Additive Manufacturing
Vukile Dumani | 14 July 2014
GKN PLC: Delivering to our Markets
We have four operating divisions: GKN Driveline and GKN
Powder Metallurgy that focus on the automotive market; GKN
Aerospace, and GKN Land Systems. Every division is a market
leader, each outperforming its markets, giving unrivalled expertise
and experience in delivering cutting-edge technology and
engineering to our global customers:
GKN Aerospace
A leading first tier supplier to the
global aviation industry focussing on
aerostructures, engine systems and
products and specialty products.
GKN Driveline
A world leading supplier of
automotive driveline systems
and solutions, including
all-wheel drive.
2013 - Sales by division
£104m
Other
1%
£899m
Land
Systems
12%
GKN Powder Metallurgy
The world’s largest manufacturer of
sintered components,
predominantly to the automotive
sector.
£3,416m
Driveline
45%
£2,243m
Aerospace
30%
GKN Land Systems
A leading supplier of technologydifferentiated power management
solutions and services to the
agricultural, construction, industrial
and mining sectors.
Powder
Metallurgy
12%
£932m
2
GKN Aerospace
$3.5 billion Global Aerospace company, 35 sites in 9 countries, 11,700 people
Market leaders in airframe structures, engine components and transparencies
Increasing investment in technology and focus on deployment
Growing global footprint as part of drive for increasing competitiveness
3
GKN Aerospace – World Class Product Portfolio
Aerostructures Global #3
Engine structures
45% of Sales 2013
50% of Sales 2013
Wing
Fuselage
Nacelle and
Pylon
Global #2
Engine Systems and Services
Engine structures
Engine rotatives
Special
products
Global
#1/2
5% of Sales 2013
Transparencies
and Protection
Systems
J-UCAS Fuselage
A380 Fixed Trailing Edge
B747-8 Exhaust
B787 Anti-icing System
A350XWB Rear Spar
CH53K Aft Fuselage
A400M Engine Intake
V22 Fuel Tanks
A330 Flap Skins
B787 Floor Grid
B767 Winglet
HondaJet Fuselage
B787 Cabin Windows
B787 Inner Core Cowl
Full Engine MRO and support
Ariane 5 Exhaust nozzle
F35 Canopy
4
A Broad Customer Base
Military 27%
Civil 73%
2013 Sales
5
Targeted Innovation – Technology
Engine
Statics
Engine
Rotatives
Future Wing
Technologies
Advanced
Fuselage
Composite Technology
Metallic Technology
Supporting Technology
6
Nacelle,
Pylon &
Exhaust
Transparencies Protection
& Coatings
Systems
Two Ways of Fabrication - Traditional View
Subtractive
Additive
7
Two Ways of Fabrication - Modern View
Subtractive
Additive
Aircraft Rib Structures
( Source: Cranfield)
Aircraft Rib Structures
( Source: Cranfield)
8
Powder Based Technologies
Powder Bed
Nozzle Deposition
Layer Deposition
9
Powder Based Technologies
Powder Bed
Nozzle Deposition
Two Methods:
One Method:
Electron Beam Melting
Direct Metal Deposition
Selective Laser Melting
10
Powder Based Technologies
Powder Bed
Nozzle Deposition
Characteristics:
Materials
Characteristics:
1. Good mechanical properties
2. High part complexity
3. Surface finish
4. Not as precise as SLM
1. High build rate
2. Suitable for repairs
3. High powder utilisation
4. Low part complexity
1. High accuracy
2. High part complexity
3. Low build rate
4. Residual stress
11
Powder Based Technologies
Powder Bed
Nozzle Deposition
Applications:
Turbine Blade
( Source:Avio)
Applications:
Orthopaedic Implants
( Source:Arcam)
Blisk Repairs ( Source: Fraunhofer Institute)
Lattice Housing
(Source:Arcam)
Dental Prostheses ( Source:EoS)
Laser Cladding
(Source: Fraunhofer Institute)
Fuel Injector & Swirler
Jewellery ( Source:CPM)
12
Metallic Leading Edge
( Source: Fraunhofer Institute)
Wire Based Technologies
Laser Wire Deposition
Electron Beam Wire Deposition
13
Wire Based Technologies
Laser Wire Deposition
Electron Beam Wire Deposition
Characteristics:
Characteristics:
1. Relatively fast
2. Good mechanical properties
1. Relatively fast
2. Suitable for repairs
3. Low complexity
3. Low complexity
4. Residual stress
4. Surface finish
14
Wire Based Technologies
Laser Wire Deposition
Electron Beam Wire Deposition
Applications:
Applications:
Aircraft Rib Structures
( Source: Cranfield)
Aircraft Rib Structures
( Source: Cranfield)
Aircraft Rib Structures
( Source: Cranfield)
Aircraft Rib Structures
( Source: Cranfield)
Aircraft Rib Structures
( Source: Cranfield)
15
Why Use Additive Manufacturing?
