Abstract
This paper suggests a methodology based on a neuroevolutionary approach to optimize the use of material in blow molding applications. This approach aims at determining the optimal thickness distribution for a certain blow molded product as a function of its geometry. Multiobjective search is performed by neuroevolution to reflect the conflicting nature of the design problem and to capture some possible trade-offs. During the search, each design alternative is evaluated through a finite element analysis. The coordinates of the mesh elements are the inputs to an artificial neural network whose output determines the thickness for the corresponding location. The proposed approach is applied to the design of an industrial bottle. The results reveal the validity and usefulness of the proposed technique, which was able to distribute the material along the most critical regions to obtain adequate mechanical properties. The approach is general and can be applied to products with different geometries.
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