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Additive manufacture of cores for aerospace: Linking quality

and controlDavid Pollard - dp0084@bristol.ac.uk - 20th October 2016

SAMPE UK and Ireland Chapter 2016 Masterclass – Additive Manufacture

The Manufacturing Technology Centre, Ansty Park, Coventry

Contents

• Motivation

• Introduction

• Quality Definitions

• Assuring Quality

• Progress in Control

• AM Cores in Aerospace

• Further work

Images from:http://airinsight.com/2011/09/06/first-a350-xwb-flyable-wing-upper-cover/http://www.designboom.com/technology/dx-toronto-3dxl-large-scale-3d-printing-05-15-2015/

Contents

• Motivation

• Introduction

• Further work

Motivation

Source: http://www.3ders.org/articles/20160323-airbus-seeks-to-3d-print-half-of-its-future-airplane-fleet.html

Motivation

• Aurora Flight Science and Stratasys collaboration

• Demonstrates feasibility of custom aircraft• Reduced cost

• Faster design time

Source: http://www.stratasys.com/resources/case-studies/aerospace/aurora-flight-sciences

Motivation

• Faster design iterations• 50% Design and Build time

reduction

• 80% AM components

• ULTEM FDM Plastic• Meets FAA Flame, Smoke, and

Toxicity (FST) requirements

Source: http://www.stratasys.com/resources/case-studies/aerospace/aurora-flight-sciences

Motivation

• Impossible Objects:• Composites Based Additive Manufacture (CBAM)

• Laminate-based method for long-fibre reinforcement printing

• Collaboration with Aurora Flight Sciences• Produced AM stabilisers capable of taking

landing load

Source: http://www.compositesworld.com/articles/3d-printed-composite-parts-provide-solution-for-uav

CompositesWorld: September 2016

Contents

• Motivation

• Introduction

• Further work

Introduction

• Processes• Vat Polymerisation

• Powder Bed Fusion

• Binder Jetting

• Material Jetting

• Sheet Lamination

• Material Extrusion

• Directed Energy Deposition

• ASTM F2792:• “process of joining materials to make

objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies”

Introduction

• Google Trends:• Search terms:

• 3D printing (Industry)

• Manufacturing (Industry)

• 3D printing was more commonly used than Additive Manufacturing

• Results are the percentage of peak searches

Introduction

3D printing (Industry)

Introduction

3D printing (Industry)

Manufacturing (Industry)

Introduction

Source: European Commission Report:Identifying current and future application areas, existing industrial value chains and missing competences in the EU, in the area of additive manufacturing (3D-printing)

Introduction

Ridged print failure - nozzle blockage

Sprue – insufficient retraction to stop flowSupport structures

Peeling from print bed

Contents

• Motivation

• Introduction

• Further work

Quality Definitions

• Quality:• Degree of excellence

• Conformance with requirements

• Totality of product features

• Fitness for use

• Freedom from defects, imperfections, or contamination

Quality Definitions

• “Design process is a journey into the unknown, whereas the production process is a journey along a proven path with a predictable outcome” - David Hoyle, Quality Systems Handbook

• ISO 9001 requires: “establish procedures for identifying adequate statistical techniques required for verifying the acceptability product characteristics”

Quality Definitions

Images from:http://aerospaceengineeringblog.com/sandwich-panel/http://communicats.blogspot.co.uk/p/technical-art.html

Face sheets

Adhesive material

Core splicing

Core type 1

Core type 2 Core type 2

Insert

Quality Definitions

AM Aerospace Core

Manufacturing Design

Machine location?

Which process?

Manufacturing workflow?

Component optimisation?

Fulfilling requirements?

Design workflow?

Customer Input

Quality Definitions

AM Aerospace Core

Machine location?

Which process?

When in the process?

Design workflow?

Quality Assurance

Customer Input

Quality Definitions

AM Aerospace Core

Quality Control

Machine location?

Which process?

When in the process?

Design workflow?

Quality Assurance

Customer Input

Contents

• Motivation

• Introduction

• Further work

Assuring Quality

• FDA – Technical Considerations for Additive Manufactured Devices• Draft guidance for qualifying medical devices

• Highlights need for documentation

• Separation of Geometry/Build certification

• Difficulties in inspection of internal defects and complex geometries

Source: Witherell, P., Herron, J., & Ameta, G. (2016). Towards Annotations and Product Definitions for Additive Manufacturing. Procedia CIRP, 43, 339-344.Images: http://www.bbc.co.uk/news/technology-34044453http://www.wakehealth.edu/WFIRM/

Assuring Quality

• Geometric Dimensions and Tolerancing (GD&T)• Common accuracy control

• Suited for 2D Shapes

Source: Witherell, P., Herron, J., & Ameta, G. (2016). Towards Annotations and Product Definitions for Additive Manufacturing. Procedia CIRP, 43, 339-344.