Additive Manufacturing saves significant resources over current methods:
raw materials, energy, fewer chemicals (cutting fluids), lead time = cost
20:1
Buy-to-Fly
Forged Billet =200kg
Finished Part = 10kg
Swarf = 190kg
2:1
Buy-to-Fly
Baseplate=10kg
Wire = 10kg
Swarf = 10kg
Finished Part = 10kg
16
Barriers to Implementation
Qualification barriers
Many variables require standardisation
Material allowables need to be generated for the different process variables
Each machine may produce unique characteristics that increase process variability
Material properties may vary from process to process, machine to machine, location to
location and orientation to orientation
Raw material cost may be reduced by
Mass production
Cheaper manufacturing methods
Cheaper sources such as swarf
Process speed
On-going research is aiming to improve this
Design and analysis tools
Requires a change of mind-set from traditional design
Machine cost
Limited number of suppliers will improve as new players come onto the market
17
Optimisation in Aerospace Design
Farnborough International Airshow 2014
Wilson Wong | 14 July 2014
Author
Wilson Wong
Design and Analysis Lead – Additive Manufacturing Centre
Background:
− MEng Aeronautical Engineering, University of Bristol
− Phd Composite Buckling, University of Bristol
− Design / Structural / FEA engineer
− Assystem, Atkins
− GKN Aerospace – Additive Manufacturing Centre
Interests:
− Novel methods on design and analysis
− Exploration of advance design and analysis techniques
− Incorporating latest IT advancement in the design and analysis process
19
20
Definition of Optimisation
From Latin optimus (best)
Cambridge dictionary:
The act of making something as good as possible
Oxford dictionary:
“Make the best or most effective use of (a situation or resource)”
What does it really entail?
21
We Carry Out Optimisation in Different Scenarios
Route optimisation (travelling
salesman problem)
Online presence optimisation (inc. Search Engine
Optimisation and Social Media Optimisation)
Priority identification
Process optimisation
Space optimisation
(Source: CiS)
Task planning / resource optimisation
(Source: http://www.iprod-project.eu/)
22
Project planning
Outcome
Cost
Route optimisation (travelling
salesman problem)
Online presence optimisation (inc. Search Engine
Optimisation and Social Media Optimisation)
Quality
Priority identification
Optimisation
Performance
Process optimisation
Time
Space optimisation
(Source: CiS)
Task planning / resource optimisation
(Source: http://www.iprod-project.eu/)
23
Project planning
Outcome
Cost
Route optimisation (Travelling
salesman problem)
Online presence optimisation (inc. Search Engine
No tooling – reduce cost,
Optimisation & Social Media Optimisation)
Quality
Optimisation
time
Performance
Reduce waste
Priority identification
New design freedom to
increase performance
Process optimisation
Rapid response to
modification
Time
Space optimisation
(Source: CiS)
Task planning / resource optimisation
(Source: http://www.iprod-project.eu/)
24
Project planning
AM and Optimisation – Relationship
25
Current State of the Art – 2D/2.5D Structural Optimisation
Source: Airbus, Altair
Source: Boeing, Desktop Engineering
Source: Eurocopter, Altair
Source: Airbus, Technische Universität München
26
Current Examples – 3D Structural Optimisation (Enabled by
AM)
Source: EADS Apworks GmbH, Altair
Source: Within Lab
Source: GE
Source: Airbus, Altair
Source: EADS Innovation Works, Altair
Source: GE, GrabCAD
Source: GKN
Source: GKN, Airbus
