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 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

Incremental Forming process 1. Tool moves step downwards; 2. Draws profile on horizontal plane; 3. Step downwards; 4. 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

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

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

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

Incremental Forming process Features: Simple tools Universal equipment Products with complicated geometry Long NC controlled toolpath No need for high cost tooling Short preparation period High flexibility

Phases of the simulation process 1. Building CAD models of product, blank and tool (SolidEdge) 2. Preparing toolpaths (SurfCAM) 3. Preparing Finite Element model (ANSYS) 4. Solving model (ANSYS, LS-DYNA) 5. Post processing (ANSYS) 6. Validation CAD CAM FEA

Simulation Model Loading Tool movement control Material models Element types

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

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

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

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)

Finite Element model validation Physical tests were made Part was scanned and compared with FEA results Maximum positive normal deviation: 0,74 mm; maximum negative normal deviation was measured: -0,80 mm

Comparison of results Ansys (8- noded shell elements): LS-Dyna (Fully integrated shell elements): LS-Dyna (Belytschko- Tsay shell elements):

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

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

Experimental study: results Thickness: Flatness deviation: Surface roughness: Form deviation:

Experimental study: results

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

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

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