Numerical analysis and experimental validation of surface roughness and morphology in honing of Inconel 718 nickel-based superalloy AITranslate
Abstract AITranslate
Honing is an important technology for machining onboard system parts. The parts are usually made of difficult-to-machining materials, e.g., Inconel 718 superalloy. Honing can improve the finishing accuracy and surface quality. However, the selection of the honing parameters was primarily based on the results of a large number of experiments. Therefore, the establishment of a reliable model is needed to predict the honed surface roughness and morphology, and offers a theoretical direction for the choice of parameters. In the present study, a numerical simulation model was constructed for analysis of the honing process by Python. The oilstone, workpiece surface morphology and motion trajectory were discretized by Python, and the machined surface was obtained by trajectory interference. Firstly, based on the statistical analysis of the surface topography of oilstone, the shape of grains was simplified and the surface topography of oilstone was built accordingly. Then, the initial surface morphology of the workpiece was constructed and the trajectory of grains on the workpiece surface was analyzed, which showed the distribution of the removed material. Meanwhile, the plastic deformation of material was analyzed in the simulation model. The critical depth of three stages of contact between grains and workpiece was calculated by the theoretical formula: scratching, ploughing and cutting. By analyzing the distribution of bulge, the plastic deformation in ploughing and cutting stage was studied. Further, the simulated results of honed surface roughness and morphology were validated and agreed reasonably well with the honing experiment. Finally, the effects of honing process parameters, including grain size, tangential speed, axial speed, radial speed and abrasive volume percentage, on the surface roughness of the workpiece were analyzed by the simulation model.
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DOI:https://doi.org/10.1007/s40436-022-00422-0
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Honing is an important technology for machining onboard system parts. The parts are usually made of difficult-to-machining materials, e.g., Inconel 718 superalloy. Honing can improve the finishing accuracy and surface quality. However, the selection of the honing parameters was primarily based on the results of a large number of experiments. Therefore, the establishment of a reliable model is needed to predict the honed surface roughness and morphology, and offers a theoretical direction for the choice of parameters. In the present study, a numerical simulation model was constructed for analysis of the honing process by Python. The oilstone, workpiece surface morphology and motion trajectory were discretized by Python, and the machined surface was obtained by trajectory interference. Firstly, based on the statistical analysis of the surface topography of oilstone, the shape of grains was simplified and the surface topography of oilstone was built accordingly. Then, the initial surface morphology of the workpiece was constructed and the trajectory of grains on the workpiece surface was analyzed, which showed the distribution of the removed material. Meanwhile, the plastic deformation of material was analyzed in the simulation model. The critical depth of three stages of contact between grains and workpiece was calculated by the theoretical formula: scratching, ploughing and cutting. By analyzing the distribution of bulge, the plastic deformation in ploughing and cutting stage was studied. Further, the simulated results of honed surface roughness and morphology were validated and agreed reasonably well with the honing experiment. Finally, the effects of honing process parameters, including grain size, tangential speed, axial speed, radial speed and abrasive volume percentage, on the surface roughness of the workpiece were analyzed by the simulation model.
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| GB/T 7714-2015 | [1] ChangYong Yang, Zhi Wang, Hao Su, et al. Advances in Manufacturing, 2023(11). DOI:10.1007/s40436-022-00422-0. |
| MLA | [1] ChangYong Yang, et al., Advances in Manufacturing, no. 11, 2023, https://doi.org/10.1007/s40436-022-00422-0. |
| APA | [1] ChangYong Yang, Zhi Wang, Hao Su, YuCan Fu, NianHui Zhang, & WenFeng Ding. (2023). Advances in Manufacturing(11). https://doi.org/10.1007/s40436-022-00422-0 |
| IEEE | [1] ChangYong Yang, Zhi Wang, Hao Su, YuCan Fu, NianHui Zhang, and WenFeng Ding, Advances in Manufacturing, no. 11, 2023, doi: 10.1007/s40436-022-00422-0. keywords: {Numerical analysis;Surface roughness;Plastic deformation;Morphology} |
