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Titanium alloys are widely used in various fields, but milling titanium alloy materials often leads to problems such as high milling forces, increased milling temperatures, and chip adhesion. Thus, the machinability of titanium alloys faces challenges. To improve the milling performance of titanium alloy materials, this study analyzes the effective working area on the surface of the milling cutter through mathematical calculations. We design micro-grooves in this area to utilize their friction-reducing and wear-resisting properties to alleviate the aforementioned issues. The effective working area of the ball end milling cutter's cutting edge is calculated based on the amount of milling and the installation position between the milling cutter and the workpiece. By observing the surface structure of seashells, micro-grooves are proposed and designed to be applied in the working area of the milling cutter surface. The impact of the micro-groove area on the milling cutter surface and spindle speed on milling performance is discussed based on milling simulation and experimental tests. Experimental results show that the cutting force, milling temperature, and chip resistance to adhesion produced by micro-groove milling cutters are superior to conventional milling cutters. Milling cutters with three micro-grooves perform best at different spindle speeds. This is because the presence of micro-grooves on the surface of the milling cutter improves the friction state, promoting a reduction in milling force, while the micro-grooves also serve as storage containers for chips, alleviating the phenomenon of chip softening and adhesion to the cutter. When conducting cutting tests with a milling cutter that has three micro-grooves, the milling force is reduced by 10% to 30%, the milling temperature drops by 10% to 20%, and the surface roughness decreases by 8% to 12%. [ABSTRACT FROM AUTHOR]

Aiming at the problems of the Tyrannosaurus optimization algorithm, of poor search accuracy, insufficient global search capability, and ease of falling into local optimality, a dynamic hierarchical improved Tyrannosaurus optimization algorithm (DHTROA) with hybrid topology structure is proposed. Initially, a chaotic opposition-based learning approach is selected to start the population, ensuring a more uniform distribution of prey across the solution area and boosting population diversity; later, a dynamic hybrid bi-population strategy is introduced to divide the initial population into an 'advantaged group' and a 'disadvantaged group' to improve the efficiency of individual information exchange. Finally, the 'advantaged group' and 'disadvantaged group' are hunted synchronously; for the 'advantaged group', the position update is carried out using the cellular ring topology strategy, and for the 'disadvantaged group', the original algorithm is run in accordance with the main loop process. For the problem of the constant running rate of the Tyrannosaurus in the original algorithm, an adaptive running rate strategy is proposed, which enhances the ability of global optimization, and at the same time, the shortcomings of the original algorithm's 'failure' strategy are improved in order to enhance the original algorithm to jump out of extrema. DHTROA was tested for performance with nine optimization algorithms in different dimensions of the CEC2017 test function. The efficiency of these enhancements was confirmed through the Wilcoxon rank sum test and Friedman test, while DHTROA was utilized for six engineering optimization challenges of differing complexities. The experimental results show that DHTROA has improved greatly in convergence speed, optimality search accuracy, global search ability, and stability, and the excellent engineering optimization performance also proves the excellent robustness of DHTROA. [ABSTRACT FROM AUTHOR]

An enhanced dung beetle optimization algorithm (EDBO) is proposed for nonlinear optimization problems with multiple constraints in manufacturing. Firstly, the dung beetle rolling phase is improved by removing the worst value interference and coupling the current solution with the optimal solution to each other, while retaining the advantages of the original formulation. Subsequently, to address the problem that the dung beetle dancing phase focuses only on the information of the current solution, which leads to the overly stochastic and inefficient exploration of the problem space, the globally optimal solution is introduced to steer the dung beetle, and a stochastic factor is added to the optimal solution. Finally, the dung beetle foraging phase introduces the Jacobi curve to further enhance the algorithm's ability to jump out of the local optimum and avoid the phenomenon of premature convergence. The performance of EDBO in optimization is tested using the CEC2017 function set, and the significance of the algorithm is verified by the Wilcoxon rank-sum test and the Friedman test. The experimental results show that EDBO has strong optimization-seeking accuracy and optimization-seeking stability. By solving four engineering optimization problems of varying degrees, EDBO has proven to have good adaptability and robustness. [ABSTRACT FROM AUTHOR]

