VTT For Industry

VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD
VTT – Technology for business

211/06/2015 2
 For Industry – Scenarios >>
 VTT ProperTune™ for integrated computational materials engineering >>
 Robotics at VTT >>
 Design for additive manufacturing: Topology optimization >>
 InnoLeap - Take an innovative leap to the future with VTT’s concept
design! >>
 Additive manufacturing at VTT - AM-liiketoiminta project >>
 New ecosystem at Hervanta Campus >>
Contents

For Industry - Scenarios

411/06/2015 4
For Industry scenario work
What will be future ways of doing
successful business at Finnish
manufacturing companies?
 Target year of scenarios 2025
 Special emphasis on SMEs
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511/06/2015 5
For Industry scenario work
Four potential future worlds for which scenarios
will be made
The future worlds characterized by key-word pairs
Local-global
Growth - scarcity
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Growth
Scarcity
Local Global
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Local - growth
Localized business within EU
Focus on European markets
Focus on innovations
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Global - growth
Strongly globalized business
with global value chains
Focus on customer needs
Highly specialized business
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Local - scarcity
Strong localization because
of risks related to global
value chains and business
Scarcity of raw materials and
skilled labour
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Global - scarcity
Global labour markets and
business
Focus on quality and
durable products
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Conclusions of scenario work
It will be possible for a manufacturing SME to make
successful business in each of the potential future world
BUT
business models for successful business will not be the
same in the different worlds.
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VTT ProperTune™ for
integrated computational
materials engineering

1311/06/2015 13
Methodological
approach -
multiscale
modeling
(“toolset”)
Multiscale modeling = Means of quantifying the material
structure and behavior critical for desired and tailored
performance. « BACK TO CONTENTS

141411/06/2015
The main application areas of VTT ProperTune are 1) modeling of
nano-microstructures and their properties at mesoscale:
 is a collection of software libraries, interfaces and
modeling packages and tools
 enables the rapid development and deployment of
modeling solutions
 is not a single software package, but rather a material
modeling toolset
…and 2) performance dominating mechanisms and processes
related to component operating environments or manufacturing
(or both):
VTT ProperTune™ is a computational modeling assisted
material design, tailoring and performance evaluation
methodology and software platform. It incorporates and
integrates a range of multiscale modeling methods and
techniques for materials related problems:
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1511/06/2015 15
Multiscale modeling and ICME
The primary function of VTT ProperTune™ is to enable the rapid development and deployment of novel
integrated computational materials engineering (ICME) solutions.
This will be carried out by way of exploiting multiscale modeling and material design approaches such as the
Process-Structure-Properties-Performance (PSPP) principle.
ICME =
Holistic modeling assisted design of
material, process and component
aspects from materials sciences and
engineering perspectives
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Principal arguments for multiscale modeling
and ICME TRADITIONAL
DESIGN
Sole reliance on “trial-and-error” in design of complex
material solutions is costly and time consuming, and hardly
yields optimal results.
Traditional material development from basic sciences to applied
sciences and to industry, from discovery to deployment ~15 - 35
years2.
STAGES OF
TECHNOLOGY
IMPLEMENTATION
TIMELINE1
1, “Materials Genome Initiative”, NIST-MGI
2, “ICME Impact on Technology Implementation”, US DoE « BACK TO CONTENTS