Assuring Quality

• Geometric Dimensions and Tolerancing (GD&T)

• Product and Manufacturing Information (PMI)• Complex curvatures

• Strong Process/Product interaction

• Not meant for human interpretation

Source: Witherell, P., Herron, J., & Ameta, G. (2016). Towards Annotations and Product Definitions for Additive Manufacturing. Procedia CIRP, 43, 339-344.

Assuring Quality

• Process inputs

• Thermal:• Contraction of layers during cooling

• Inter-layer bonding effects

• Mechanically induced:• Machine vibration

• Variable flow rates

Image: https://www.simplify3d.com/support/print-quality-troubleshooting/

Assuring Quality

Process Parameters

Material Properties

Build Environment

AM Process Model[TODO – image]

Surface Roughness

Accuracy

Strength

Build time

Build cost

Density

Image: By Zureks - Own work, GFDL, https://commons.wikimedia.org/w/index.php?curid=5544055

Source: Garg, A., Tai, K. and Savalani, M.M., 2014. State-of-the-art in empirical modelling of rapid prototyping processes. Rapid Prototyping Journal, 20(2), pp.164-178.

Thermal & Mechanical effects

Assuring Quality

Process Parameters

Material Properties

Build Environment

Surface Roughness

Accuracy

Strength

Build time

Build cost

Density

Layer thicknessSpeedFlow rateNozzle temperatureNozzle diameterPart orientationRaster angleInfill type/density

Assuring Quality

Process Parameters

Material Properties

Build Environment

Surface Roughness

Accuracy

Strength

Build time

Build cost

Density

Filament shape + sizeRheologyElastic modulus

Assuring Quality

Process Parameters

Material Properties

Build Environment

Surface Roughness

Accuracy

Strength

Build time

Build cost

Density

Chamber temperatureMechanical responseAir properties

Assuring Quality

• Thermal distortion• Can cause separation from build surface

• Affects final accuracy

• Can be predicted and reduced based on model

• Thermal bonding• Layers bond above Tg

• Modelling of heat flow during print

Source: Huang, Q., Zhang, J., Sabbaghi, A. and Dasgupta, T., 2015. Optimal offline compensation of shape shrinkage for three-dimensional printing processes. IIE Transactions, 47(5), pp.431-441.

Assuring Quality

• Thermal distortion modelling• Traditionally constrained my

CAD/Simulation tools

• Functional Generative Design:• Developed by Dassault Systèmes

• CATIA geometry

• Abaqus FEA

• Tosca topology optimisation

Image: http://perspectives.3ds.com/tag/functional-generative-design/Source: CompositesWorld September 2016, p13

Assuring Quality

• Cores produced through FDM tested in compression

• Similar ultimate stress for wall thickness variation

• Different failure characteristics• Especially compared to Nomex

Source: Pollard, D., Ward, C., Herrmann, G., Etches, J., 2016. Manufacture of Honeycomb Cores through Fused Deposition Modelling. Proceedings of the 17th European Conference on Composite Materials

Contents

• Motivation

• Introduction

• Further work

Progress in Control

• Flow control• Iterative Learning Control

• Different flow states discretised

• Road thickness variations used to modify input signal for next iteration

• 80% reduction of RMS error

Source: Hoelzle, D.J., Alleyne, A.G. and Johnson, A.J.W., 2009, June. Iterative Learning Control using a basis signal library. In 2009 American Control Conference (pp. 925-930). IEEE.

Progress in Control

• Machine control• Majority of low-cost printers use open-

loop stepper motors

• With axis encoders and PI control, 75% reduction in tracking error for jagged contours

Source: Weiss, B.M., 2014. Closed-Loop Control of a 3D Printer Gantry (Doctoral dissertation, University of Washington).

NB: Errors radially amplified by 20x

Progress in Control

• MarkForged X• Prints with carbon

reinforcement

• 50 µm resolution

• Laser scanner for part accuracy checks

Source: https://markforged.com/introducing-the-mark-x/

Progress in Control

Additive/Subtractive manufacture

Source: Keating, S. and Oxman, N., 2013. Compound fabrication: A multi-functional robotic platform for digital design and fabrication. Robotics and Computer-Integrated Manufacturing, 29(6), pp.439-448.

