Research on cutting mechanism and process optimization method of gear skiving
Abstract The cutting force and cutting temperature have a significant impact on the service life and durability of gear skiving cutters. Due to unreasonable design, the existing process parameters lead to dramatically nonuniform cutting force and cutting temperature, which aggravates the rapid wear...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-88469-4 |
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| _version_ | 1823862504172814336 |
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| author | Peng Wang Yuanchao Ni Xiaoqiang Wu Jiaxue Ji Geng Li Jiahao Wu |
| author_facet | Peng Wang Yuanchao Ni Xiaoqiang Wu Jiaxue Ji Geng Li Jiahao Wu |
| author_sort | Peng Wang |
| collection | DOAJ |
| description | Abstract The cutting force and cutting temperature have a significant impact on the service life and durability of gear skiving cutters. Due to unreasonable design, the existing process parameters lead to dramatically nonuniform cutting force and cutting temperature, which aggravates the rapid wear of gear skiving cutters. To address this issue, this paper first establishes a finite element model of skiving the internal circular arc tooth in pin wheel housing, and the simulation model is simplified to improve computation efficiency. Next, the impact of single process parameter on cutting force and cutting temperature is analyzed by controlling variable. Then, an orthogonal experiment is designed and the method of range analysis is employed to evaluate the significance of each process parameter. Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. This prediction model allows for the construction of a multi-objective optimization model for the process parameters. By solving this model, the optimal combination of process parameters within the given ranges can be obtained to achieve reasonable and balanced cutting force and cutting temperature. |
| format | Article |
| id | doaj-art-a43cb1037645409594297f53cdaf6446 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-a43cb1037645409594297f53cdaf64462025-02-09T12:29:34ZengNature PortfolioScientific Reports2045-23222025-02-0115111710.1038/s41598-025-88469-4Research on cutting mechanism and process optimization method of gear skivingPeng Wang0Yuanchao Ni1Xiaoqiang Wu2Jiaxue Ji3Geng Li4Jiahao Wu5Tianjin High-end Intelligent Machine Tool Engineering Research Center, Tianjin University of Technology and EducationTianjin High-end Intelligent Machine Tool Engineering Research Center, Tianjin University of Technology and EducationCollege of Engineering, Inner Mongolia Minzu UniversityTianjin High-end Intelligent Machine Tool Engineering Research Center, Tianjin University of Technology and EducationTianjin High-end Intelligent Machine Tool Engineering Research Center, Tianjin University of Technology and EducationTianjin High-end Intelligent Machine Tool Engineering Research Center, Tianjin University of Technology and EducationAbstract The cutting force and cutting temperature have a significant impact on the service life and durability of gear skiving cutters. Due to unreasonable design, the existing process parameters lead to dramatically nonuniform cutting force and cutting temperature, which aggravates the rapid wear of gear skiving cutters. To address this issue, this paper first establishes a finite element model of skiving the internal circular arc tooth in pin wheel housing, and the simulation model is simplified to improve computation efficiency. Next, the impact of single process parameter on cutting force and cutting temperature is analyzed by controlling variable. Then, an orthogonal experiment is designed and the method of range analysis is employed to evaluate the significance of each process parameter. Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. This prediction model allows for the construction of a multi-objective optimization model for the process parameters. By solving this model, the optimal combination of process parameters within the given ranges can be obtained to achieve reasonable and balanced cutting force and cutting temperature.https://doi.org/10.1038/s41598-025-88469-4Gear skivingCutting forceCutting temperatureProcess parametersGenetic algorithmMulti-objective optimization |
| spellingShingle | Peng Wang Yuanchao Ni Xiaoqiang Wu Jiaxue Ji Geng Li Jiahao Wu Research on cutting mechanism and process optimization method of gear skiving Scientific Reports Gear skiving Cutting force Cutting temperature Process parameters Genetic algorithm Multi-objective optimization |
| title | Research on cutting mechanism and process optimization method of gear skiving |
| title_full | Research on cutting mechanism and process optimization method of gear skiving |
| title_fullStr | Research on cutting mechanism and process optimization method of gear skiving |
| title_full_unstemmed | Research on cutting mechanism and process optimization method of gear skiving |
| title_short | Research on cutting mechanism and process optimization method of gear skiving |
| title_sort | research on cutting mechanism and process optimization method of gear skiving |
| topic | Gear skiving Cutting force Cutting temperature Process parameters Genetic algorithm Multi-objective optimization |
| url | https://doi.org/10.1038/s41598-025-88469-4 |
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