Titanium alloy material has physical properties such as low thermal conductivity, high hardness, and surface resilience, which are prone to problems such as large milling force, low machining efficiency, and poor surface quality in processed products during dry milling. This document details our process of isolating micro-textures from biological structures, applying them to cutting tool surfaces to create micro-texture milling cutters, and employing this micro-texture technique to reduce friction and prevent wear on these cutters. According to the milling dosage and the installation position between the tool and the workpiece, the effective working area of the cutting edge of the ball-end milling cutter is calculated. At the same time, a self-lubricating cutter was constructed by using a laser to process micro-textures and filling solid lubricant inside the micro-textures. An analysis was conducted to compare the milling efficiency of bionic microtextured cutters in both dry and micro-lubricated environments. It was found that the self-lubricating tool promoted a 3% to 5% decrease in milling force, a reduction in the coefficient of friction, a high surface finish of the machined workpiece, and an alleviation of chip sticking at the edge area. [ABSTRACT FROM AUTHOR]

Dry cutting is an effective method to realize the concept of green cutting today. However, in the process of cutting bearing steel, the high temperatures and high pressures produced by the cutting tool and chip under dry friction seriously affect the machining performance of the tool. Therefore, a bionic microstructure tool based on bionics is proposed to improve the cutting performance and reduce friction by changing the size parameters of the microstructure. On the basis of finite element simulation and cutting tests, the cutting force, surface roughness, and chip shape are used to evaluate the cutting performance. It is found that composite bionic micro-textured tools have a significantly reduced cutting force compared with non-micro-textured tools; composite bionic micro-textured tools lead to a reduction in surface roughness of 10–25%; and composite bionic micro-textured tools are more prone to enhancing the curling and breaking of chips. In addition, with the increase in the microstructure area occupancy, the cutting performance of the tool was also significantly improved. Moreover, it was found that the cutting performance of the tool was improved when the area occupancy of the micro-texture on the front face of the tool was increased. [ABSTRACT FROM AUTHOR]

In order to solve the problem of poor stability of hard brittle material in cutting process, a 45° groove micro-textured composite bionic tool was proposed. Under the same cutting parameters and conditions, the temperature rise and cutting force can be suppressed, and the tool stability can be reduced. Firstly, the design tool was modeled in three dimensions and the optimal bionic tool structure was optimized by finite element simulation technology. Secondly, four microstructures were constructed on the basis of biomimetic tools, and the optimum microstructures were selected based on shear force, stress distribution and chip discharge capacity. The smallest microstructure size parameters were obtained by changing the spacing of microstructures. Finally, on the basis of optimizing the micro-textured biomimetic tool, the surface of the tool was coated, and the influence of coating material on tool performance was discussed. The results showed that the cutting fracture rate of the material increased and the cutting accumulation phenomenon was alleviated obviously when the 45° chute micro-textured bionic tool with composite coating was used for machining. The cutting stability of the tool was enhanced and chip adhesion was reduced when cutting forces and cutting temperatures were reduced. At the same time, compared with conventional tools, the main cutting force and radial force decreased by 35% and 62%, and the cutting temperature decreased by 3.5%. With the decrease in cutting force and cutting temperature, the stability of cutting was enhanced and the phenomenon of chip adhesion on the tool surface was reduced. [ABSTRACT FROM AUTHOR]

Aluminum alloy materials are very difficult to break in the processing process; chip accumulation leads to poor processing stability. In this paper, a coated composite micro–textured tool is presented. The influence of coated composite micro–textured tool on chip shape and cutting force under the same cutting parameters is studied. Firstly, the combination of cutting force and cutting temperature is optimized based on cutting test. Secondly, combined with the finite element simulation technology, three kinds of composite micro–texture tools are tested to determine the same cutting parameters, tools and workpiece materials, and optimize the composite micro–texture combination from the angle of chip shape, cutting temperature and cutting force. Finally, on the basis of optimizing the microstructure combination, the optimization of the cutting performance of aluminum alloy by coating material is studied. It was found that the chip was more easily broken in the composite microstructure when two tools were used. The cutting force decreased by 25% and the cutting temperature decreased by 9.09% compared with the non–micro–texture tools. The cutting temperature and cutting force decreased by 3% and 4.99% compared with those of uncoated composite microstructure. [ABSTRACT FROM AUTHOR]