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Principal arguments for multiscale modeling
and ICME The core concept of ICME is to support a
systematic design approach and establish a
digital factory for design – including
experimental, modeling and digitalization
activities.
The arguments being put forth and benefits
being demonstrated are:
 ICME time-to-market of new material solutions >
2 times faster than traditional trial-and-error.
 Decrease the time required for component
deployment by a factor of 2-3.
 Return of investment by a factor of 3 to 9 across
industry sectors.
 Decreases in component costs due to the
improved design process.
 Enables improved and disruptive discovery of
novel designs and material solutions, leading to
improved products.
DESIGN APPLYING
ICME
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Case example: Tailoring of a
wear resistant composite
coating solution
Structure-Properties-Performance (SPP) problem of wear
resistance of a metal matrix composite microstructure ↔
the impact and tailoring of material microstructure to satisfy
and meet a specific component function.
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1911/06/2015 19
Case example: Tailoring of a wear resistant composite
coating solution
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Phenomena and physics
 deformation and strength, fracture, fatigue,
wear (adhesive, abrasive, erosive)
 high rate and nonlinear response, crystal
plasticity, multibody contact phenomena
 material defects, interfaces
 multiphysics (heat transfer,
electromagnetism, computational fluid
dynamics, granular and discrete flow,
reactivity and flow….)
 phase transformations, solidification,
aging…
Application areas and methods
Materials
 metallic materials (high strength and wear
resistant steels, various metals and alloys;
most metallic microstructures)
 ceramics (thin coatings, carbon materials,
oxides)
 polymers, elastomers
 composites (metal matrix composites,
coatings, polymer composites)
Methods
 meso to macroscale: (X)FEM, DEM, PF, SPH, PD, LB, CFD
 atomistic scale: (R)MD, KMC, PFC, CGMD, DFT, DD
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Implementation and packages
Post-processing,
data mining
(“pT_postProc”)
VTT ProperTune™ (pT) toolset for multiscale modeling and integrated computational materials engineering (ICME)
Initialization and
pre-processing
(“pT_preProc”)
Image based and synthetic mesoscale and atomistic models of nano-microstructures
(“pT_mesolib”)
Material models, failure models, stochastics, multiphysics etc. for various solvers
(“pT_fyslib”)
Discretization
(“pT_meshlib”)
Interfaces to FEA, discrete, in-house and other
solvers (“pT_interface”)
Multiscale packages, concurrence, adaptivity and
interfaces (“pT_mca”)
The novel parts are a collection of libraries, interfaces and various routines developed in Python, C++ and fortran.
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CASE 1: First step of interest,
introduction of microstructural features
Scratch testing of a thick coating
with microstructurewithout microstructure
approximately
30 µm
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2311/06/2015 23
CASE 1: Building a model of microstructure (synthetic)
Stochastic means
for generation of
microstructures,
often polygonal
and geometry
based
Stochastic means
for generation of
substructures
(defects and like)
Synthetic metal-matrix
composite microstructure
Synthetic defect containing
composite microstructure
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SEM image
detail
Segmentation for
phases and
defects
Meshing or use of
discrete methods
Simulated
material test –
indentation stress
and strain
distribution
Local material
distribution
Stress contours Strain contours
CASE 1: Building a model of microstructure
(imaging based) – WC-Co
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CASE 1: Building a model of
microstructure (imaging based)
Orthoslice plot of the original 3D
tomography image of the composite
Representative
volume 3D finite
element model
PLA matrix phase
Fiber phase
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(imaging based)
Equivalent stress contours Equivalent stress isosurfaces
Equivalent stress contours, birch pulp Equivalent stress contours, matrix
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CASE 2: Building models of metallic microstructures
Introduction of secondary
features such as twins (or
laths etc.) to a primary
structure
Use of 3D discrete voxel volumes for complete freedom in manipulating nano and microstructures, to obtain 3D images of
structure. Emphasis in metallic and composite (or plainly multi-phase) structures, but no morphological limitations with
respect to the method itself.
Isosurfaces after
stochastic Monte-Carlo
sampling of grain
boundaries (to generate
more realistically shaped
structures)
Introduction of 2nd phase
structures (precipitates,
carbides etc.) to a primary
structure
Tesselation of
synthetic micro-
structures
Also, mixing of synthetic and imaging features (i.e. “pluck” features of imaging data)
Generation of micro-
structures with
texture
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Mesoscale and microstructural models,
examples of metallic materials
Generation of FCC
structures
Generation of BCC
structures
(~bainite like)
Generation of BCC
structures
(~martensite like) Generation of
composite
microstructures
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CASE 2: Building models of metallic microstructures
Inherently stable geometric operations at non-smoothened
single grain voxel scale
Basic geometry based means for operating on grains and
sub-features implemented either as deterministic and
statistical versions
Multi-level operation, creation of higher
resolution and fidelity features:
Example of a complex microstructure generation process:
1. Tesselate prior structure
2. Tesselate packet structure
3. Tesselate block, sub-block, lath structure
4. Include additional phases and features
5. Random walks at phase boundaries or further
operations for specific features (=“stochastic
statistically informed noising”)
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Robotics at VTT

