The Rate of Material Addition is the Key Measurand with Fused Filament Fabrication in Additive Manufacturing
Pieter Greeff
Test and Measurement Conference
2019
Additive Manufacturing (AM) ExplainedThe current principle: “layer by layer
AM is the “process of joining materials to make parts from 3D model data, usually
layer upon layer, as opposed to subtractive manufacturing and formative
manufacturing methodologies” [1]
[1] Additive manufacturing – General principles – Terminology. Geneva, CH: International Organization for Standardization, 2015
AM: Additive Manufacturing
(3D Printing)
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https://facfox.com/what-is-3d-printing
Additive manufacturing -- General principles -- Terminology. Geneva, CH: International Organization for Standardization, 2015.
T. Wohlers and T. Gornet, “History of Additive Manufacturing 2014,” Wohlers Rep. 2014 - 3D Print. Addit. Manuf. State Ind., pp. 1–34, 2014.
ISO Categories and Timeline
Vat
Polymerisation
Material
Extrusion
Binder Jetting
Sheet
Lamination
Direct Energy
Deposition
Powder Bed
Fusion
Material Jetting
1991
1987
1992
1993
1994
1998
SLA™ (Stereolithography), DLP™ (Digital Light
Processing), CDLP™ (Cont. DLP), 3SP™ (Scan, Spin
and Selectively Photocure)
LOM (Laminated Object Manufacturing), SDL (Selective
AM), UAM (Ultrasonic AM)
PolyJet™, SCP™ (Smooth Curvature Printing), MJM
(Multi-Jet Modelling), NPJ (NanoParticle Jetting), DOD
(Drop on Demand), Projet™
3DP™ (3D Printing), ExOne, Voxeljet
MJF (Multi Jet Fusion), SLS (Selective Laser Sintering),
DMLS (Direct Metal Laser Sintering), SLM (Selective
Laser Melting), EBM (Electron Beam Melting)
LENS™ (Laser Engineered Net Shape), EBAM (Electron
Beam AM), LMD (Laser Metal Deposition), DMD™
(Direct Metal Deposition)
Additive
Manufacturing
FDM™ (Fused Deposition Modelling),
FFF (Fused Filament Fabrication)
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Additive Manufacturing:Reasons for Growth
R. Leach, “Metrology for Additive Manufacturing”, Measurement and Control, Vol. 49(4) 132–135, 2016
Also:
https://3dprintingindustry.com/news/3d-printing-ready-mass-production-132576/
https://all3dp.com/2/can-3d-printing-be-used-for-mass-production/
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➢ Mass customisation
➢ ‘Free’ complexity
➢ Positive environmental impact
➢ Reduce mass and component count in assemblies
➢ Mass production of complex parts
➢ Adidas: Two new factories, each of which is intended to turn out up to 500,000 pairs of trainers a year (2017)
➢ Chanel: 1 million make-up brushes per month (2018)
➢ Siemens: (Fully) Automated factories of the future
Liquid lattice structures produced
with EOS Additive Manufacturing
technology
(Source: Autodesk Within),
https://www.eos.info/automotive
Cross-section of the 3D printed
Conflux CoreTM Heat Exchanger
(Source: EOS)
https://www.eos.info/press/case_st
udies/conflux-heat-exchanger
[1] J. Pellegrino, T. Makila, S. McQueen, and E. Taylor, “Measurement science roadmap for polymer-based additive manufacturing”,
National Institute of Standards and Technology, Gaithersburg, MD, Tech. Rep. 5, Dec. 2016
In-Process Quality Assurance
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Concepts: digital twin, unique complex
parts, functional specification assurance?
