Additive Manufacturing. Vukile Dumani 14 July 2014

Transcription

1 Additive Manufacturing Vukile Dumani 14 July 2014

2 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. 2,243m Sales by division 899m Land Systems 12% Aerospace 30% 104m Other 1% Powder Metallurgy 12% Driveline 45% 3,416m GKN Driveline A world leading supplier of automotive driveline systems and solutions, including all-wheel drive. GKN Powder Metallurgy The world s largest manufacturer of sintered components, predominantly to the automotive sector. GKN Land Systems A leading supplier of technologydifferentiated power management solutions and services to the agricultural, construction, industrial and mining sectors. 932m 2

3 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

4 GKN Aerospace World Class Product Portfolio Aerostructures 45% of Sales 2013 Global #3 Engine structures Global #2 50% of Sales 2013 Special products 5% of Sales 2013 Global #1/2 Wing Fuselage Nacelle and Pylon Engine Systems and Services Engine structures Engine rotatives 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 B787 Inner Core Cowl Full Engine MRO and support B787 Cabin Windows B767 Winglet HondaJet Fuselage Ariane 5 Exhaust nozzle F35 Canopy 4

5 A Broad Customer Base Military 27% Civil 73% 2013 Sales 5

6 Targeted Innovation Technology Engine Statics Engine Rotatives Future Wing Technologies Advanced Fuselage Nacelle, Pylon & Exhaust Transparencies & Coatings Protection Systems Composite Technology Metallic Technology Supporting Technology 6

7 Two Ways of Fabrication - Traditional View Subtractive Additive 7

8 Two Ways of Fabrication - Modern View Subtractive Additive Aircraft Rib Structures ( Source: Cranfield) Aircraft Rib Structures ( Source: Cranfield) 8

9 Powder Based Technologies Powder Bed Nozzle Deposition Layer Deposition 9

10 Powder Based Technologies Powder Bed Nozzle Deposition Two Methods: One Method: Electron Beam Melting Direct Metal Deposition Selective Laser Melting 10

11 Powder Based Technologies Characteristics: Powder Bed Characteristics: Nozzle Deposition Materials 1. Good mechanical properties 2. High part complexity 3. Surface finish 4. Not as precise as SLM 1. High accuracy 2. High part complexity 3. Low build rate 4. Residual stress 1. High build rate 2. Suitable for repairs 3. High powder utilisation 4. Low part complexity 11

12 Powder Based Technologies Powder Bed Nozzle Deposition Applications: Applications: Turbine Blade ( Source:Avio) Orthopaedic Implants ( Source:Arcam) Lattice Housing (Source:Arcam) Blisk Repairs ( Source: Fraunhofer Institute) Dental Prostheses ( Source:EoS) Laser Cladding (Source: Fraunhofer Institute) Metallic Leading Edge ( Source: Fraunhofer Institute) Fuel Injector & Swirler Jewellery ( Source:CPM) 12

13 Wire Based Technologies Laser Wire Deposition Electron Beam Wire Deposition 13

14 Wire Based Technologies Laser Wire Deposition Characteristics: Electron Beam Wire Deposition Characteristics: 1. Relatively fast 2. Suitable for repairs 3. Low complexity 4. Surface finish 1. Relatively fast 2. Good mechanical properties 3. Low complexity 4. Residual stress 14

15 Wire Based Technologies Laser Wire Deposition Applications: Electron Beam Wire Deposition 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

16 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 Swarf = 190kg Finished Part = 10kg 2:1 Buy-to-Fly Baseplate=10kg Wire = 10kg Swarf = 10kg Finished Part = 10kg 16

17 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

18 Optimisation in Aerospace Design Farnborough International Airshow 2014 Wilson Wong 14 July 2014

19 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

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21 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

22 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 Task planning / resource optimisation (Source: Space optimisation (Source: CiS) Project planning 22

23 Outcome Route optimisation (travelling salesman problem) Cost Quality Optimisation Online presence optimisation (inc. Search Engine Optimisation and Social Media Optimisation) Performance Priority identification Process optimisation Time Task planning / resource optimisation (Source: Space optimisation (Source: CiS) Project planning 23

24 Outcome Route optimisation (Travelling salesman problem) Cost Priority identification Quality Optimisation Process optimisation Time Online presence optimisation (inc. Search Engine No tooling reduce cost, Optimisation & Social Media Optimisation) Performance time Reduce waste New design freedom to increase performance Rapid response to modification Task planning / resource optimisation (Source: Space optimisation (Source: CiS) Project planning 24

25 AM and Optimisation Relationship 25

26 Current State of the Art 2D/2.5D Structural Optimisation Source: Airbus, Altair Source: Boeing, Desktop Engineering Source: Airbus, Technische Universität München Source: Eurocopter, Altair 26

27 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, Airbus Source: GKN 27

28 AM Facilitates Optimisation With machining constraints Without machining constraints 28

29 Structural Optimisation Future 29

30 Structural Optimisation - Macro Topology, Size, Shape Lattice + Skin (Size, Shape) Topology Topography Free-Size Concept Size Shape Free-Shape Refine Source: Within Lab Source: LimitState Source: GE, GrabCAD Source: USTC, DUT, MRA Source: DTI 30

31 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

32 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

33 Optimisation Unleashes Potential of AM With machining constraints Without machining constraints 33

34 Process change Mindset change Development of new methods IT backbone to support Challenges Design More integrated/easy modelling software required Software to handle exponential amount of geometries Culture change 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 34

35 Development Process Flow Conventional Customer Requirements Concept Detail Design Detail Analysis (Stress, F&DT) Final Design Design Detail Design Customer Requirements Optimisation Concept Local Final Design Future Analysis Global Detail Analysis (Stress, F&DT) 35

36 Current Topology optimisation CFD optimisation Configuration optimisation Source: GE, GrabCAD Multi-physics optimisation Source: Airbus, Altair Source: RR 36

37 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

38 GOAL - Holistic Optimisation MDO for Aircraft Configurations with High-fidelity (MACH) 38

39 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

40 Why Are We Not Using Global Optimisation More? Challenges Big data data management Computing power Physics coupling complex Different software platforms Paradigm shift in mindset, culture, working procedures Barriers Specialist software Very specific technical skills needed Much greater complexity of problems Steep learning curve Embedded culture 40

41 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

42 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

43 Future and Questions Source: Airbus Source: Emerging Objects Source: Altair Source: Henri Freiherr von Freyberg Source: MIT Source: Concept Laser Source: EDAG, 3ders Source: Aerojet Rocketdyne Source: Dame Zaha Hadid 43