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Robotic activities and focus areas at VTT
Industrial robotics
Telerobotics
Sensor fusion
Human-robot interaction
Navigation and perception
Robotic cars
Ambient assisted living
Medical
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3511/06/2015 35
VTT’s Production lab
 Full-scale production modelling, simulation
and planning. Order and delivery process
development.
 Assembly methods based on 3D vision, force
sensing and machine learning.
 Developing close to market solutions, and
transfer the know-how to Finnish and
international industry.
Polishing robot cell
Welding robot cell
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3611/06/2015 36
VTT’s Production lab
 Implementing latest technologies for modern
production environments.
 Proof-of-concept prototyping of integrated,
multi-technological and multi-disciplinary
production solutions.
 Robots:
 ABB IRB 120
 ABB IRB 4600
 Comau NM 45-2.0
 Kuka KR 110-150
 Kuka KR 2500-150
 Schunk Powerball LWA 4P
Measurement and
inspection
Grinding robot cell
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Rapid prototyping
Rapid prototyping using
industrial robots
 A robotic cell for automatic
manufacturing of various types and
sizes of prototypes and billets
 Digital library substitutes pattern
shop
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Sensor fusion
Multi-calibration in the
production cell
 Flexible calibration methods for
geometrical relationships between
robots, cameras and laser
rangefinders in robot cell
 Tools to estimate geometric
inaccuracies
fixed
sensors
target
object
robot2
base
robot1
base
Eyes-in-hand1:
camera21,
camera22,
camera23
tool1
tool2
path points
Camera11
Camera12
Camera13
Eyes-in-hand2:
camera31,
camera32,
camera33
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 Natural physical interaction
utilizing 6 DOF force/torque
sensor with vision system
 Assistive sequences for
semiautomatic assembly
Natural physical human-
robot interaction
Human-in-loop assembly
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Safety of human-robot collaboration
 Maintaining the efficiency of robotic
system when human worker in close
proximity
 Slowing down the robot and changing
the defined safety area dynamically
 Designing the safety system and risk
analysis focused on large industrial
robots
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4111/06/2015 41
Research projects on industrial robotics
 CustomPacker
 FP7 project with TUM, PROFACTOR, Tekniker, Ferrobotics, MRK-Systeme, Loewe.
 Transferable and self-configuring robotic production cell (LIIKU)
 A concept and demonstrations of a transferable robotic system
 Sensor-based, fenceless safety systems
 Automation islands for the future (TUAUSA)
 A concept for short series, small batch production systems and demonstrations
 Semiautomatic robot systems (PATRA)
 Machine vision guided robot bin picking (BinPicking)
 Demonstrations of vision based parts picking directly from boxes
 Deburring of parts in short series production (Deburring)
 3D vision measurement of product shapes,
 Force controlled grinding and machining with robots
 Desktop assembly for light and small sized products (DeskAsse)
 Digital direct printing decoration for 3D objects (DIDECO)
 Ubiquitous manufacturing (U-Manu)
 Productivity with User Friendly Human-Robot Collaboration (TUOHIRO)
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Design for additive
manufacturing:
Topology optimization
Optimized Design
Geometry
Design Space

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What is topology optimization?
 Finite element based topology optimization is a
process of finding the optimal distribution of
material and voids in a given design space,
dependent on loading and boundary conditions,
such that the resulting structure meets prescribed
performance targets.
 Topology optimization can also be performed on
fluid dynamics problems where the flow region is
modified in order to reduce e.g. backflow and
recirculation, leading to a reduction in pressure
drop.
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4411/06/2015 44
Topology optimization in product development
 Well-suited for early development stages
 Can produce design proposals (i.e. “ideas” about how a design within
a given space might look)
 Not a tool for fine-tuning
 Topology optimization needs only design space, loads and boundary
conditions to be defined  no need for detailed or parameterized
CAD geometry models
Definition Concept Design
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Interpret
Results &
Remesh
Validate
Optimized Design
Geometry
 79% reduction
in mass
Design Space
Define Model
Run Topology
Optimization
Example 1:
Structural topology
optimization of a Jet
Engine Bracket
Step 1
Determine design space,
loads and boundary
conditions
Step 2
Create finite element
model
Step 3
Run topology optimization to
determine where material
can be removed
Step 4
Interpret optimization results
and create a new mesh for
reanalysis
Step 5
Run FE analysis of
optimized design to ensure
initial design criteria are
satisfied
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Example 2:
CFD topology optimization of 1/10th scale tractor cabin ventilation
system – 2 versions (with and without obstacles)
 Inlet
 Outlets
 Design SpaceInitial Model Model with Obstacles
In
Out1
Out 2
In
Out1
Out 2
Step 1
Determine design space, flow parameters
and boundary conditions
Initial Model Model with Obstacles
Step 2
Create and run CFD models
Steps 3 & 4
Run topology optimization; smooth and
interpret results
3
4
3
4
Step 5
Validate optimized geometry
 62% reduction in
pressure drop
 44% reduction in
pressure drop
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Additive manufacturing provides capability to produce
complicated optimized designs without compromise.
Topology optimization is the natural design technology for AM as
it can fully exploit its potential.
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Additional considerations
 Successfully printing a part with AM requires knowledge of:
 The given AM technology (i.e. printer)
 Printed material(s)
 Build direction & orientation
 Supporting structures & their removal
 Post-processing procedures
 VTT has experts in advanced manufacturing techniques, structural design &
analysis, and material science all under one roof. Knowledge sharing within
these areas of expertise can help ensure successful design and creation of
AM parts.

