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Abstract Thin-walled parts are typically difficult-to-cut components due to the complex dynamics in cutting process. The dynamics is variant for part during machining, but invariant for machine tool. The variation of the relative dynamics results in the difference of cutting stage division and cutting parameter selection. This paper develops a novel method for whole cutting process optimization based on the relative varying dynamic characteristic of machining system. A new strategy to distinguish cutting stages depending on the dominated dynamics during machining process is proposed, and a thickness-dependent model to predict the dynamics of part is developed. Optimal cutting parameters change with stages, which can be divided by the critical thickness of part. Based on the dynamics comparison between machine tool and thickness-varying part, the critical thicknesses are predicted by an iterative algorithm. The proposed method is validated by the machining of three benchmarks. Good agreements have been obtained between prediction and experimental results in terms of stages identification, meanwhile, the optimized parameters perform well during the whole cutting process.

Thin-walled parts are typically difficult-to-cut components due to the complex dynamics in cutting process. The dynamics is variant for part during machining, but invariant for machine tool. The variation of the relative dynamics results in the difference of cutting stage division and cutting parameter selection. This paper develops a novel method for whole cutting process optimization based on the relative varying dynamic characteristic of machining system. A new strategy to distinguish cutting stages depending on the dominated dynamics during machining process is proposed, and a thickness-dependent model to predict the dynamics of part is developed. Optimal cutting parameters change with stages, which can be divided by the critical thickness of part. Based on the dynamics comparison between machine tool and thickness-varying part, the critical thicknesses are predicted by an iterative algorithm. The proposed method is validated by the machining of three benchmarks. Good agreements have been obtained between prediction and experimental results in terms of stages identification, meanwhile, the optimized parameters perform well during the whole cutting process. [ABSTRACT FROM AUTHOR]

Abstract In order to predict the quality and the stability properties of milling processes, the relevant dynamics reduced to the cutting edges needs to be known. However, the dynamics varies through the workspace along the tool path during a given machining operation. This is the case for large heavy duty milling operations, where the main source of the relevant dynamics is related to the otherwise slowly varying machine structure rather than to the fairly steady milling tool dynamics. The effect of slowly varying dynamic parameters is presented for milling stability when the cutting process takes place in a region of the work space where the steady-state cutting would change from stable to unstable. After the separation of the slow and fast time scales, the governing non-autonomous delay differential equation is frozen in slow-time in order to determine the time-periodic stationary cutting solution of the milling operation for different parameters. The loss of stability is predicted from the correction to the time-periodic frozen time solution, for which we obtained non-autonomous equation for the accumulated growth over the slow-time. The growth shows loss of stability with a shift on the parameters compared to the static parameter solution. [ABSTRACT FROM AUTHOR]

The structural model of the workpiece is required for modeling, analysis, and avoidance of forced and regenerative (chatter) vibrations in machining of thin-walled parts. Finite element models (FEM) provide a versatile means for modeling the workpiece dynamics, but such models need to be updated frequently as the mass and stiffness of the workpiece varies continuously during machining. The computational time and power that is needed for re-meshing the FEM and then re-computing the natural modes of the workpiece is prohibitive. In this paper, a new approach based on Finite strip modeling (FSM) is presented for modeling the structural dynamics of thin-walled structures during pocket milling operations. The substantially higher computational efficiency of the FSM approach in predicting the varying dynamics of thin-walled pocket structures is verified by comparing its performance against FEM and the multi span plate (MSP) approach presented in (J Manuf Sci Eng 133:021014, 2011). Additionally, the accuracy of the presented approach in analyzing the stability of vibrations and determining the extent of dynamic deflections is verified using experimental results. [ABSTRACT FROM AUTHOR]