing stretch length and input voltage. In addition, a proper holding force and an optimum amplitude, which are related to the best surface finish, were ascertained. The machined surfaces with ultrasonic-assisted milling exhibited better uniformity and smoothness as compared to those machined under the same conditions without assistance. In addition, the cutting-tool wear was slower during ultrasonic-assisted milling, which leads to an extension of tool life. Cutter geometry, such as positive rake angle with a larger helix angle of 45\({}^{\circ}\), and vibration parameters, such as a frequency of 50 kHz and an amplitude of 2.2 \(\upmu\)m, provided better surface smoothness and smaller cutting-tool wear during ultrasonic-assisted milling. [PERSON] et al. [6] investigated cutting machinability improvement in two-dimensional ultrasonic-assisted micro-end-milling on hardened tool steel. By varying the vibration parameters, such as amplitude and the frequency of ultrasonic assistance, experiments were conducted for both conventional and ultrasonic-assisted milling to examine their effects on surface roughness and cutting-tool wear under process parameter conditions. The results showed that cutting-tool wear in ultrasonic-assisted milling was reduced by approximately 5 to 20%. As the amplitude and frequency of the ultrasonic-assisted system increased, both cutting-tool wear and surface roughness decreased. Compared to conventional milling, this two-dimensional ultrasonic assistance effectively enhanced the overall machining performance. [PERSON] et al. [7] performed the dry milling of Ti-6 Al-4V with the assistance of longitudinal ultrasonic vibration to enhance machinability and surface quality. By varying the ultrasonic amplitude, an investigation was made with respect to cutting forces, cutting temperature, surface topography, and 3D surface roughness.