Pre-Stamped Workpiece Shape Estimation for Deep Draw Forming
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Solution Overview
Problem
Existing methods for numerically estimating the initial shape of a workpiece in deep draw metal stamping, particularly for products with complex geometries, are inadequate, leading to inefficiencies in manufacturing.
Innovation Solution
A system and method that utilize a 3-D mesh model with triangular shell finite elements, calculate averaged nodal curvatures, and iteratively update a 2-D mesh model with internal nodal forces to estimate the pre-stamped shape of a workpiece, ensuring accurate representation and convergence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to estimate the initial shape of a workpiece for deep draw metal stamping, then the manufacturing process can proceed with basic tools, but the accuracy of predicting complex geometry workpiece shapes is insufficient
Solution Approach 1:
The workpiece geometry is segmented into a mesh model comprising multiple nodes and elements. The complex 3D geometry is divided into manageable triangular shell finite elements, allowing precise local analysis of curvature and shape characteristics while maintaining overall geometric accuracy.
Solution Approach 2:
The patent replaces traditional mechanical measurement and estimation methods with a numerical computation system. By using computational algorithms to calculate nodal curvatures and iteratively solve for the pre-stamped shape, the system achieves high measurement precision without requiring complex physical measurement devices.
2Manufacturing precision
If a detailed 3-D mesh model with many nodes and elements is used to represent complex geometry, then the precision of the pre-stamped shape estimation is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary calculations of nodal curvatures and establishes the mesh model structure before the main iterative estimation process. By pre-computing curvature values at each node based on the 3D geometry, the system prepares essential data that accelerates the subsequent iterative solving process.
Solution Approach 2:
The patent uses triangular shell finite elements which provide sufficient precision for complex geometry estimation without requiring an excessively dense mesh. The triangular element formulation offers an optimal balance between model detail and computational efficiency, achieving accurate shape prediction with reasonable processing time.
3Ease of operation
If the 3-D mesh model is unfolded to a 2-D mesh model to represent the pre-stamped shape, then the visualization and manufacturing guidance is improved, but the accuracy of representing the original 3-D geometry may be lost
Solution Approach 1:
The patent creates a 2-D copy of the 3-D mesh model by unfolding it onto a plane. This 2-D representation serves as a manufacturing guide that preserves the essential shape information while being easier to visualize and work with. The nodal coordinates in the 2-D model are calculated to maintain geometric fidelity to the original 3-D structure.
Data Source
AI summary
A 3-D mesh model represents 3-D geometry of a product/part manufactured with deep draw metal forming process. The 3-D model contains nodes connected by shell finite elements. 3-D model is modified by converting each quadrilateral shell finite element to triangular shell finite elements. Respective averaged nodal curvatures of all nodes of the 3-D model is calculated based on the 3-D geometry. A 2-D mesh model is created by unfolding the 3-D model to a plane while maintaining all corresponding triangular shell finite elements between the 2-D and the 3-D models as similar triangles. An estimated pre-stamped shape of a workpiece used for manufacturing the product/part is obtained by iteratively updating the 2-D model with a set of internal nodal forces with respect to the 3-D model and with a set of nodal force adjustments based on the respective averaged nodal curvatures.