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 1271-1286.

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

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)

Simulation

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

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, (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

638,0163,0 s

ZZ pRpRFD 204,0024,0157,016,000284,0259,0

ZZZ pRRppRRa 15,4145,017,0319,0478,00932,02,1

ZZ ppRFMD 72,347,125,30466,047,6

•Thickness:

•Flatness deviation:

•Surface roughness:

•Form deviation:

Experimental study: resultsStep size - form deviation relationship

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

0 0,2 0,4 0,6 0,8 1 1,2

Step size, pz (mm)

Fo

rm d

ev

iati

on

(m

m)

Form deviation (R=3;Alfa=30)

Form deviation(R=10; Alfa=30)

Form deviation (R=3;Alfa=60)

Form deviation(R=10; Alfa=60)

Experimental study: resultsDraft angle - part thickness relationship

0,400

0,450

0,500

0,550

0,600

0,650

0,700

0,750

0,800

0,850

0,900

25 30 35 40 45 50 55 60 65

Draft angle

Pa

rt t

hic

kn

es

s (

mm

)

Thickness (R=3;pz=0,1)

Thickness (R=10;pz=0,1)

Thickness (R=3;pz=1)

Thickness (R=10;pz=1)

Sine law

Process Optimization

satisfying constraints: min),,,,( fRpLTT z

,),,( FDpRFD z ,),,( aza RpRR

,),,( FMDpRFMD z ,maxmin

,maxmin RRR ,maxmin zzz ppp

maxmin fff

(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

Thank You!

Questions?

Info: meelisp@staff.ttu.ee