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INTEGRATION OF MATERIALS MODELING IN
BUSINESS DECISIONAPPLICATION TO COMPOSITE MATERIALS AND MANUFACTURING PROCESSES
H2020 COMPOSELECTOR PROJECT. Salim BelouettarEuroNanoForum 2017. Valetta, Malta
Decision(s) Making for a Tire
Image from MSC
3
Rubber composite
Material solution
Availability of material, cost
Database connectivity
ManufacturingCost, access to the technology, Complexity
Flexibility, Time, Variability
CustomerVolume, price, market segment, margins …
Decision(s) Making for a Tire
(Inter/multi)disciplinartiy
Computational
Tools
Digital DataExperimental
Inputs
Multiscale and Multiphysics
Modelling and Simulation
Uncertainty
Quantification and
Management
Verification and Validation ‐Experiment/Model coupling
Databases
management
Data sciences
and material
informatics
Decision‐based
multi-objective
systems design
Models for
manufacturing
Green Design and
Life Cycle
Engineering
Mat
eria
l &
Pro
cess
Model
ling F
arm
ework
Dat
a In
tegra
tion
Interoperability and Metadata
Multi disciplinary Design Optimisation, Uncertainty
Management and Model Selection
Busi
nes
s D
ecis
ion
Syst
em
PMCs Selection for
Aerospace and Transport
Markets
complex INTERACTIONS
INTERACTIONS BETWEEN MATERIALS MODELLING
STAKEHOLDERS IS OFTEN THWARTED BY
COMPLEXITY.
MODELLING
ACTIVITY
EXPERIMENTAL EVIDENCE
(USER CASE)
e.g. material, process,
phenomenon
PHYSICAL MODEL Equations describing the
behaviour of chosen entities
(equations for physical
quantities)
NUMERICAL SOLVER
Methods and software for
the solution of
the PE+MR.
POST-PROCESSING
Translation of the results in
a more convenient human-
understandable format.
Need of Common Language …
MODELLING
SOFTWARE PROVIDERS
EXPERIMEN-
TALISTS
ACADEMIA
INDUSTRIAL
USERS
SOFTWARE
DEVELOPPERS
MATHEMATICIANS
MODA
Need of a Paradigm Shift: Decision should be
objective as possible and less/not subjective
increase the fraction of critical decisions
informed by modeling and simulation
human
interaction
Simulation
decision
making
databases
MODELLING as a node of the glabal BUSINESS
WORKFLOW Chain
Decision require workflows involving different types of models and their coupling
and linking. MODA- EMMC (www.emmc.info)
What is needed
Decision is typically undertaken in the context of product
development/enhancement – coupling with manufacturing is natural.
Need to optimize concurrently materials and process contextually with the
effective use of materials models at different scales in the selection procedure.
Need for managing uncertainty and its propagation through model/experiment
and business chains.
Need for interoperability standards
Workflows involving different types of models and
their coupling and linking. MODA- EMMC
Reinforcement particles, filers,
fibers
Matrix
Meso-Micro Scale Characterisation, design and elaboration
Molecular scales Characterisation, design and
elaboration
1m – 100µm
Representative service
conditions
0.1µm – 10nm
Interface behaviour and
nano-reinforcement
100µm – 10µm
Microstructure
complexity
10µm – 0.1µm
Phase morphologies
Macroscale Characterization
and design
Interface/interphase
AB INITIO
MOLECULAR
DYNAMICS
COARSE
GRAINED
CONTINUUM
MODELS
Modeling Data (MODA)
Da
ta a
cquisitio
n
Da
ta C
om
pre
ssio
n
Coupling with manufacturing Process
Process
Control
Quality
Control
Optimisation
Process
Control
Quality
Control
Decision making
Optimisation
Manufacturing Decision making
Productivity
Complexity
Quality Robustness
Variables « Machine »
Variables «Process»
Quality
Creteria
Analogy with the Maslow pyramid
Need to optimize concurrently materials,
process and Business (MDO)MULTISCAL&M
ULTIPHISCAL
COMPOSITEM
ATERAILSYSTEM
GREENDESIGNANDLCE
COMPUTATION
Computedprototype
MaterialProper es
DATADRIVENSIMULATION
Manufacturing Tes ng
OPTIMISATION
ERRORESTIM
ATION
SENSITIVITY
Experimentalprototype
MaterialProper es
Manufacturing Tes ng
Valida on Valida on
Managing uncertainty and its propagation through
model/experiment and business chains.
DigimatM
F,MX
COMPOLAB
DIGIMATFE
COMPOLAB&
DIGIMATCAE
PAM-FORM
,
PAM-RTM
,PAM
DISTORTIONDigimatM
F,MX
M3
M3
MUL2
Minimum
Uncertainty
Parameter
Uncertainty
Model
Uncertainty
Unce
rta
inty
Complexity
Incertainties are the key drivers of model
adaptivity
Need for interoperability standards
The success of such integration
heavily relies on the openness of
application interfaces, the
maturity of various software tools.