InnoLeap - Take an
innovative leap to the
future with VTT’s
concept design!

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Why InnoLeap?
 Future-oriented and innovative concepts
 Based on trend and user studies, co-innovation, scenario stories and
visualisations
 Built on in-depth understanding of users and their work activity
 Enhance innovation practices
 Adopt new design approaches
 Create fresh business opportunities
 Engaging visualisations for customers,
media, and other stakeholders
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Benefits of InnoLeap for your company
 With VTT’s InnoLeap concept design, your company will be:
 Able to develop innovative concepts that are both radical and user-
oriented
 Supported in the creation of new business opportunities by building
a market demand
 A forerunner in the industry with future oriented solutions
 The new concepts will:
 Provide a WOW experience for all stakeholders
 Offer concrete benefits for users
 Create buzz around the proposed products
 Improve your company’s brand image as an innovative company
 Inspire your company and stakeholders to adopt a new design
mindset and working methods to become more innovative
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VTT’s InnoLeap service modules
1. Trend
insight
2. Analysis
of user
activity
3. Draft
operation
concepts
4. Concept
evaluation
5. Creating
final
concepts
6.Final concept
visualizations
7. Concept
release and
media buzz
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Module 1 | Trend insight
Understanding future trends helps in creating the products of the
future:
 Technology trends, describing the future technologies that
have the most potential for your industry’s products.
 Interaction trends, describing future human-technology
interaction methods that are relevant in revolutionizing the way
your products are used.
 Societal trends, describing the future challenges for your
industry that you need to tackle with your products.
 Trending theoretical ideas related to your product’s context of
use; what does current scientific knowledge say about what is
important for your users?
Outcome: A summary of the most important trends and theories related to your
products and their usage.
►
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To go deep into discovering the desired future
experience of your product, we will carry out:
 Field studies of your chosen product’s users and
their activity with the product.
 A Core-task analysis, helping to distinguish the
basic demands and aims of your product’s user
activity.
 User experience vision and goal setting,
providing empathic understanding of the users of
your product.
 Reconceptualizing in a way that inspires new
design ideas.
Module 2 | Analysis of user activity
Outcome: Inspiration and empathic understanding of the product’s users.►
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The initial concept ideas are generated collaboratively in:
 Interaction method and future studies workshops, where
the most interesting methods and trends from module 1 are
gone through to provide inspiration.
 Concept development workshops, where various new
concept ideas are generated based on the understanding
drawn from modules 1 and 2.
 The result is several possible new concepts of operation that
describe novel ways of achieving your product’s users’ aims
with new technologies.
 The produced concepts can be communicated with scenario
stories, lo-fi sketches, and physical mock-ups.
Module 3 | Draft operation concepts
Outcome: Several innovative operational concept ideas.►
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It is important to evaluate the potential of the
initial concept ideas with actual users, for
example with:
 Focus group interviews
 Useful for recognizing the weaknesses
and strengths, as well as the potential
“wow” effect of the new design ideas, for
choosing the best concepts for further
development.
 In-depth expert interviews
 Useful for enhancing the chosen ideas
and ensuring that they work in the actual
context of use.
Module 4 | Concept evaluation
Outcome: Best ideas chosen for further development.►
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 After evaluating the concept ideas (in
module 4), we can create the final
operational concepts.
 These concepts describe our vision of
the future work with the proposed
technical solutions.
 This acts as a solid ground for the
production of potential visualizations in
module 6.
Module 5 | Creating final concepts
Outcome: Final concepts of operation.►
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 We can produce impressive visualizations of the final
operational concepts
 The possibilities include engaging concept pictures, 3D
prints, and top-notch 3D-animated concept videos.
 Concept pictures and videos are influential means of
communicating the design ideas, especially in today’s digital
media.
Module 6 | Final concept visualizations
Outcome: Impressive visualizations of the concepts.
►
►
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 The concepts can be released to the media together with VTT.
 Our status as a recognized research institute and our
professional media services facilitate access to the mainstream
media.
 Media buzz, in turn, ramps up the demand for the proposed
products and improves your company’s brand image.
 Following the dissemination of the concepts in the media allows
evaluation of their impact and gathering of feedback from
potential users and customers.
 For example, discussion in social media can bring forward new
ideas or enhancements for the proposed concepts.
Module 7 | Concept release
and media buzz
Outcome: Media events, press release, a buzz about the concepts in traditional and
social media, and feedback on the concepts for further development.
►
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InnoLeap reference case:
Future bridge operation for Rolls-Royce
 By utilizing the InnoLeap concept design method in the
FIMECC UXUS program, we have developed future ship
command bridge concepts with Rolls-Royce for tugboats,
cargo ships, and platform supply vessels.
 The aim of the concepts was to provide an impressive
vision of enhanced ship operations in the year 2025 as a
way of renewing the maritime industry.
 Rolls-Royce intends to use the concepts to influence its
stakeholders, such as customers and maritime law
regulators
 The aim is that the envisioned concept solutions might be
implemented on real ships’ bridges in the future.
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Benefits of the project for Rolls-Royce
 The produced concept videos received appraisal from the top
management of Rolls-Royce.
 Over 250 separate news articles about the concepts, including
Wired, Gizmag, T3, and several maritime magazines.
 Plenty of publicity for the released concept video: the YouTube
version of the video received over 40,000 hits in only three
weeks!
 The media buzz has uplifted Rolls-Royce’s brand image as an
innovative company.
“The starting point for the concept
development was to consider user
experience in the maritime
context. The development process
combined analysis of work activity
with experience-driven design.
Based on these analyses, we
created the concepts that reflect
our vision of future bridge
operations. Our customers have
found the concepts extremely
inspiring and really appreciated
the user-oriented approach”
Iiro Lindborg
Development Project Manager
Rolls-Royce Oy Ab
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Additive manufacturing at VTT
- AM-liiketoiminta project

