Study On Parameter Optimization Of Cutting Difficult-to-machine Materials With CBN Cutting Tools In Dry Conditions

Cold work tool steels are widely used in the manufacture of molds and dies on account of their exceptional hardness,high wear resistance,high compressive strength,and good tempering performance.On the other hand,turning is a frequently used conventional machining method.The selection of cutting parameters in turning is closely related to the cutting force,cutting temperature,and surface residual stress,which in turn affects the mechanical properties and assembly characteristics of the product.Therefore,optimizing the cutting parameters during processing has become an important research topic in the field of mechanical manufacturing in recent years.Firstly,a 3-D model of turning Cr12 Mo V using cubic boron nitride(CBN)cutting tools in dry conditions was established by using finite element technique.Taking cutting speed,feed rate,cutting depth,and corner radius as variables,the simulation scheme was designed by using orthogonal experiment method.The simulation results of cutting force,cutting temperature and surface residual stress as research targets were extracted,and the influence of the above four cutting parameters on the three research targets were obtained.Then,the prediction analysis of cutting force,cutting temperature and surface residual stress was carried out,and the artificial neural network(ANN)prediction model and multiple linear regression(MLR)prediction model of the three research targets were established respectively.The results show that the maximum prediction errors of the ANN and MLR models are respectively 7.84% and 71.5%,indicating that the former has much higher prediction accuracy.Finally,in the part of optimizing the cutting parameters,the singleobjective analysis of cutting force,cutting temperature and surface residual stress was conducted by using signal-to-noise ratio analysis,and the main factors affecting cutting force,cutting temperature and surface residual stress are respectively cutting depth,cutting speed and feed rate,and the optimal processing parameters were obtained when separately considering cutting force,cutting temperature and residual stress.In the followed multiobjective optimization,the matrix analysis method was used and it was found that the order of the comprehensive effect of the cutting parameters on the three research indexes from high to low was cutting speed,cutting depth,feed rate,and corner radius.The neural network improved by genetic algorithm was used at last to optimize the multi-objective parameters and a set of optimal cutting parameters were obtained.This research provides theoretical support for the selection of cutting parameters for hard turning of Cr12 Mo V using CBN cutting tools in dry conditions.It should give a guidance for the practical production.Figure 33;Table 9;Reference 106...