Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet
This paper presents a novel Q-value-based formability assessment for optimizing deep drawing processes. The Q-value, derived from thinning limit diagrams (TLDs), uses offset thinning and wrinkling limit curves to define severity levels. It is calculated by summing the product of Pascal’s triangle we...
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MDPI AG
2025-01-01
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| author | Jidapa Leelaseat Aekkapon Sunanta Surasak Suranuntchai |
| author_facet | Jidapa Leelaseat Aekkapon Sunanta Surasak Suranuntchai |
| author_sort | Jidapa Leelaseat |
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| description | This paper presents a novel Q-value-based formability assessment for optimizing deep drawing processes. The Q-value, derived from thinning limit diagrams (TLDs), uses offset thinning and wrinkling limit curves to define severity levels. It is calculated by summing the product of Pascal’s triangle weighting factors and normalized element counts within each severity level. The effectiveness of this Q-value assessment was demonstrated using experimentally validated finite element analysis (FEA) to optimize blank size, tool geometry, and drawbead design (male bead height and contra-bead radius) for a deep-drawn AA5754-O automotive fuel tank. Validation of FEA results with experimental thickness measurements showed that the Barlat and Lian 1989 yield criterion provided higher accuracy than Hill’s 1948 model. An optimal condition, determined using the Q-value, consists of a 430 mm × 525 mm blank formed by a redesigned tool cooperated with optimized semi-circular drawbead geometries, achieving experimental significant formability improvements by minimizing wrinkling and thinning. During optimization, this study revealed a significant interaction between blank width and length, which influenced formability. Side-wall wrinkles were attributed to insufficient tool support for the blank during forming and were relieved through tool redesign. Furthermore, increasing the male drawbead height effectively reduced wrinkling but led to increased thinning, whereas increasing the contra-bead radius had the opposite effect. |
| format | Article |
| id | doaj-art-ce538db074d64deb87c24407cb9b4d65 |
| institution | Kabale University |
| issn | 2075-4701 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-ce538db074d64deb87c24407cb9b4d652025-01-24T13:41:34ZengMDPI AGMetals2075-47012025-01-011516810.3390/met15010068Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys SheetJidapa Leelaseat0Aekkapon Sunanta1Surasak Suranuntchai2Department of Tool and Materials Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Rd., Bang Mod, Thung Khru, Bangkok 10140, ThailandDepartment of Tool and Materials Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Rd., Bang Mod, Thung Khru, Bangkok 10140, ThailandDepartment of Tool and Materials Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Rd., Bang Mod, Thung Khru, Bangkok 10140, ThailandThis paper presents a novel Q-value-based formability assessment for optimizing deep drawing processes. The Q-value, derived from thinning limit diagrams (TLDs), uses offset thinning and wrinkling limit curves to define severity levels. It is calculated by summing the product of Pascal’s triangle weighting factors and normalized element counts within each severity level. The effectiveness of this Q-value assessment was demonstrated using experimentally validated finite element analysis (FEA) to optimize blank size, tool geometry, and drawbead design (male bead height and contra-bead radius) for a deep-drawn AA5754-O automotive fuel tank. Validation of FEA results with experimental thickness measurements showed that the Barlat and Lian 1989 yield criterion provided higher accuracy than Hill’s 1948 model. An optimal condition, determined using the Q-value, consists of a 430 mm × 525 mm blank formed by a redesigned tool cooperated with optimized semi-circular drawbead geometries, achieving experimental significant formability improvements by minimizing wrinkling and thinning. During optimization, this study revealed a significant interaction between blank width and length, which influenced formability. Side-wall wrinkles were attributed to insufficient tool support for the blank during forming and were relieved through tool redesign. Furthermore, increasing the male drawbead height effectively reduced wrinkling but led to increased thinning, whereas increasing the contra-bead radius had the opposite effect.https://www.mdpi.com/2075-4701/15/1/68formabilitydeep drawing processoptimizationfinite element simulationautomotive partaluminum alloys sheet |
| spellingShingle | Jidapa Leelaseat Aekkapon Sunanta Surasak Suranuntchai Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet Metals formability deep drawing process optimization finite element simulation automotive part aluminum alloys sheet |
| title | Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet |
| title_full | Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet |
| title_fullStr | Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet |
| title_full_unstemmed | Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet |
| title_short | Formability Assessment Based on Q-Value for Optimizing the Deep Drawing Process of Automotive Parts Made from Aluminum Alloys Sheet |
| title_sort | formability assessment based on q value for optimizing the deep drawing process of automotive parts made from aluminum alloys sheet |
| topic | formability deep drawing process optimization finite element simulation automotive part aluminum alloys sheet |
| url | https://www.mdpi.com/2075-4701/15/1/68 |
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