Automated design and analysis of dies for the bearing hub hot forging process using adaptive parametric CAD design with real-time design changes.
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| Title: | Automated design and analysis of dies for the bearing hub hot forging process using adaptive parametric CAD design with real-time design changes. |
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| Authors: | Oh, Minseong1 (AUTHOR), Yi, Sarang1 (AUTHOR), Cho, Juhyun2 (AUTHOR), Kim, Jinkuk2 (AUTHOR), Kim, Mincheol3 (AUTHOR), Moon, Hokeun3 (AUTHOR), Hong, Seokmoo4,5 (AUTHOR) smhong@kongju.ac.kr |
| Source: | International Journal of Advanced Manufacturing Technology. Jul2025, Vol. 139 Issue 5/6, p2365-2375. 11p. |
| Subjects: | Parametric modeling, Forging (Manufacturing process), Three-dimensional modeling, Computer-aided design software, Prototypes, Sensitivity analysis, Automotive engineering, Automobile parts |
| Abstract: | The diversification of automobile brands and models has recently rendered the design of bearing hubs increasingly complex, as it must accommodate the varying purposes of different vehicles. The design process has become more time-intensive due to the growing number of variables that must be considered in the development of bearing hub hot forging preforms. Furthermore, modifications to preform designs frequently necessitate repetitive iterations of similar design processes. To address these challenges, this study proposes a method for automating the design and analysis of the automotive bearing hot forging process using adaptive parametric computer-aided design (CAD). The proposed methodology employs three-dimensional (3D) parametric CAD to produce manufacturing-ready designs by identifying the feature points embedded within the two-dimensional (2D) shape drawings of bearing hubs, while simultaneously generating 3D die sets. Additionally, the adaptive parametric concept, which specifies points based on their spatial locations, was introduced to facilitate automated design without user intervention. This approach enables the seamless importation of similar bearing hub designs, even when variations in the positions and quantities of feature points occur. The proposed method was applied to the design and analysis of hot forging processes for automotive bearings, demonstrating its practicality. Automation of die design and analysis accelerated preprocessing and postprocessing by approximately 660-fold. Based on these results, sensitivity analysis and optimal design were successfully performed by integrating the adaptive parametric design methodology with analysis automation software featuring a graphical user interface (GUI). [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | The diversification of automobile brands and models has recently rendered the design of bearing hubs increasingly complex, as it must accommodate the varying purposes of different vehicles. The design process has become more time-intensive due to the growing number of variables that must be considered in the development of bearing hub hot forging preforms. Furthermore, modifications to preform designs frequently necessitate repetitive iterations of similar design processes. To address these challenges, this study proposes a method for automating the design and analysis of the automotive bearing hot forging process using adaptive parametric computer-aided design (CAD). The proposed methodology employs three-dimensional (3D) parametric CAD to produce manufacturing-ready designs by identifying the feature points embedded within the two-dimensional (2D) shape drawings of bearing hubs, while simultaneously generating 3D die sets. Additionally, the adaptive parametric concept, which specifies points based on their spatial locations, was introduced to facilitate automated design without user intervention. This approach enables the seamless importation of similar bearing hub designs, even when variations in the positions and quantities of feature points occur. The proposed method was applied to the design and analysis of hot forging processes for automotive bearings, demonstrating its practicality. Automation of die design and analysis accelerated preprocessing and postprocessing by approximately 660-fold. Based on these results, sensitivity analysis and optimal design were successfully performed by integrating the adaptive parametric design methodology with analysis automation software featuring a graphical user interface (GUI). [ABSTRACT FROM AUTHOR] |
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| ISSN: | 02683768 |
| DOI: | 10.1007/s00170-025-15966-1 |
