Experimental Study And Finite Element Simulation Of Turning Machining Of Stainless Steel

Stainless steel materials are widely used in each link of oil and natural gas industry in china because of excellent corrosion resistance. However, surface quality of stainless steel have a large effect on fatigue life and corrosion resistance according to use on the scene, and the surface quality often leads to failure. In addition, high plasticity, high hardness and serious work hardening of stainless steel make its surface quality difficult to improve in the cutting process. This thesis concentrates on AISI304stainless steel, the analytical method based on FEA and experiments is used to research the cutting performance under different cutting parameters. And under the premise of meeting the demands for surface quality, parameter combinations with the highest machining efficiency are obtained.The thesis, after investigation on a large quantity of domestic and international literatures about metal cutting, analyses key technology about FEA simulation of metal cutting. On this basis, Abaqus FEM software is used to establish a two-dimensional orthogonal metal cutting model of YW2carbide Tool turning AISI304stainless steel. And the rule of cutting force, cutting temperature, chip shape and machining-induced residual stresses with the change of cutting parameter and cutting tool geometry parameter are analysed.In order to research the change rule of surface quality of stainless steel with the change of cutting parameters and validate the accuracy of FEM model, turning experiments of AISI304stainless steel are conducted. After the experiments, surface roughness and work hardening layer thickness are obtained and the rule of cutting parameter and cutting tool geometry parameter are analysed. Moreover, main cutting force is contrast with simulation value to validat validity of FEM model.Prediction model of surface roughness and work hardening layer thickness is fitted by using response surface method on the basis of surface roughness and work hardening layer thickness under central composite experimental conditions.With the constraint conditions of prediction model, with objective function of metal removal rate, with boundary condition of value range of three factors of cutting, carring on optimal combination of cutting parameters under homologous constraint value by using multi-island genetic algorithm optimizing, optimal cutting factors for quality of the machined surface are obtained.