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Computational diagnostics of self-excited vibration in a machine tool-cutting process system.

100%

Bodnar A.

tom vol. 22, nr 2

53-72

The paper presents a methodology of computational diagnostics of self-excited vibration, i.e. detecting the weak links - in term of the machine tool's cutting process system stability - in the machine mass-dissipation-spring system (the MDS system). A way of creating a mathematical model of the machine tool-cutting process system in the convention of the rigid finite element method is outlined. For such a definited computational model an algorithm for seeking weak links in the machine tool MDS system is presented. The algorithm action effectiveness is ilustrated by a computational example done for the FWD 32J milling machine.

Przedstawiono metodykę obliczeniowej diagnostyki drgań samowzbudnych obrabiarki, czyli wykrywania w jej układzie masowo-dyssypacyjno-sprężystym (MDS) słabych ogniw ze względu na wibrostabilność systemu obrabiarka-proces skrawania. Pokazano w zarysie sposób tworzenia matematycznego modelu systemu obrabiarka-proces skrawania w konwencji metody sztywnych elementów skończonych. Dla tak zdefiniowanego modelu obliczeniowego opracowano algorytm poszukiwania słabych ogniw w układzie MDS obrabiarki. Skuteczność działania algorytmu ilustruje przykład obliczeniowy wykonany dla frezarki FWD 32J.

Investigation of the Dynamic Characteristics and Machining Stability of a Bi-rotary Milling Tool

84%

Hung J.-P. , Lin W.-Z.

2019

tom Vol. 13, no 1

14--22

Bi-rotary milling head is the primary component of multiple-axis machine tool toward the multiply machining operation. The machining performance is greatly related to the structure characteristics and positioning precisions of the swivel head. This study was aimed at developing a bi-rotary milling head module, which is composed of a direct drive motor, cross roller bearings and motorized spindle unit. In order to evaluate the machining stability at the design phase, the dynamic characteristics of the rotary milling were first analyzed with finite element method. Especially, the variations of the dynamic characteristics of the spindle tool with the changing of the titling configuration of swivel axis were examined. In order to consider the accurate presentation of a spindle tool system and swivel mechanism, the bearings in the rolling components were also included in the finite element model and simulated with surface contact elements with adequate contact stiffness. The dynamic frequency response function of the spindle tool at different swinging positions were predicted for comparisons, which were further used to calculate the machining stability based on the machining mechanics. The current results show that the feeding direction and swinging positions of rotary milling head have a significant influence on the dynamic characteristics and machining ability of the spindle tool. The variations of the cutting depth with the swinging of A axis fall in the range of 11% to 40%, depending on the feeding direction and swinging angle. The analysis results are expected to clearly demonstrate the variation of the machining performance of the spindle tool under different milling configurations. The devised model and modeling approach can be applied to develop a five axis milling machine with desired dynamic and machining performance.

Prediction of Surface Roughness based on the Machining Conditions with the Effect of Machining Stability

84%

Lin Y.-C. , Chen Y.-C. , Wu K.-D. , Hung J.-P.

tom Vol. 14, no 2

171--183

This study was aimed at analyzing the influence of the cutting parameters (spindle speed, feed rate and cutting depth) on the surface roughness of the machined parts with the influence of the machining stability of the cutter. In order to consider the chattering effect, the machining stabilities were calculated based on the measured tool tip frequency response functions. A series of machining tests were conducted on aluminum workpieces under different cutting parameters. Then, the surface roughness prediction models in the form of nonlinear quadratic and power-law functions were established based on the multivariable regression method, in which the input parameters, cutting depth and spindle speed, were respectively defined in the stable and unstable regions, according to the stability lobes diagram. The current results show that both models built with the cutting parameters defined in stable regions demonstrate higher prediction accuracy of the surface roughness, about 90%, when compared with the models defined in full regions with the accuracy of about 80%. In particular, the power-law model is proven to have 90% prediction accuracy when validated with the cutting parameters in a stable region. As a conclusion, the mathematical models based on the cutting parameters with well-defined machining stability were proven to show more accurate prediction ability of the surface roughness. It could be expected that the prediction model can further be applied to optimize the machining conditions in low speed roughing and high speed finishing process with desirable surface quality.