## 1 Introduction  
The development of technology has led to the demand for micro-products in the automotive, aerospace, electronics, medical implants, biomedicine, and robotics industries, among others. Micro-cutting is the key technology to suffice an industry in terms of functionality and size miniaturization [1]. [PERSON] et al. [2] indicated that the cutting depth is generally less than 200 \(\upmu\)m, the processing size of micro turning is less than 100 \(\upmu\)m, and the slots of the micro-milling processing width are within 50 \(\upmu\)m. Given the exceptional material properties of titanium alloys, Ti6 Al4V has been analyzed and applied to micro-cutting in several studies [3, 4]. Owing to the low thermal conductivity of Ti6 Al4V and relatively slow heat dissipation, it is relatively easy to form adiabatic shear bands and serrated chips in traditional micro-cutting machining [5, 6]. Periodically fluctuating cutting forces are generated during the formation of serrated chips, which accelerates tool wear and affects the surface quality of machined parts [7, 8]. However, the experimental studies regarding Ti6 Al4V processing technology continue to encounter several challenges, including cost and time constraints [9]. Therefore, the finite element numerical analysis method constitutes an imperative method to overcome experimental limitations and better explain the experimental mechanism [10, 11]. An accurate cutting simulation model directly determines the accuracy of the formation mechanism of the serrated chips. In any finite element model (F.E.M. ), an essential input defines the material properties; it is usually modeled by constitutive equations expressing the stress-strain response along with its dependence on strain rate, temperature, and work hardening [12]. Therefore, an accurate material constitutive corresponds to the key issue for developing an accurate cutting simulation model [13, 14, 15]. Currently, in the metal cutting simulation process, the Johnson-Cook (J-C) constitutive model is the most frequently used model in the finite element modeling of metal cutting [16; 17], and the J-C constitutive equation is commonly expressed as Equation (1). The J-C constitutive model considers the strain hardening effect, strain rate strengthening effect, and thermal softening effect. Simultaneously, the model reflects mechanical changes in metals under high strains, high strain rates, and high temperatures, which are suitable for different materials. The model can separate plastic, viscous, and thermal aspects [18]. Several previous studies utilized the J-C constitutive model to predict and explain the experimental mechanism, including the mechanochemical effect [19], stress distribution [20], distribution of displacement [21], cutting force, and serrated chip morphology [22]. \[\sigma=\left(A+B\epsilon_{p}^{n}\right)\left(1+Cln\frac{\dot{\epsilon}}{ \dot{\epsilon}_{p}}\right)\left[1-\left(\frac{T-T_{r}}{T_{m}-T_{r}}\right)^{m }\right] \tag{1}\]  
where \(\sigma\), \(\epsilon\), \(\dot{\epsilon}\), and \(\dot{\epsilon}_{p}\) denote the equivalent flow stress, plastic strain, strain rate, and reference strain rate, respectively. Additionally, \(T\), \(T_{m}\), and \(T_{r}\) denote the current temperature, melting temperature of the working material, and room temperature, respectively. The J-C constitutive model is generally obtained by a split Hopkinson pressure bar (SHPB) test, and the experimental configuration allows a strain rate of 0.5-10\({}^{4}\)[23; 24], or the J-C constitutive constant is fitted via numerical methods [25]. [PERSON] et al. [26] obtained the effects of a high strain rate and elevated temperatures on the deformation behavior of laser assisted manufacturing FeCr alloy using the SHPB tests (Split Hopkinson Pressure Bar). Based on the experimental results, the J-C model and modified Johnson-Cook model were established. [PERSON] et al.