Kinematic simulation of surface grinding process with random cBN grain model

Chen, Hao; Yu, Tianbiao; Dong, Jie; Yú, Zhao; Zhao, Ji

doi:10.1007/s00170-018-2840-x

Cited by 17 publications

(2 citation statements)

References 20 publications

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“…It is predicted that the surface damage forms are mainly burrs, pits, and boundary bosses caused by plastic deformation of the material, while the subsurface damage forms are mainly cracks, gullies, and so on. This is similar to the single particle simulation model and grinding results proposed by Chen et al [31] , and it also verifies the groove phenomenon under the plowing effect proposed by Zhou [32] . By analyzing the information contained in the surface topography and subsurface, the feasibility of the establishment of multiple abrasive rake angles is also confirmed.…”

Section: Fig 4 Materials Adhesion Diagramsupporting

confidence: 89%

Study on grinding surface quality of superalloy GH4145

zhao,

Gao,

Wang

et al. 2024

Preprint

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Nickl-based Superalloy GH4145 is widely used in aero-engine springs, blades, and other parts due to its excellent mechanical properties. It is a high-hardness and difficult-to-machine material. Improving the surface quality after processing has great significance for the long-term stable service of aero-engines. In this paper, Simulation models with different rake angles were established to predict the damage forms on the machined surface and subsurface on Abaqus. The effects of different process parameters on the surface quality of GH4145 were studied by using CBN grinding wheel. The influence of experimental parameters on the surface quality of GH4145 was analyzed and the related grinding mechanism was expounded. Under the scanning electron microscope (SEM) detection, the crack propagation process and the phenomenon of serious damage to the surface quality such as white layer were analyzed. The results show that the single particle prediction models with different rake angles can reflect the actual grinding situation to a large extent, and the model with the rake angle of -15° is more consistent with the detection phenomenon observed in this experiment. The surface damage forms are mainly pits, burrs, and boundary bosses caused by plastic deformation under simulation and experimental detection. The detection of the subsurface shows that in addition to the above phenomena, there are cracks and debris adhesion. The linear velocity of the grinding wheel is the main factor affecting the surface quality of the machined surface, the cutting depth is the second, and the feed rate has the least influence. The maximum roughness in the grinding experiment reaches 1.992 µm. Considering the thermal softening phenomenon of the material, the linear velocity range should be selected from 30 m/s to 35 m/s, and the feed rate and grinding depth should be selected relatively small values.

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Section: Fig 4 Materials Adhesion Diagramsupporting

confidence: 89%

Study on grinding surface quality of superalloy GH4145

zhao,

Gao,

Wang

et al. 2024

Preprint

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“…Academic and industrial relevance of proposed research topic is well described in various literature, notably instigated from the time-honored approach by Chen and Rowe 13,14 based on shape and spacing of cutting edges as well as cross-sectional area of chips. Investigations are still active as reported by Jiang et al 15 Wiederkehr et al, 16 Chen et al 17 and Kuffa et al 18 by incorporating wheel topography, grain distributions, material properties, tribological parameters, grain wear etc. However, many of these methodologies involve measurement of grinding wheel topography and its digital reproduction to superimpose with a flat surface to model the roughness of ground surface.…”

Section: Introductionmentioning

confidence: 99%

Feed based trajectory addition and elimination algorithm combined with stochastic meshless modelling to simulate roughness in surface grinding

Sooraj

Arun

Jithendrakumar

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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Surface grinding is observed to be an inevitable machining event in many of the functional engineering surfaces after pre-processing stages such as milling. Prediction of roughness profile after grinding on such initial surfaces, for selected operating conditions and grinding wheel specification, is always an interesting topic of investigation. Though a number of models have been reported in prior art, value additions through hybrid modelling strategies have been always contributing positively to this field of research due to the stochastic nature of abrasive interactions. Since feed rate of work piece is identified as a key grinding variable influencing the surface roughness, present paper introduces grain trajectory addition and elimination algorithm driven by feed based time scale to predict the ground surface topography. A realistic initial surface modelling is considered using meshless moving least square approximation incorporating both roughness as well as geometric deviation, expected to be imparted during pre-grinding stages. The algorithm is configured to compute two dimensional roughness parameters from the simulated surface profiles and these results are compared with experimental outcomes at various depths of grinding to validate the proposed model.

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Investigation of Micro Grinding via Kinematic Simulations

Altherr¹,

Kirsch²,

Aurich³

2023

Proceedings of the 3rd Conference on Physical Modeling for Virtual Manufacturing Systems and Processes

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With increasing demand for micro structured surfaces in hard and brittle materials, the importance of micro grinding increases. The application of micro pencil grinding tools (MPGTs) in combination with ultra precision multi axes machine tools allow an increased freedom of shaping. However, small dimensions of the grinding tools below 500 µm substantiate high rotational speeds and low feed rates to enable the machining process. Besides, the abrasive grits of the tool can be large in comparison to the tool dimensions. All factors will influence the resulting surface topography of the workpiece. But some of the topography properties are no longer accessible for optical measurements, making process evaluations and improvements difficult.In the present contribution the measurement results are supplemented by the results of a kinematic simulation model. The built up of such a kinematic simulation is described, which considers real process and tool properties. The results received by the simulation are compared to measurements to validate the model and point out the advantages of the simulations. In a further step, a principle is shown how the simulation can be used to make the undeformed chip thickness accessible, a process result which cannot be measured within the real machining process.

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Kinematic simulation of surface grinding process with random cBN grain model

Cited by 17 publications

References 20 publications

Study on grinding surface quality of superalloy GH4145

Study on grinding surface quality of superalloy GH4145

Feed based trajectory addition and elimination algorithm combined with stochastic meshless modelling to simulate roughness in surface grinding

Investigation of Micro Grinding via Kinematic Simulations

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