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What is additive manufacturing?
(3D printing)
The process of joining materials to make objects from 3D model data,
usually layer upon layer, as opposed to subtractive manufacturing
methodologies.
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AM-liiketoiminta project
 Total budget 3 M€
 R&D project coordinated by
VTT, budget ~1 M€
 Subcontracting from
companies 200 - 300 k€
 Duration 2014 - 2016
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Scope of the project
Project is going to tackle the challenges that prevent the large scale utilization of
AM-technology in Finland. Project’s main objective is to generate new
business around AM technology in Finland. Project focuses mainly on
metal printing.
R&Dproject
TP1: Available materials and their performance
TP2: Product development utilizing full potential of AM-
technology
TP3: Integration of AM-technology into production
TP4: Development of business models and processes
utilizing possibilities offered by AM-technology.
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New metal printing machine
SLM 125 (SLM Solutions GmbH)
 Powder bed fusion technology
 Maximum part size: 123 x 123 x 100 mm
 Optimal for material development and testing
 Materials: stainless steels, tool steels, Inconel,
cobalt-chromium, aluminium, titanium, etc.
 Laser: 400W
 Building speed ~15cm3/h
 Other machines also available
 (FDM and binder jetting)
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Two Inconel 625 printed samples
These can be
found at
Fimecc booth.
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Smart machines and manufacturing
- knowledge and industrialization
ecosystem
Agile support for internationalizing
growth companies
 GROWTH – agile co-creation models
for growth companies
 INFRASTRUCTURE – benefit from public
and private investments
 INTERNATIONAL - full exploitation of
European networks
New ecosystem at
Hervanta Campus
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Contact us!
Risto Kuivanen
Business Development Manager
Tel. +358405116699
risto.kuivanen@vtt.fi
Erja Turunen
Vice President, Research
Tel. +358503809671
erja.turunen@vtt.fi
VTT ProperTune
Anssi Laukkanen
Senior Scientist
Tel. +358408208039
anssi.laukkanen@vtt.fi
Tuomas Pinomaa
Key Account Manager
Tel. +358406873054
tuomas.pinomaa@vtt.fi
Additive manufacturing,
3D
Erin Komi
Research Scientist
Tel. +358406829705
erin.komi@vtt.fi
Petri Laakso
Senior Scientist
Tel. +358405445646
petri.laakso@vtt.fi
VTT Innoleap
Hannu Karvonen
Research Scientist
Tel. +358 40 021 6396
hannu.karvonen@vtt.fi
Mikael Wahlström
Research Scientist
Tel. +358 40 670 3649
mikael.wahlstrom@vtt.fi
For Industry
scenarios
Jaakko Paasi
Principal Scientist
Tel. +358408206138
jaakko.paasi@vtt.fi
Nina Wessberg
Senior Scientist
Tel. +358407428185
nina.wessberg@vtt.fi
Riikka Virkkunen
Head of Research Area
Tel. +358505202381
riikka.virkkunen@vtt.fi
Robotics
Ali Muhammad
Senior Scientist
Tel. +358400560851
ali.muhammad@vtt.fi
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