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Modelling and optimal design of sheet metal RP&M processes

Modelling and optimal design of sheet metal RP&M processes. Meelis Pohlak Rein Küttner Jüri Majak. Tallinn University of Technology 2004. Outline. Objective What is Incremental Forming Simulation of the process Experimental study Optimization model. Objectives.

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Modelling and optimal design of sheet metal RP&M processes

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  1. Modelling and optimal design of sheet metal RP&M processes Meelis Pohlak Rein Küttner Jüri Majak Tallinn University of Technology 2004

  2. Outline • Objective • What is Incremental Forming • Simulation of the process • Experimental study • Optimization model

  3. Objectives • To study the mechanics of the process • To analyze the limitations of incremental forming process • To study the influence of process and product parameters to the properties of products • To create models for process optimization

  4. Incremental Forming process • Tool moves step downwards; • Draws profile on horizontal plane; • Step downwards; • next profile, etc Kim T. J., Yang D. Y., Improvement of formability for the incremental sheet metal forming process. International Journal of Mechanical Sciences 42 (2000), pp 1271-1286.

  5. Two types of Incremental Forming: 1. With support 2. Without support

  6. Some additional types of Incremental Forming: 2. Forming using soft plastic support material 1. Multistage or multiaxis forming

  7. Limitations of the process • Problems with steep walls • Accuracy issues • Better surface quality – longer processing time

  8. CAD CAM FEA Phases of the simulation process • Building CAD models of product, blank and tool (SolidEdge) • Preparing toolpaths (SurfCAM) • Preparing Finite Element model (ANSYS) • Solving model (ANSYS, LS-DYNA) • Post processing (ANSYS) • Validation

  9. Simulation Model • Loading • Tool movement control • Material models • Element types

  10. Simulation Model • Loading • Tool movement control • Coordinates from CAM software • Several loadsteps • Material models • Element types

  11. Simulation Model • Loading • Tool movement control • Material models • Testing of material properties is essential • Multilinear isotropic strain hardening plasticity model was used • Element types

  12. Simulation Model • Loading • Tool movement control • Material models • Element types • 4 noded shell elements • 8 noded shell elements • Tool and support: rigid

  13. Process of simulation • Element size • 1 mm and 2,5 mm in separate cases • >2000 elements • Duration (CPU: 1,6 GHz Pentium 4) • More than 70 hours with 2,5 mm elements and 20 step-down cycles (ANSYS) • Similar model 26 hours with mass scaling (LS-DYNA)

  14. Simulation • Simulation provides data for optimization • Elements need to be smaller • Simulations are very resource intensive

  15. Experimental study • Variables: • Tool radius, R (Rmin= 3 mm; Rmax = 10 mm); • Step size, pz (pz min = 0,1 mm; pz max = 1 mm); • Wall draft angle, a (amin = 30º; amax = 60º). • Measured parameters: • Wall thickness; • Flatness deviation of non-horizontal walls; • Surface roughness on processed surfaces; • Total form deviation of part.

  16. Experimental study: results • Thickness: • Flatness deviation: • Surface roughness: • Form deviation:

  17. Experimental study: results

  18. Experimental study: results

  19. Process Optimization (Processing time) (Flatness deviation) (Surface roughness) (Form deviation) (Wall draft angle) (Tool radius) (Vertical step size) (Feed rate) satisfying constraints:

  20. Conclusion • Accuracy of the forming process has to be improved • In process modeling in addition to linear relationships also interactions of the parameters have to be considered • Our study creates the basis for using response surface methodology for process optimization

  21. Thank You! Questions? Info: meelisp@staff.ttu.ee

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