Complete voxel (3D pixel) part history (digital thread)
Built-in conformance testing of each part: an ideal, but also an necessity
Example Target:
10 µm voxel resolution,
multiple variables, including time [1]
E.g.: 100 mm cube
1012 points
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Fused Filament Fabrication (FFF)
(Heated) Build Bed
Extr
ud
er
Cold End
Hot End
Liquefier
Temperature
Sensor
Heater
Filament
Supply
Heat Break
Deposited Layers in the
XY Plane
Extruded Track or Road
X
Y
Z
Filament
Filament
Feed
Mechanism
Nozzle
RF 1000
https://www.conrad.de/de/renkforce-rf1000-3d-
drucker-...html
Open Loop Control
CAD
ModelSlicer
G-code
commands
Printer Firmware
(interpreter)
Bottom-Up Approach
Fused Filament Fabrication Possibilities
[1] B. Hampel, S. Monshausen, and M. Schilling, “Properties and applications of electrically conductive thermoplastics for
additive manufacturing of sensors”, Technisches Messen, vol. 84, no. 9, pp. 593–599, 2017
[2] M. Gibson, N. Mykulowycz, J. Shim, et al., “3D printing metals like thermoplastics: Fused filament fabrication of metallic
glasses”, Materials Today, vol. 21, no. 7 pp.697-702, 2018
Siz
e
Reso
luti
on
Mate
rial
Re
so
luti
on
https://all3dp.com/danish-engineering-students-
use-bigrep-3d-printer-create-functional-bicycle/
Functional Bicycle
Frame
Electrically
Conductive [1]
Fully Dense
Metal [2]Wood Filled
https://3dwithus.com/wood-filament
http://www.soliforum.com/topic/15
474/printing-with-a-02mm-
airbrush-nozzle/
Small Parts
Nozzle diameter : 0.2 mm
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Feed Speed Measurement: Bottom-up approach
USB Microscope
Support Arm Cable Guide
Side View
In-process measurement of feed and filament speed, as well as filament width →
volumetric flow rate
Feed Slippage with Machine Vision
( )
( ) 3
2.00 0.06 mm s
12.76 0.39 mm sQ
=
=
Filament Feeding Feed Slippage
[1] G. P. Greeff and M. Schilling, “Closed loop control of slippage during filament transport in molten material extrusion,” Addit.
Manuf., vol. 14, pp. 31–38, 2017
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Free-air Extrusion Experiments
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Δ𝑣𝑚𝑜𝑑𝑒𝑙 = 1 + 𝑒− 𝛽1𝑣𝑝+𝛽2
𝑇−𝛽0Empirical Model:
[1] G. P. Greeff, “Applied Metrology in Additive Manufacturing,” mensch und buch verlag, Berlin, 2019
[1] G. P. Greeff and M. Schilling, “Closed loop control of slippage during filament transport in molten material extrusion,”
Addit. Manuf., vol. 14, pp. 31–38, 2017
Closed Loop Control
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Measured Slip
(%)
G-code
Machine
Command
Object File
Machine
Vision
Flow
Multiplier
(%)
Feed Slippage
Data
Recording
3D Printer
(a) Control Block Diagram
Test Layers(b) Control Off: 1,425 g
(c) Control On: 1,622 g
Under-extrusion
[1] G. P. Greeff and M. Schilling, “Comparing Retraction Methods with Volumetric Exit Flow Measurement in Molten Material
Extrusion,” in Special Interest Group meeting on Dimensional Accuracy and Surface Finish in Additive Manufacturing,
euspen, 2017, no. October, pp. 70–74
Melt Pressure Measurement
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Liquefier
Filament
Strain Gauges
X-axis
X-axis
Filament Feed Mechanism
Or 13% at a feed speed of 2 mm/s
( )
( )
( )
2
5.00 0.26 MPa
f
cnt fit cnt fit
a cnt
m x k x c
g m xFP
A R
P
= +
= =
=
[1] A. Bellini, S. Guceri, and M. Bertoldi, “Liquefier Dynamics in Fused Deposition,” J. Manuf. Sci. Eng., vol. 126, no. 2, p. 237,
2004
Modelling Pressure with Temperature and Speed
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( )3
1total i
i
P H T P=
= Bellini Model:
75 600 datapoints to 18 per
measurand for a part feature (wall)
Modelling Feed Speed with Pressure and Temperature
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𝑣𝑓 = 𝜙Δ𝑃
ሻ𝐴1 + 𝐴2 + 𝐴3 𝐻(𝑇
𝑚
𝐻 𝑇 = 𝑒𝛼
1𝑇−𝑇0
−1
𝑇𝛼−𝑇0
𝑣𝑓 = 𝛽0 + 𝛽1𝑇 + 𝛽2Δ𝑃 + 𝛽12Δ𝑃𝑇
Inverse Bellini Model:
Empirical Model (filament feed speed as a function of
temperature and pressure)
Verification Experiments
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Test with verification print runs (2)• Different T/v for each run
• Same T/v for each printed object in run
• Fit inverted and non-inverted Bellini model
Predicts responses well enoughwithin uncertainty expectations
Resultpossible to predict slippage
using temperature and pressure
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Additive Manufacturing is a key technology for the fourth industrial revolution, but requires standardisation and therefore needs new
metrology.
