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

EXAMPLES … USERS CASES

H2020 BNMP. www.composelector.netDeMEASS VIII

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 !