Successful Springback Compensation Retooled

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Sheet metal forming simulation to identify not only feasibility, but process capability. Springback compensation without a repeatable process is folly.

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  • During simulation traditionally we run like tryout—tuning the die we design and subsequently build to run on a discrete set of inputs which are in themselves not repeatable. We need to treat simulation and tryout with a production mindset. Ensuring that the tools we design are capable of absorbing the variation that life will throw at it.
  • Successful Springback Compensation Retooled

    1. 1. SUCCESSFUL Springback Compensation Eric Kam AutoForm Engineering
    2. 2. SUCCESSFUL springback compensation is more than just… <ul><li>Having springback predictions </li></ul><ul><li>Generating compensation “map” </li></ul><ul><li>Exporting compensated tool data </li></ul>Version 1.1
    3. 3. SUCCESSFUL springback compensation IS: <ul><li>Springback that repeats </li></ul><ul><li>HERE today with AutoForm </li></ul>Version 1.1
    4. 4. Compensation is easy… Version 1.1 <ul><li>Observe deviation </li></ul><ul><li>Adjust by the opposite </li></ul>
    5. 5. Compensation is easy… Version 1.1 <ul><li>Observe deviation </li></ul><ul><li>Adjust by the opposite </li></ul>
    6. 6. But what if conditions don’t repeat… Version 1.1 <ul><li>Observe deviation </li></ul><ul><li>Adjust by the opposite </li></ul><ul><li>Hope for the best </li></ul>
    7. 7. Springback reliability <ul><li>How good is it? </li></ul><ul><li>VERY …. </li></ul><ul><li>All things held equal……. </li></ul>Version 1.1
    8. 8. Unfortunately the world does not “hold all things equal” Version 1.1
    9. 9. Everything changes <ul><li>Most simulations we do today assume constant: </li></ul><ul><ul><li>Blank (material) </li></ul></ul><ul><ul><li>Binder/Pad pressure </li></ul></ul><ul><ul><li>Friction (Lube, coating, condition) </li></ul></ul><ul><ul><li>Tool setup </li></ul></ul>Version 1.1 Material Range good bad X X X
    10. 10. 120, 200, 300 simulations ???? <ul><li>Simulations can be sent to “slave” solvers </li></ul><ul><li>Inputs are varied </li></ul><ul><li>Each simulation represents another “reality” </li></ul><ul><li>Results are returned to master </li></ul><ul><li>Lather, rinse, repeat </li></ul>Version 1.1
    11. 11. The result <ul><li>More data than we collect during buyoff </li></ul><ul><ul><li>What changes? </li></ul></ul><ul><ul><li>By how much? </li></ul></ul><ul><ul><li>What is influential? </li></ul></ul><ul><ul><li>To what degree? </li></ul></ul>Version 1.1 Input B Response 1 Input A Response 1
    12. 12. Springback responses “in control” <ul><li>Controlled process? </li></ul><ul><li>Yes </li></ul><ul><ul><li>Compensate to this design </li></ul></ul><ul><li>NO </li></ul><ul><ul><li>Find better process! </li></ul></ul>Version 1.1 Distance from net Noise Variable
    13. 13. Pre-compensation robustness with AutoForm <ul><li>Use your cluster effectively to: </li></ul><ul><li>See springback variation </li></ul><ul><li>Preview REALITY </li></ul><ul><li>Know if compensation is plausible </li></ul><ul><li>Compensate for variable conditions (real life) </li></ul><ul><li>Not just make ONE answer faster…. </li></ul>Version 1.1

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