Progress in Control

Surface scanning and printing

Source: Song, X., Pan, Y. and Chen, Y., 2015. Development of a low-cost parallel kinematic machine for multidirectional additive manufacturing. Journal of Manufacturing Science and Engineering, 137(2), p.021005.:

Progress in Control

Source: Song, X., Pan, Y. and Chen, Y., 2015. Development of a low-cost parallel kinematic machine for multidirectional additive manufacturing. Journal of Manufacturing Science and Engineering, 137(2), p.021005.

Full video available from: https://www.youtube.com/watch?v=qGyiXFGvkqE

Progress in Control

• Superimposition of object over surface for 3D printing

• Identified key issues for multi-dimensional printing• Tight tolerance for nozzle positioning

• Requires stiff mechanical system

Source: Bausch, N., Dawkins, D., Frei, R., Klein, S., 2016.3D Printing onto Unknown Uneven Surfaces. Proceedings of the 7th

IFAC Symposium on Mechatronic Systems

Contents

• Motivation

• Introduction

• Further work

AM Cores in Aerospace

• Optimisation of honeycomb cores for required loads• Reinforcement for higher stress concentrations

• Variations in cell density or shape around holes

• Curved panels production with no added complexity

Source: Riss, F., Schilp, J. and Reinhart, G., 2014. Load-dependent optimization of honeycombs for sandwich components–new possibilities by using additive layer manufacturing. Physics Procedia, 56, pp.327-335.

• Boeing Patent US 2004/0048027• “Honeycomb Cores for Aerospace Applications”

• Discuss key advantages:• Reduces manufacturing cost for complex Radar

Cross Section

• Internal features and geometry

• Multiple gradients of material for testing reduction

Source: Hayes, M., DeGrange, J., Rice, C. and Polus, J., Hayes Michael W., DegrangeJeffrey E., Rice Christian V. and Polus Jeffrey E., 2002. Honeycomb cores for aerospace applications. U.S. Patent Application 10/236,361.

Source: White, J., Etches, J. Ward, C., 2013. CDE 28088: The Development of Low Cost Additive Layer Manufacturing for Use as Repair Equipment in the Field, to Improve Operations and Support for Composite Platforms.

Source: Pollard, D., 2014, Automated sandwich panel production utilisingadditive manufacture and silicone pick and place technology, Masters Thesis, University of Bristol

Contents

• Motivation

• Introduction

• Further work

Further work

• Efficient structure

• Manufacturability

• Increased functionality

Design optimisation

• Failure monitoring

• Reduction of manual input

• In-process quality control

Reliability in production

• Non Destructive Testing

• Quality Assurance/Control

• Advances in qualification processesPart verification

Selection of further reading• Review papers:

• Huang, Y., Leu, M.C., Mazumder, J. and Donmez, A., 2015. Additive manufacturing: current state, future potential, gaps and needs, and recommendations. Journal of Manufacturing Science and Engineering, 137(1), p.014001.

• Huang, T., Wang, S. and He, K., 2015, October. Quality control for fused deposition modeling based additive manufacturing: Current research and future trends. In Reliability Systems Engineering (ICRSE), 2015 First International Conference on (pp. 1-6). IEEE.

• Guessasma, S., Zhang, W., Zhu, J., Belhabib, S. and Nouri, H., 2015. Challenges of additive manufacturing technologies from an optimisation perspective. International Journal for Simulation and Multidisciplinary Design Optimization, 6, p.A9.

• Modelling and Process Control:• Sun, Q., Rizvi, G.M., Bellehumeur, C.T. and Gu, P., 2008. Effect of processing conditions on the bonding quality of FDM polymer

filaments. Rapid Prototyping Journal, 14(2), pp.72-80

• Huang, Q., Nouri, H., Xu, K., Chen, Y., Sosina, S. and Dasgupta, T., 2014. Statistical predictive modeling and compensation of geometric deviations of three-dimensional printed products.Journal of Manufacturing Science and Engineering, 136(6), p.061008.

• Yoon, J., He, D. and Van Hecke, B., 2014, September. A PHM approach to additive manufacturing equipment health monitoring, fault diagnosis, and quality control. In Proceedings of the Prognostics and Health Management Society Conference, Fort Worth, TX, USA (Vol. 29, pp. 1-9).

Acknowledgements

• Supervisors: Dr Carwyn Ward, Dr Guido Herrmann, Dr Julie Etches

• This work was supported by the EPSRC Centre for Doctoral Training in Future Autonomous Robotic Systems (FARSCOPE) at the Bristol Robotics Laboratory, (grant: EP/L015293/1).

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