Automated shape optimization improves polymer extrusion die design
Efficient Geometry Representation Strategies for the Shape Optimization of Profile Extrusion Dies
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Summary
Designing the shapes of tools that form plastic into profiles is really hard because the plastic flow is complicated. The authors created a computer method that automatically improves these shapes by calculating how small changes affect the flow. They use a way to represent shapes that avoids tricky mesh problems, making the process more reliable and efficient. Their approach was tested on realistic 3D designs and showed better flow performance, suggesting this could reduce the need for manual trial-and-error in manufacturing.
What this means in practice
- •For manufacturing engineers: Automatically optimize extrusion die shapes to improve polymer flow uniformity and reduce trial-and-error design cycles.
- •For computer-aided design teams: Integrate adjoint-based shape optimization methods into CAD tools for more accurate and efficient die geometry updates.
Authors
Jana Sasse, Maximilian Esser, Markus Mügge, Stefan Turek
Abstract
The design of profile extrusion dies remains a challenging task due to the complex rheological behavior of polymer melts and the geometric intricacies of flow channels. Traditional manual optimization approaches, which rely heavily on human experience, are inefficient and often employ unvalidated heuristics. To address these challenges, we present a deterministic and explainable framework for automatic die design based on adjoint-based shape optimization. This approach enables the computation of sensitivities that directly indicate beneficial modifications to the flow channel geometry. A major difficulty in such optimization processes lies in generating boundary-conforming meshes that evolve consistently with changing geometries. To overcome this issue, we employ non-boundary conforming geometry representation methods that eliminate the need for an explicit surface representation along physical boundaries. A dedicated reconstruction technique is developed to recover accurate sensitivity information at the virtual interface between fluid and solid regions. The proposed algorithm is demonstrated on 3D geometries with varying complexity, including realistic extrusion die flow channels. Several objective functionals relevant to industrial applications, such as flow balance at the outflow, are considered. The results highlight significant improvements in performance metrics while maintaining numerical robustness. This work showcases the potential of adjoint-based techniques for automated die design in a domain still largely governed by manual trial-and-error procedures, establishing a foundation for data-efficient, sustainable manufacturing workflows using computational rheology.