# Improved Cutting Force Modelling in Micro-Milling Aluminum Alloy LF 21 Considering Tool Wear
## 1 Introduction  
Aluminum alloy LF 21 has a strong ability to reflect electromagnetic waves. LF 21 waveguide slit array structure is widely used in waveguide radar antenna. The stiffness of the slit array structure is relatively weak. So, the structure is prone to deformation under the cutting force in conventional milling processes. Micro-milling technology can realize high-precision machining of mesoscale parts/structures, which is a potential effective machining technology for waveguide thin slot array structures. However, the small diameter and the low stiffness of the micro-milling cutter, the feed per tooth similarly sized the arc radius of the cutting edge, causes the micro-milling cutter to wear easily. The factors affecting the micro-milling force, such as tool wear, elastic recovery of material, the minimum cutting thickness and friction of metal cutting dead zone, etc., cannot be ignored. Yet, so far, few studies have reported to explore micro-milling aluminum alloy LF 21. Simulation is an effective method to study the tool wear in micro-milling. [PERSON] and [PERSON] conducted in-depth research on the tool wear of micro-milling titanium alloyTi6 Al-4V and simulated full-immersion and semi-immersion straight-inverse milling processes based on DEFORM 3D [1] and DEFORM 2D [2], respectively. They revealed that 3D simulation contributed to exploring the distribution of tool wear, tool wear led to the increase innegative rake angle and the tool wear in down-milling was slower than that in up-milling. [PERSON] et al. utilized DEFORM 3D to simulate micro-milling nickel-based superalloy Inconel 718 and realized the prediction of tool flank wear [3]. [PERSON] et al. [4] introduced the coefficient of the size effect into the Usui wear model, calibrated the coefficient through experiments, and then established a 2D simulation model of the micro-milling AISI4340 alloy steel process based on Abaqus/CAE, achieving the prediction of tool wear. [PERSON] and [PERSON] et al. [5] studied the influence of the coating on tool wear and built a simulation model of the micro-milling titanium alloy Ti-6 Al-4V process based on DEFORM 2D. So far, there are few studies on the investigation of tool wear in micro-milling aluminum alloy LF 21, and the existing micro-milling force models are all without considering the prediction results of tool wear based on simulation. Many experts and scholars have studied the force model. Tool wear, the effects of elastic recovery of material, the minimum cutting thickness and friction influence the micro-milling force. [PERSON] et al. [6] developed a micro-milling force model considering friction at the metal dead zone. [PERSON] et al. [7] deduced the size of the metal cutting dead zone, and length of the shear surface and realized the prediction of micro-milling force based on DEFORM 2D. [PERSON] et al. [8,9] suggested that vibration displacement and cutter runout should be considered in the micro-milling force model dominated by the shear and plough effect, respectively. The results showed that the prediction accuracy of the model is high. [PERSON] et al. [10] established a micro-milling force model considering multiple influencing factors, such as cutter runout, multi-tooth cutting, the arc radius of the cutting edge and the minimum cutting thickness. They also found that the prediction accuracy of the micro-milling force model considering cutter coating is higher than that without considering cutter coating [11]. [PERSON] et al. [12] proposed an analytical geometry method to analyze the relative position relationship between the blade and the workpiece so as to load the cutter runout into the force model and incorporated the force component caused by too much wear into the force coefficient increment, thus realizing the prediction of the micro-milling force. [PERSON] et al.