Presentation of my colleague
Adham Hashibon
Mate
rial
& P
rocess
Mo
dell
ing F
arm
ew
ork
Data
In
tegra
tion
Interoperability and Metadata
Multi disciplinary Design Optimisation, Uncertainty
Management and Model Selection
Bu
sin
ess
Decis
ion
Sy
stem
PMCs Selection for
Aerospace and Transport
Markets
H020 Composelector Concept
DEC
ISIO
N S
UP
PO
RT A
PP
S
LCE, Li
ght
Weig
hting
, V
isua
liza
tion C
ost
ing
,
Res
Sub
s A
ssess
ment. e
tc…
MATERIAL WORKFLOW FRAMEWORK
DigimatM
F,MX
COMPOLAB
DIGIMATFE
COMPOLAB&
DIGIMATCAE
PAM-FORM
,
PAM-RTM
,PAM
DISTORTIONDigimatM
F,MX
M3
M3
MUL2
Reconstruction
Shape,
Orientation,
Distribution
ijK
Analysis and
Design
AIRBUS: Airplane frame
Application of the BDSS for Material and Process
Selection of fuselage thermoplastic frame
Composite materials complexity19
Structurecentric(sizing)
Materialcentric(sizing)
ManufacturingProcesscentric(CAM,CAE,CFD)
Designcentric(CAD)
micro-mesolevels Macrolevel
Couponlevel-plyproper es
characteriza onMeso-macro
Materialselec onmicro-mesoFibre/resine/
inteface
Manufacturingprocesstes ng
(physicalandnumerical)PermeabilityFlow,defects
micro-macroapproach
ElementlevelCharacterisa on
Numerical/Exp
ComponentLevel
Characteriza onNumerical/Exp.
Assembliestes ng
Numerical/Exp
FullpartlevelPhysicalandnumericaltes ngs
ManufacturingProcess• Resinflow(CFD)• Curing(CAE)• Thermoforming(CAE)• Fiberplacement(CAD/
CAE)• Op misa onofprocess.
ComponentLevelDraping
Assemblies Fullpartlevel
Op misa onoffib
e
rplacement(e.g.stacking
sequence)ordesign(shape,topology)
Conceptualdesign-rapidsizing
Preliminarydesign
Detaileddesign:nonlinearFEAandop misa on Valida on
Composite materials complexity20
Structurecentric(sizing)
Materialcentric(sizing)
ManufacturingProcesscentric(CAM,CAE,CFD)
Designcentric(CAD)
micro-mesolevels Macrolevel
Couponlevel-plyproper es
characteriza onMeso-macro
Materialselec onmicro-mesoFibre/resine/
inteface
Manufacturingprocesstes ng
(physicalandnumerical)PermeabilityFlow,defects
micro-macroapproach
ElementlevelCharacterisa on
Numerical/Exp
ComponentLevel
Characteriza onNumerical/Exp.
Assembliestes ng
Numerical/Exp
FullpartlevelPhysicalandnumericaltes ngs
ManufacturingProcess• Resinflow(CFD)• Curing(CAE)• Thermoforming(CAE)• Fiberplacement(CAD/
CAE)• Op misa onofprocess.
ComponentLevelDraping
Assemblies Fullpartlevel
Op misa onoffib
e
rplacement(e.g.stacking
sequence)ordesign(shape,topology)
Conceptualdesign-rapidsizing
Preliminarydesign
Detaileddesign:nonlinearFEAandop misa on Valida on
KPIs Definition for Material Selection
Composite Leaf Spring
Simulation Workflow
Modeling UD
Dry Fibre
Preforming
Characteristics
Modeling
Preforming
(Modeling) TP
Binder
Characteristics
Binder
placement
Micromechanics RVE
(Leuven Software?/Digimat)
PAM-FORM
Initial Preforming
Tool Design,
Molding Conditions
• UD Fibre
Bundel
Mechanics
• Permeability
Model
• Binder
Rheology
Model
• Pre-form UD-Fibre
distribution
• Pre-form Permeability
Modeling HP-
RTM
Infusion**
Initial HP-RTM
Tool Design,
Molding Conditions,
Resin Rheo-Kinetics*
* RheoKinetic Modeling? or from tests?
** Incl cure development during infusion
*** PAM-RTM?
• Infusion pattern
• Pressures
• Infusion Time
• Fibre movement***
PAM-RTM
• Material Usage
• Weight
• Cycle Time
• Tooling Cost
• Capital
• Energy Cost
• # of operators
Modeling HP-
RTM Curing /
Demoulding
PAM-RTM
• Cure Time
• Cure Development
• Residual Stresses
• Part geometry after
demoulding/
Shrinkage
Mechanical
Modeling
Local Part
DIGIMAT
• Local non-linear
Stiffness
• Local Strength
• Temperature
Dependency
Cost, Value,
Risk Modeling
Cost &NPV Models
Leaf Spring
Stiffness/
Strength
Modeling
• Stiffness Response vs
design target
• Strength safety margin
• Temperature Dependency
ESI / MSCMolding Conditions,
Resin Kinetics*
Loads, Boundary Conditions
- Weight requirements & weight reduction value (assume 5 Euro/kg)
- Production Scenarios (target, low, high volume scenario), lifetime
- Production cost target (Capital, Running Costs).
- Manufacturing targets: cycle time options (tooling)
- Material cost scenarios
KPIs
LINKS ..
Important links:
EMMC: The European Materials Modelling Council (http://emmc.info)
MODA: Modeling Data:
Short version of RoMM VI. https://bookshop.europa.eu/en/what-makes-a- material-function--pbKI0417104/. Edited by Anne F de Baas
Vocabulary, classification and metadata for materials modelling (130 FP7 and H2020 projects)
RoMM
VI
Review of Materials Modelling
(RoMM version V and VI)
http://ec.europa.eu/research/industrial_technologies/modelling-materials_en.html
Acknowledgements ..
The funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 721105 is acknowledged.
The author acknowledge the contribution of all the COMPOSELECTOR project partners.
Thank you !