Sheet Metal Assembly Simulation with Springback Compensation
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Solution Overview
Problem
Existing methods for simulating and optimizing sheet metal forming and assembly processes are computationally expensive and inefficient due to the need for repeated simulations to achieve desired geometries and internal states.
Innovation Solution
A method that iteratively adjusts the compensated sprung back part geometry and tool parameters to match the reference geometry, reducing the need for multiple forming simulations by using a single forming simulation to determine the sprung back part simulation model, followed by an assembly simulation loop to optimize the assembly process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If repeated forming simulations are performed to achieve desired geometry, then manufacturing precision is improved, but computational effort and time increase significantly
Solution Approach 1:
The method performs a preliminary forming simulation to generate an initial sprung back part simulation model before the assembly simulation. This preliminary model captures the springback effects and geometry deviations, which are then used to pre-adjust the compensated sprung back part geometry. By performing this action in advance, the method avoids the need for repeated forming simulations during the assembly optimization process, thereby reducing computational effort while maintaining geometry accuracy.
Solution Approach 2:
The simulation process is segmented into distinct stages: (1) forming simulation to generate sprung back part model, (2) assembly simulation using the sprung back part model, and (3) iterative adjustment of compensated geometry based on assembly results. This segmentation allows each stage to be optimized independently, with the forming simulation performed only once rather than repeatedly, thus reducing total simulation time while maintaining precision.
2Manufacturing precision
If multiple forming simulations are executed to optimize the process, then manufacturing precision is improved, but computational complexity increases
Solution Approach 1:
The sprung back part simulation model serves as an intermediary between the forming process and the assembly process. Instead of performing multiple full forming simulations, the method creates this intermediate model that captures the essential springback effects and geometry characteristics. This intermediary model is then used in the assembly simulation and iterative optimization process, simplifying the overall computational complexity while maintaining the ability to achieve precise process optimization.
3Productivity
If the assembly simulation uses the sprung back part simulation model, then computational efficiency is improved, but the accuracy of internal state computation may be compromised
Solution Approach 1:
The method adjusts the compensated sprung back part geometry parameters iteratively based on the results of the assembly simulation. By modifying the geometry parameters to compensate for springback effects and assembly-induced deformations, the method maintains accuracy in the final part geometry and internal states while using the more efficient sprung back part simulation model as the basis for the assembly simulation.
Data Source
AI summary
A design method, for processes forming and assembling parts, begins by simulating a forming process (2) to generate a sprung back part simulation model (30) that corresponds to a reference geometry (10) of the formed part (3). Next, an assembly simulation (40) uses this sprung back model (30) to create an assembled sprung back part simulated model (50). If the geometry of this assembled model (50) does not match the reference geometry (10), a compensated sprung back part geometry (60) is iteratively adapted, and the assembly simulation (40) is repeated until the assembled model (50) aligns with the reference geometry (10). The final optimized geometry (60) can then be used to design and manufacture both the parts and the tools needed for forming them. The method avoids an iterative repetition of forming simulations, which allows a user interacting with the process to work in a more efficient manner.