VTT For Industry

76
VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD VTT Technology for business

Transcript of VTT For Industry

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VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD

VTT – Technology for business

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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 Otsikoissa on

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ao. osioon.

Sisältökalvoissa

on Back-kohta,

josta pääsee

takaisin

sisällys-

luetteloon.

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VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD

For Industry - Scenarios

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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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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 TECHNICAL RESEARCH CENTRE OF FINLAND LTD

VTT ProperTune™ for

integrated computational

materials engineering

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Methodological

approach -

multiscale

modeling

(“toolset”)

Multiscale modeling = Means of quantifying the material

structure and behavior critical for desired and tailored

performance. « BACK TO CONTENTS

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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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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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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 microstructure without microstructure

approximately 30 µm

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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) – WC-Co

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CASE 1: Building a model of microstructure

(imaging based) – WC-Co

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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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CASE 1: Building a model of microstructure

(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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VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD

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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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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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

objec t

robot2

baserobot1

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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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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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 Space Initial 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

Initial Model Model with Obstacles

Steps 3 & 4

Run topology optimization; smooth and

interpret results

3

4

3

4

Initial Model Model with Obstacles

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.

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VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD

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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VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD

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&

D p

roje

ct

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

[email protected]

Erja Turunen

Vice President, Research

Tel. +358503809671

[email protected]

VTT ProperTune

Anssi Laukkanen

Senior Scientist

Tel. +358408208039

[email protected]

Tuomas Pinomaa

Key Account Manager

Tel. +358406873054

[email protected]

Additive manufacturing,

3D

Erin Komi

Research Scientist

Tel. +358406829705

[email protected]

Petri Laakso

Senior Scientist

Tel. +358405445646

[email protected]

VTT Innoleap

Hannu Karvonen

Research Scientist

Tel. +358 40 021 6396

[email protected]

Mikael Wahlström

Research Scientist

Tel. +358 40 670 3649

[email protected]

For Industry

scenarios

Jaakko Paasi

Principal Scientist

Tel. +358408206138

[email protected]

Nina Wessberg

Senior Scientist

Tel. +358407428185

[email protected]

Riikka Virkkunen

Head of Research Area

Tel. +358505202381

[email protected]

Robotics

Ali Muhammad

Senior Scientist

Tel. +358400560851

[email protected]

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