weld distortion optimisation using hyperstudy
DESCRIPTION
Distortion induced in parts due to the cooling of welds complicates automated manufacturing lines in the automotive industry. The resulting deformation leads to additional investment such as end of line machining to correct affected assemblies. Utilising optimisation software a welding pattern can be found which retains the intended performance of a part while reducing the distortion induced from welding. Weld locations may be optimised alongside welding sequence to allow process requirements to be considered within the early design stage. This leads to high performance, low distortion assemblies which can ultimately be manufactured at the lowest possible cost.TRANSCRIPT
25/06/14
European Altair Technology Conference
Munich 2014
Weld Distortion Optimisation
©2012 GESTAMP 1
Altair Technology Conference 2014– Weld Distortion Optimisation
• Zidane Tahir : Design Analyst – Gestamp Chassis
• Inverse Identification in weld Distortion using
HyperStudy
• Weld Distortion Optimisation using HyperStudy
Introduction
NORTH AMERICA
8 Production Plants
SOUTH AMERICA
10 Production Plants
EUROPE
60 Production Plants
RUSSIA
3 Production Plants
ASIA
15 Production Plants
A GLOBAL COMPANY
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Altair Technology Conference 2014– Weld Distortion Optimisation
Gestamp Chassis
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Altair Technology Conference 2014– Weld Distortion Optimisation
Gestamp Chassis
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld Distortion is the physical warping of a part, induced by the heating and
subsequent cooling caused by the welding process.
TSB Project No. TP/TP/DSM/6/1/16131 – 2010 Roger O’Brien
Macro section of butt weld, (shown in Figure 6.1.17) in 2.5mm thick Xf350
material, weld produced using LSND process
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld Distortion
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Altair Technology Conference 2014– Weld Distortion Optimisation
WELD DISTORTION ANALYSIS AND CORRELATION
Inverse Identification using HyperStudy
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld Distortion Analysis – Modelling Method and inverse identification
𝐷𝑖𝑠𝑡 = 𝑙0𝛼1∆𝑇 𝑊𝑒𝑙𝑑_𝑠𝑒𝑡 + 𝑙0𝛼1𝜷∆𝑇 𝑎𝑑𝑗𝑎𝑐𝑒𝑛𝑡_𝑠𝑒𝑡
Weld_set
Adjacent_set
β is the temperature diffusion factor in adjacent elements affected by heating
β is identified using inverse method implemented in HyperStudy
𝐹𝑖𝑛𝑑 𝛽
min 1
2𝐷𝑖𝑠𝑡𝐹𝐸𝐴 − 𝐷𝑖𝑠𝑡𝑇𝐸𝑆𝑇
12
The advantage of this
method is to avoid thermal
transient time consuming
calculation
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld Distortion Analysis – Correlation
Optimum
β= 0.57
Dist = 8.08 mm
Sequential Quadratic Programming has
been used successfully to obtain the
optimum
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Altair Technology Conference 2014– Weld Distortion Optimisation
“REDUCE THE DISTORTION OF A PART WITHOUT ADDING COST OR
SIGNIFICANTLY ALTERING PERFORMANCE.”
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld Optimisation (Stiffness/Durability)
Fully Welded
Remove weld causing significant
distortion
Weld Removal Optimisation
Weld Sequence Optimisation
Manage distortion through additional process and design
features
Reduce weld and meet structural constraints
(hope for reduced distortion)
Arbitrary removal based on reducing
magnitude of distortion
Optimum solution Combine removal
and sequence
First true optimisation based on distortion
Fine tuning of sequence to further
reduce distortion
Weld Distortion Optimisation Evolution
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Altair Technology Conference 2014– Weld Distortion Optimisation
• Front Subframe tower case study
• Towers susceptible to distortion due
to their geometry
• Tolerance regained by having “float”
designed into the components
• Objective – reduce distortion
without changing geometry.
