Ti6Al4V Titanium Alloy Machining Mechanism And Parameters Optimization

Manufacturing is the foundation of the entity economy, which is a measure of a country's pillar industry and influence national comprehensive strength, however, metal cutting processing plays an important role in the manufacturing industry, the titanium alloy material is also an important part of metal materials and has great research value in the field of machinery manufacturing industry. Because of the titanium alloy material has high strength, good abrasion resistance, strong ability to resist high temperature, creep and many of excellent mechanical performances, therefore it is widely used in aerospace, railway transport, car, special engineering machinery, petroleum, chemical, medical and other military and civilian fields. But the titanium alloy material also has low coefficient of thermal conductivity, low elastic modulus, severe work hardening and many cutting characteristics, so that lead to exist cutting heat in the process of machining, quality of surface processing and so on a series of technical problems, which is regarded as the typical difficult to machine materials. High speed cutting is considered a titanium alloy materials most widely used method in the manufacturing process, because of which has high processing efficiency to reduce cutting heat in the process of working and get higher machining precision effect on the machining surface. Based on Ti6Al4 V titanium alloy as the research object and the method of cutting are studied during the machining process, mainly including in the following several aspects:(1) The related of physical quantities theory and method of research are introduced, to the machining simulation provides the corresponding theoretical guidance.(2) The performance of titanium alloy, high speed machining principle and the chip formation, cutting force analysis, theoretical analysis of surface roughness and residual stress are described.(3) The machining process simulation experiment was carried out by DEFORM-3D. Analysis of the cutting parameters on cutting force, the influence of residual stress, etc. Which provides a reference and lay a foundation for actual production process to improve the processing precision, short the production cycle, and reduce cost.(4) To various physical quantity functions are not displayed in the actual processing engineering, in this paper, a method is researched based on support vector machine(SVM) model for physical quantity forecast. To establish forecasting model, the appropriate design parameters of the sample points are selected by using the method of orthogonal experiment design, and the predicted values and experimental values fitting curve are obtained, and test value are obtained from the finite element modeling. The predicted values and the experimental results respectively are analyzed to test error rate and significant. The BP neural network model is established to predict the test value, and compared with the predicting result of SVM model, the results show that SVM model can more accurately predict the results of Small sample data.(5) Based on the finite element software simulation data, the intelligent prediction model and parameter optimization theory, using genetic algorithm to optimize cutting parameters of titanium alloy, and the optimization results of cutting force is obtained.