27
AM Facilitates Optimisation
With machining
constraints
Without machining
constraints
28
Structural Optimisation – Future
29
Structural Optimisation - Macro
Topology, Size, Shape
Topology
Size
Topography
Shape
Free-Size
Free-Shape
Concept
Refine
Lattice + Skin (Size, Shape)
Source: LimitState
Source: Within Lab
Source: USTC, DUT, MRA
Source: GE, GrabCAD
Source: DTI
30
Structural Optimisation - Meso
Combine features of topology and lattices
Reduces mass of topology optimised structure
further
Provide robustness of features in topology
optimised structure
Source: Delta 7
Source: DTI, Compolight
Source: Altair
31
Structural Optimisation - Micro
Mimic nature (bio-mimetic), e.g. bone
Design material at micro scale to cater for properties required
Source: MIT, LLNT
Source: BBC, 3ders.org
Source: HRL Laboratories LLC
32
Optimisation Unleashes Potential of AM
With machining
constraints
Without machining
constraints
33
Challenges
Design
More
integrated/easy
modelling
software required
Software to
handle
exponential
amount of
geometries
Analysis
New analysis
methods needed
Significantly better
solver capability
Manufacturing
Speed
Reliability
Inspection
New techniques
required
Post
processing
New techniques
required
Testing
New test
methodology
needed
•
•
•
•
Process change
Mindset change
Development of new methods
IT backbone to support
Culture change
34
Development Process Flow
Conventional
Customer
Requirements
Concept
Detail Analysis
(Stress, F&DT)
Detail Design
Design
Customer
Requirements
Future
Final Design
Detail Design
Optimisation
Concept
Local
Detail Analysis
(Stress, F&DT)
Analysis
Global
35
Final Design
Current
Topology optimisation
CFD optimisation
Configuration optimisation
Source: GE, GrabCAD
Multi-physics optimisation
Source: Airbus, Altair
Source: RR
36
Different Aspects of Aircraft Design
Source: McGill University
Source: Technishe Universitat
Braunschweig
Source: Antonio Silva
Source: Linflow
Source: MOOG, NI
Source: ANSYS
Source: MSC
37
GOAL - Holistic Optimisation
MDO for Aircraft Configurations with High-fidelity (MACH)
38
GOAL - Holistic Optimisation
Multi-level of details
•Top level approximate system modelling
•Low level detail modelling
Accessible to every stakeholder
•Bidding team
•Detail analyst
Allow quick what-if scenarios at any time offline
•Impact analysis on changes
39
Why Are We Not Using Global Optimisation More?
Challenges
Barriers
Big data – data management
Specialist software
Computing power
Very specific technical skills needed
Physics coupling complex
Much greater complexity of problems
Different software platforms
Steep learning curve
Paradigm shift in mindset, culture, working
procedures
Embedded culture
40
Possible Solutions
Analytics method
−
−
−
−
Multivariate analysis
Design of Experiment
Design Structural Matrix
Parallel Coordinate
HPC, distributed computing, Cloud
Multi-scale analysis
Source: EnterpriseTech Cloud Edition
Custom code to interconnect different platforms
Simplistic software for quick approximate answer
Source: NASA
41
In Brief
AM
Optimisation
What is optimisation?
Emphasis on structural optimisation (now and future)
Challenges ahead for implementing future structural optimisation
Importance of culture
Local and global optimisation
Challenges on global optimisation
Quick peek to future
42
Future and Questions
Source: Emerging Objects
Source: Airbus
Source: Henri Freiherr von Freyberg
Source: Altair
Source: MIT
Source: Concept Laser
Source: EDAG, 3ders
Source: Aerojet Rocketdyne
43
Source: Dame Zaha Hadid