CAOT Computer Aided Optimization Tool

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CAOTComputer Aided Optimization Tool

• Institute of Metal Forming

Dr. rer. nat. Martin Franzke Innovationsforum
Florianópolis 2008
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Outline

• Computer Aided Optimization (CAO)
• Introduction of CAOT (Computer Aided
  Optimization Tool)
• Optimization of a drawing process
• Optimization of a process chain
• Summary

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Computer Aided Optimization (CAO)
job
new input data
process model
simulation program
execution
evaluation
variation
results
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Evaluation of target function value
simulation
results
res1
res2
resm
penalty terms
pen1(res1)
pen2(res2)
penm(resm)
w1 pen1(res1)
w2 pen2(res2)
wm penm(resm)
weighting
target functionvalue

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whereas penk(resk) desired value (resk)
actual value (resk)
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Evaluation of target function value example
simulation
results
penalty terms
weighting
target function value

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Evaluation of target function value
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Monte-Carlo Method
2
0
0
1
1
4
2
3
4
3
1
1
2
3
3
4
5
6
4
1
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Hill Climbing Method
2
0
0
1
1
4
2
3
success
4
3
failure
1
1
2
3
3
4
5
6
4
1
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CAOT user interface

• No restriction for the number of variation
  parameters
• Not restricted on linear FEM models
• Modular system architecture
• Direct coupling of any simulation program
• Combination of several simulation processes in
  one optimization operation
• Reduction of optimization time by parallel
  system organization

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Parallel architecture of CAOT
slave(i) (simulation)
master (optimization)
automatic variation
new parameters
input data
no
yes
exit check
result data queue (FIFO)
simulation result data
simulation result data
slave(n)
slave(2)
slave(1)
optimization result
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Optimization of a drawing process
Range/Initial
Design parameter
1-6 / 3 4-10 / 6 3-30 / 15
Length of parallel lz Angle of
inclination of drawing hole a Transition radius
R
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Optimization of a drawing process
966,68 N/mm2
- 613,22 N/mm2
LARSTRAN/Shape
Optimization objective Decrease the tensile
stress near the surface without decreasing the
compressive strain in the middle of the wire
essential by variation of the design
parameters Restrictions Range for tensile stress
0..800 N/mm2, range for compressive stress
-800..-600 N/mm2
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Optimization of a drawing process
optimized
CAOTLARSTRAN/Shape
783,10 N/mm2
966,68 N/mm2
- 713,66 N/mm2
- 613,22 N/mm2
initial configuration
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Optimization of a process chain
Initial blank
flexible rolling
cutting
HBU
cutting
loading
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Optimization of a process chain
Optimization objectiveMinimal bending under
loading! RestrictionWeight less than 100!

blank with constant thickness

Ta
i
lor Rolled Blank

sheet thickness

1,4

0,8

1,2 1,4

1,2 1,4

2,55 (100)
10,23 (400)
1,48 (58)
bending



2,81 (110)


weight

100

57

80

95


The maximum bending of the optimized component is
58 and the weight is 95 compared to the initial
configuration!
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Summary

• Automatic optimization of metal forming
  processes is applicable
• The basic condition is to use a process model
  which covers the real process exactly
• The computing time is still high in the case of
  using 3D-FEM
• In the case of elementary or empirical models
  the introduced optimization system can deliver
  very fast significant process improvement