Axis Position Dependent Dynamics of Multi-axis Milling Machines

Brecher, Christian; Altstädter, H.; Daniels, Matthias

doi:10.1016/j.procir.2015.03.068

Cited by 25 publications

(11 citation statements)

References 16 publications

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“…The interpolation of the FRFs at the involved MPs is shown in Eq. (7). For the required FRF, the interpolated data from the MPs are B u and B o represent the two B-axis positions where measurement data exist and the required B-axis position B r is located in between.…”

Section: Utilized Interpolation Methodsmentioning

confidence: 99%

“…The dynamic properties of machining centers change when the position of the rotary and linear axes is varied [7]. Hung and Lin, e.g., showed the influence of the position of a bi-rotating milling head on the process stability [8].…”

Section: Introductionmentioning

confidence: 99%

“…Lee and Altintas, as well as Kono et al determined an alteration of the compliance magnitude of up to 40 % resulting from a variation of the tilt angle [10,13]. Moreover, the position of the linear axes can also influence the dynamic properties of the machining center [7].…”

Section: Introductionmentioning

confidence: 99%

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Application of interpolation methods for the determination of position-dependent frequency response functions for the simulation of 5-axis milling processes

Wilck

Wirtz

Biermann

et al. 2021

Prod. Eng. Res. Devel.

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The occurrence of chatter vibrations in 5-axis milling processes is a common problem and can result in part failure, surface defects and increased wear of the cutting tool and the machine tool. In order to prevent process vibrations, machining processes can be optimized by utilizing geometric physically-based simulation systems. Since the modal parameters of the machine tool are dependent on the position of the linear and rotary axes, the dynamic behavior of milling processes can change along the NC path despite constant engagement conditions. In order to model the pose-dependent modal properties at the tool tip, the frequency response functions (FRFs) were measured at different locations of the workspace of the machine tool for various poses of the rotary axis of the spindle. To take the varying compliance within the workspace of a machine tool into account in a geometric physically-based milling process simulation, different interpolation methods for interpolating FRFs or parameter values of oscillator-based compliance models (OPV) were applied. For validation, the resulting models were analyzed and compared to measured data. In OPV interpolation, the individual oscillation modes were interpolated in their respective characteristics based on the oscillator parameters (eigenfrequencies, modal masses and damping values). In FRF interpolation, however, there was no differentiation between the modes, resulting in a wrong interpolation. It can therefore provide good results when only a small shift of the eigenfrequencies is expected, as in case of the analyzed machine tool, with only small movements of the translatory axes.

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Section: Utilized Interpolation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of interpolation methods for the determination of position-dependent frequency response functions for the simulation of 5-axis milling processes

Wilck

Wirtz

Biermann

et al. 2021

Prod. Eng. Res. Devel.

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“…The other way round, Spescha D et al [8][9] employed triangular interpolation based on Fourier series expansion, to introduce loads between moving interface of the feed axes of the machine tools. Brecher C et al [10][11] proposed rigid-body elements (RBE) that move with a component and search for the nearest node at the desired position. Law M [12][13] demonstrated Lagrange-multipliers method and penalty method to calculate the dynamic response of the reduced order model.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling and Experimental Research on Position-dependent Behavior of Twin Ball Screw Feed System

Duan

Lü

Zhang

et al. 2021

Preprint

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To establish the dynamic model of machine tool structure is an important means to assess the performance of the machine tool structure during the cutting process. It’s necessary to study the dynamics of the machine tools in different configurations for the sake of analyzing the dynamic behavior of the machine tools in the entire workspace. In this paper, a robust approach is presented to build an efficient and reliable dynamic model to evaluate the position-dependent dynamics of the twin ball screw (TBS) feed system. First, the TBS feed system is divided into several components and a finite element (FE) model is built for each component. Second, the Craig-Bampton method is proposed to reduce the order of the substructures. Third, a multipoint constraints (MPCs) method was introduced to model the mechanical joints substructures of the TBS system, and the spring-damper element (SDE) is employed to connect the condensation nodes. Finally, a series experimental tests and full order FE analysis are conducted on the self-designed TBS worktable in the four positions to validate the effectiveness of the proposed dynamic model. The results show that the proposed approach evaluates accurately the position-dependent behavior of the TBS system.

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“…Additionally, stability lobe diagrams (SLD) can be calculated for different combinations of the process parameter values using suitable stability criteria. However, especially when machining free-formed surfaces of large workpieces, the pose-dependent load of the spindle bearings and axis drives influences the modal properties of the system significantly [11,[13][14][15], resulting in different frequency response behaviors for each pose defined by the NC path.…”

Section: Introductionmentioning

confidence: 99%

Learning-Based Prediction of Pose-Dependent Dynamics

Finkeldey

Wirtz

Merhofe

et al. 2020

JMMP

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The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to vibrations, which can deteriorate the quality of the machined workpiece surface. The prediction of tool vibrations based on the used NC path and process configuration can be achieved by, e.g., applying geometric physically-based process simulation systems prior to the machining process. However, recent research showed that the dynamic behavior of the system, consisting of the machine tool, the spindle, and the milling tool, can change significantly when using different inclination angles to realize certain machined workpiece shapes. Intermediate dynamic properties have to be interpolated based on measurements due to the impracticality of measuring the frequency response functions for each position and inclination angle that are used along the NC path. This paper presents a learning-based approach to predict the frequency response function for a given pose of the tool center point.

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Axis Position Dependent Dynamics of Multi-axis Milling Machines

Cited by 25 publications

References 16 publications

Application of interpolation methods for the determination of position-dependent frequency response functions for the simulation of 5-axis milling processes

Application of interpolation methods for the determination of position-dependent frequency response functions for the simulation of 5-axis milling processes

Dynamic Modeling and Experimental Research on Position-dependent Behavior of Twin Ball Screw Feed System

Learning-Based Prediction of Pose-Dependent Dynamics

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