TIME DOMAIN STUDY ON THE CONSTRUCTION MECHANISM OF MILLING STABILITY LOBE DIAGRAMS WITH MULTIPLE MODES

The stability lobe diagram (SLD) is an important expression way of milling stability prediction result. The SLD obtained by only selecting the most flexible mode fails to predict the chatter if the milling process is dominated by multiple modes. To reveal the relationship between the SLD with multiple modes and the SLDs corresponding to each single mode, this paper studies the construction mechanism of the SLD with multiple modes by using a time domain method. First, the milling dynamic model of the tool with multiple modes is established. Then, the numerical method based on the Newton-Cotes rules is used to solve the milling dynamic model with multiple modes whose solution is in the form of the SLD. It shows that the SLD with multiple modes can be approximated by using the lowest envelope of the SLDs corresponding to each single mode. Finally, two study cases are adopted to verify the construction mechanism of the SLD with multiple modes. To verify the correctness of the SLD with multiple modes, a series of milling tests are carried out. The experimental results agree with the simulation results, which means the proposed time domain method can reveal the construction mechanism of the SLD with multiple modes.

Time Domain Study on the Construction Mechanism of Milling Stability Lobe Diagrams With Multiple Modes

The stability lobe diagram (SLD) is an important expression way of milling stability prediction result. The SLD obtained by only selecting the most flexible mode fails to predict the chatter if the milling process is dominated by multiple modes. To reveal the relationship between the SLD with multiple modes and the SLDs corresponding to each single mode, this paper studies the construction mechanism of the SLD with multiple modes by using the time domain method. First, the milling dynamic model of the tool with multiple modes is established. Then, the numerical method based on the Newton-Cotes rules is used to solve the milling dynamic model with multiple modes whose solution is in the form of the SLD. It shows that the SLD with multiple modes can be approximated by using the lowest envelope of the SLDs corresponding to each single mode. Finally, two study cases are adopted to verify the construction mechanism of the SLD with multiple modes. To verify the correctness of the SLD with multiple modes, a series of milling tests are carried out. The experimental results agree with the simulation results, which means the proposed time domain method can reveal the construction mechanism of the SLD with multiple modes.

Chatter Stability Prediction and Process Parameters’ Optimization of Milling Considering Uncertain Tool Information

Stability is the prerequisite of a milling operation, and it seriously depends on machining parameters and machine tool dynamics. Considering that the tool information, including the tool clamping length, feeding direction, and spatial position, has significant effects on machine tool dynamics, this paper presents an efficient method to predict the tool information dependent-milling stability. A generalized regression neural network (GRNN) is established to predict the limiting axial cutting depth, where the machining parameters and tool information are taken as input variables. Moreover, an optimization model is proposed based on the machining parameters and tool information to maximize the material removal rate (MRR), where the GRNN model is taken as the stability constraint. A particle swarm optimization (PSO) algorithm is introduced to solve the optimization model and provide an optimal configuration of the machining parameters and tool information. A case study has been developed to train a GRNN model and establish an optimization model of a real machine tool. Then, effects of the tool information on milling stability were discussed, and an origin-symmetric phenomenon was observed as the feeding direction varied. The accuracy of the solved optimal process parameters corresponding to the maximum MRR was validated through a milling test.