Optimization of springback in L-bending process using a coupled Abaqus/Python algorithm
Sheet metal L-bending processes are widely used for mass production. The design of L-bending processes is connected with time-consuming and costly experiments. Therefore, the finite element simulation of the process could be a helpful tool for the designer and quality assurance of the products. In L...
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| Published in | International journal of advanced manufacturing technology Vol. 44; no. 1-2; pp. 61 - 67 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer-Verlag
01.09.2009
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0268-3768 1433-3015 |
| DOI | 10.1007/s00170-008-1819-4 |
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| Summary: | Sheet metal L-bending processes are widely used for mass production. The design of L-bending processes is connected with time-consuming and costly experiments. Therefore, the finite element simulation of the process could be a helpful tool for the designer and quality assurance of the products. In L-bending process, springback is an important phenomenon, and its accurate prediction is important to control the final shape of the workpiece when the punch is removed. In this study, an optimization algorithm using Gauss–Newton method was developed by coupling the Abaqus/standard code and Python script which is an object-oriented language. For a given bending process problem, the proposed algorithm allows for the optimization of a set of material and/or process factors in order to minimize the workpiece springback. Python scripts allow the direct parameterization of the design variables to be optimized in the finite element input file, and hence an easy use of the procedure within the framework of industrial application. An example is presented in order to optimize three process parameters, namely, die corner radius, punch–die clearance, and the blank holder force. The results demonstrate the reliability of the proposed approach and the fast convergence of the algorithm. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0268-3768 1433-3015 |
| DOI: | 10.1007/s00170-008-1819-4 |