| With the reputation of space age metal, Titanium alloys have been used extensively in aerospace industry. However, it is difficult to machine due to their poor thermal conductivity, low elastic modulus and high chemical activation. During machining of Titanium alloys, rapid tool wear and deterioration of surface integrity make the cutting speed very low. Simultaneously, due to the characteristics of component design, a great deal of stock has to be removed from primary forms, resulting in a larger machining cost. Therefore, the contradiction between increasing machining demand and poor machining performance has been one of the bottlenecks blocking the development of aerospace industry. In this study, the high speed milling mechanism of Titanium alloys Ti6A14V was systematically researched from the sides of milling force, milling temperature, surface integrity and tool wear and life, in order to provide theoretical support for the built-up of Titanium alloys' high performance machining technique. According to the understanding of machining mechanism, the milling parameters are optimized under the objectives of both maximized production efficiency and minimized exhaustion of tool life.Cutting force is one of the important physical variables in cutting process, which shows strong influence on workpiece's surface integrity and tool wear. Therefore, it is encouraging to accurately predict cutting force in order to optimize cutting parameters and tool design. For end milling cutters, a three dimensional milling force model was proposed, in which the plough effect of tool edge's radius was incorporated. The cutting edge was discretized into a series of small elements. The cutting forces of each small element includes shear force and plough force. Through integrating the cutting forces of small elements along axial depth of cut, the cutting forces of tool can be obtained. Unlike many traditional methods about identifying milling force coefficients, a more rapid and economical method was advised, which uses the instantaneous milling forces to identify milling force coefficients. Because milling force coefficients are influenced by workpiece's material mechanical properties, an empirical model was built up with experiments and regress method, which is tenable under high speed condition. From the view of controlling of milling forces, medium milling speed, large radial depth of cut, small feed and axial depth of cut are preferred.The machining efficiency of Titanium alloys depends on the effect of heat control. Through studying the generation of heat and the distribution of temperature in workpiece and tool, the cutting process and tool life can be improved, further more, the machining efficiency and quality may be enhanced. The influences of milling parameters on milling temperature were investigated through infra-radiation measurement method. It was found that, the milling temperature increases with milling speed and feed per tooth. A three dimensional finite element model of milling was modeled to analyze the temperature distributions in workpiece's deform zones and tool. The highest temperature in workpiece locates near the root zone of the chip, where high strain rate and large strain also occur. The highest temperature in the tool is near the primary cutting edge in the rake face, which is lower relative to that in workpiece due to good thermal conductivity. When milling speed increases, the temperature in the contact zone between the chip and the tool rises up simultaneously, the heat source is expanded along the axial depth of cut, and pressure also increases.Surface integrity directly determines the performance of components, which is the criterion in production design and selection of technique. According to the observations of experiments, coated inserts and MQL conditions can get lower roughness. When milling under higher speed condition, a combination with smaller feed per tooth, small axial depth of cut and medium radial depth of cut can lead to good roughness. According to the relative movement features between tool and workpiece and the mechanical properties of workpiece, a surface residual height model for horizontal machined surface was proposed. According to the observation of the microstructure in machined surface layer with SEM, the grains show a larger deformation depth and magnitude under low milling speed or small feed per tooth condition. High speed milling may weaken the deformation of grains and reduce the thickness of deformation layer, which is beneficial to component's surface integrity. Through the measurement and analysis of microhardness, the influences of milling speed and feed per tooth were investigated. With the increase of milling speed while keep feed unchanged, the microhardness firstly decreases, then increases due to tool edge's ploughing effect. The microhardness decreases with feed per tooth. A process of hardening-softening-hardening-leveling off occurs under both high speed milling condition and low speed condition. The softening layer has smaller mircohardness and depth under high speed milling condition. According to theory of dislocation, a dynamic model of work hardening was suggested, which discloses the relation between work hardening, microstructure and flow stress. By means of X radiation diffraction method, the influences of milling parameters on residual stress were investigated. The feed per tooth shows a strong effect on residual stress, while the radial depth of cut has a minor effect. Through analysis of milling forces and temperature, it can be concluded that the surface residual stresses are only relevant with the deformation induced by mechanical and thermal stress, and the burnishing effect between machining formation surface and tool's flank surface results in the generation of compressive residual stress.During machining of Titanium alloys, rapid tool wear shortens tool's life, which reduces the machining efficiency and increases machining cost. According to experiments, the types and mechanisms of tool wear during milling of Titanium alloys Ti6A14V were investigated, the empirical model tool life was proposed through regress method and the factors influencing tool wear and tool life were concluded. During milling of Titanium alloy Ti6A14V, the wear and failure of tool were a combination of many mechanisms such as adhesion, oxidization, attrition, diffusion-expansion and crack. Milling speed, feed per tooth and axial depth of cut have a strong effect on tool life, while the radial depth of cut has a minor effect.With an attempt to relief condition of the high machining cost and low machining efficiency existed in milling of Titanium alloys, a cutting process optimization model was proposed, in which the maximal production rate and minimal exhaustion of tool life were considered. For the multi-objective optimization problems, due to the conflict or lack of comparability between objectives, much encouraging efforts are to find the Pareto-optimal solutions. Classical optimization methods usually scalarize the vector of objectives into one objective by using some knowledge of the problem being solved. The main drawbacks of these algorithms are their sensitivity towards weights or demand levels and single point solution. Evolution algorithms have strong parallel search ability and can find multiple Pareto optimal solutions in a single run. In this study, the NSGA-II was improved with the extension of non-dominance concept from solution space to constraints space. The improvement makes the handling of problems with multiple objectives and multiple constraints more robust and effective. By virtue of milling force, roughness and tool life's empirical models, an optimization process was implemented and the Pareto front was found. The technicians can choose milling parameters flexibly according to the preference to the objectives. It is more economical and convenient when compared with weight methods. It will provide benifical support for milling of Titanium alloys if it is programmed into machining database.
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