| With the development of new material technology, the tool performance requirements in cutting industry are getting more challenge. The ceramic cutting tools exhibite high hardness, high wear resistance, high temperature resistant, which provide a very broad application prospect in many industries.The research on the cutting performance of ceramic tools in general is conducted by very tedious experiment with many experimental parameters involved. The research on cutting performance needs to be repeated to ensure reliable and consistent database resulting in high cost and long research period. With the development of high performance computing technology and new calculation algorithm, the finite element analysis (FEA) method has become an effective tool to solve complex engineering analysis and calculation, and it has been fully applied in all fields of industrial production. The analysis of FEA in the cutting field has mainly focused on the cutting simulation of carbide-based tools. However,the cutting process simulation of ceramic cutting tools is very limited, especially for the Si3N4 ceramic cutting tool. Because of the large differences in physical and mechanical properties between ceramic material and hard alloy material, the cutting simulation results of cemented carbide tools are not applicable for the analysis of ceramic cutting tools. In addition, in the past, the choice of cutting parameters of ceramic tools often ignored the constraints on the investment and the production cost, because the researchers always focus on the cutting parameters of ceramic cutting tools during the application.In view of the above stated problems, this paper uses the FEA method combined with cutting experiments to predict the cutting force, cutting temperature, and tool wear of Si3N4 cutting tools and also study the influence factors during the cutting process. A genetic algorithm is also applied to optimize the cutting parameters and performance of Si3N4 ceramic tools.In this paper, the linear regression method is used to deduce the wear coefficient,with using of computer tomography technology to measure tool wear depth,using of the Deform’s point tracking function to obtain parameters of interface. Also, the FEA study includes study on cutting simulation analysis, use of the Deform finite element software for cutting simulation of four kinds of Si3N4 ceramic cutting tools, analysis of influencing factors of cutting force, cutting temperature, and tool wear. Lastly, studies on cutting experiment by comparing the simulation and experiment of the chip shape, cutting temperature, and tool wear depth were conducted to demonstrate the validility and reliability of the simulation models. The cutting parameter optimization analysis of Si3N4 ceramic tool is carried out, and the optimal cutting parameters are obtained by the genetic algorithm with the minimum unit of material production cost as the constraint boundary condition.The results of the study show that FEA results obtained via the model developed can accurately predict the wear of Si3N4 cutting tool during the cutting process, and the comparison between the FEA and experimental results shows the error is less than 15%. The analysis of the fixed point tracking function of Deform shows that the hardness, interfacial pressure, the interfacial temperature, and sliding velocity have a great impact to the wear phenomena of the Si3N4 ceramic tool. Results of FEA simulation as compated with the experimental results exhibit a comparable trend of (1) the chip morphology is consistent, (2) the cutting temperature is consistent, (3) the error is less than 15%, (4) the wear pattern and wear trend is consistent. Thus, the stdudy suggest that the simulation model developed is reliable and valid. The optimization method based on genetic algorithm is then employed to obtain the optimal cutting parameters of SiaN4 ceramic tools, and a cutting parameter optimization method is presented and discussed in ths thesis. |
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