Case Study
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Altair Technology Conference 2014– Weld Distortion Optimisation
WELD REMOVAL OPTMISATION
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• Topology Optimisation Identified critical
welds for stiffness/durability
performance (Optistruct).
• Weld lengths are split to 30mm
sections and given generic group
names (Weld01, Weld02, etc) using
automated scripting in HyperMesh
Weld Removal Optimisation
• For this study we have 30 weld sections
• 10 critical sections identified by
Optistruct
• 20 design variables
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Key Objective Values
Extraction Job Queue
Create ABAQUS Deck
Generate Welding List
(ON/OFF)
Generate Deck Geometry
Optimisation Algorithm
Material + Base Geometry etc.
Full Weld Model
Run ABAQUS
Deck
Results Cluster
Initial Conditions
(ALL WELDS ON) PROCESS IS
GENERIC
Hyperstudy
SciLab
Optimal Solution!
Weld Removal Optimisation – Process Flow
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Altair Technology Conference 2014– Weld Distortion Optimisation
Case Study
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld removal optimisation – Major iteration 1
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Weld removal optimisation – Major iteration 2
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld removal optimisation – Major iteration 3
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Weld removal optimisation – Major iteration 4
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Weld removal optimisation – Major iteration 5
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3,00E-01
4,00E-01
5,00E-01
6,00E-01
7,00E-01
8,00E-01
9,00E-01
1,00E+00
0,036 0,0362 0,0364 0,0366 0,0368 0,037
Ind
uc
ed
Dis
tort
ion
(m
m)
Tower Displacement Under Loading (mmkN-1)
Tower Case Study Pareto Frontier
Design iterations Pareto front
Pareto Frontier
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WELD SEQUENCE
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Altair Technology Conference 2014– Weld Distortion Optimisation
Key Objective Values
Extraction
Job Queue
Create ABAQUS Deck
Utilising *modelchange
Generate Weld Sequence Discrete
Variables
Generate Deck Geometry
Optimisation Algorithm
Material + Base Geometry etc.
Full Weld Model
Run ABAQUS
Deck
Results
Cluster
PROCESS IS GENERIC
Hyperstudy SciLab
Optimal Solution!
Generate Welding
Sequence
Initial Conditions
(PROCESS ORDER)
Weld Sequence Optimisation – Process Flow
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld sequence optimisation – Major iteration 1
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld sequence optimisation – Major iteration 2
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld sequence optimisation – Major iteration 3
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld sequence optimisation – Major iteration 4
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Altair Technology Conference 2014– Weld Distortion Optimisation
Weld sequence optimisation – Major iteration 5
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Weld sequence optimisation – Major iteration 6
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OPTIMAL RESULTS
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ORIGINAL DESIGN
OPTIMISED DESIGN
Case Study- Results
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Original
design
Weld Removal
Optimised design
Weld Sequence
Optimised design
Value Reduction Value Reduction
Weld distortion (mm) objective 1.24 0.54 56% 0.09 93%
Stiffness (MNmm-1) constraint
target (27.4) 30.1 27.4 0 27.4 0
Max Stress (MPa) Constraint
target (280MPa) 280 234 16% 234 16%
Weld length (mm) output 870 650 25% 650 25%
Total Robot head
movement (mm) output 1290 1140 12% 2490 +93%
Case Study- Results
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CONCLUSIONS
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• HyperStudy can be used to effectively reduce weld distortion.
• Sequence algorithm generation to be enhanced to avoid
repeatable sequences
• Gradient based optimisation techniques apply well to weld
removal problems however their applicability in weld sequencing
problems is limited where global search algorithms are more
effective.
• The platform developed is generic and applicable to any weld
distortion project without any adaptation.
• HyperStudy allows a flexible, multi-platform approach for
optimisation management and is a good tool for solving this
optimisation problem.
Conclusions
©2012 GESTAMP AUTOMOCIÓN