1. Metrology is the key to change AM from a rapid prototyping complex 3D welding fabrication process into a functional component production solution.
2. New metrology, which uses and supports concepts of Industry 4.0 cyber-physical systems, is therefore required.
3. This new metrology must rapidly obtain and integrate a large amount data from diverse sensor systems into process and end-product applicable information.
Conclusion
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The presented ideas gained can be applied to
Additive Manufacturing in general.
1. A link between the expected, commanded and actual material addition rate is not only critical to understand the process, but also to improve and qualify the final part.
2. The actual rate of material addition is critical, but hard to measure. This requires methods and models which can infer this rate from other measurements.
Conclusion Continued
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Acknowledgements
We gratefully acknowledge support by:
• Institute of Electronic Measurement and Fundamental Electrical Engineering (EMG)
• Braunschweig International Graduate School of Metrology (B-IGSM)
• Physikalisch-Technische Bundesanstalt (PTB)
• National Metrology Institute of South Africa (NMISA)
The Feed Mechanism and Extruder: Bottom Up Approach
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Feed GearFilament Pinch
Bearing
Spring
Bolt
Filament Input
Extruded Filament
Representative drawing of a liquefier
cross-section
Liq
uefi
er
Complete voxel (3D pixel) part history (digital thread) [1]:
Built-in conformance testing of each part.
[1] J. Pellegrino, T. Makila, S. McQueen, and E. Taylor, “Measurement science roadmap for polymer-based additive manufacturing”,
National Institute of Standards and Technology, Gaithersburg, MD, Tech. Rep. 5, Dec. 2016
[2] R. Leach, P. Bointon, X. Feng, S. Lawes, S. Piano, N. Senin, D. Sims-Waterhouse, P. Stavroulakis, R. Su, W. P. Syam, and M.Thomas,
“Information-rich manufacturing metrology”, in Eighth International Precision Assembly Seminar (IPAS), 2018
Example Target:
10 µm voxel resolution,
multiple variables,
including time [1]
E.g.: 100 mm cube
1012 points
Requires:
➢ Fast, non-contact measurement [2]
➢ Large dataset
Metrological challenges
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The Two Axioms
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1) The axiom of manufacturing imprecision: “All manufacturing processes
are inherently imprecise and produce parts that vary.”
2) The axiom of measurement uncertainty: “No measurement can be
absolutely accurate and with every measurement there is some finite
uncertainty about the measured attribute or measured value.”
V. Srinivasan’s two axioms in computational metrology [1]:
[1] E. Morse, J.D Dantan, N. Anwer, R. Söderberg, G. Moroni, A Qureshi, X. Jiang and L. Mathiey, “Tolerancing: Managing uncertainty from
conceptual design to design to final product”, CIRP Annals - Manufacturing Technology Vol. 67 p. 695–717, 2018
Modelling: Data Processing
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MeasurandAverage Standard
DeviationUnit
Filament Width 0,01 mm
Feed Speed 0,16 mm/s
Gear Speed 0,17 mm/s
Pressure 0,67 MPa
• Print the same part at different speeds and
temperatures
• Aligning in-process measurement data
sets
• Select G-codes which creates a specific
feature in all part layers
• Select datapoints corresponding to these
G-codes.
• Aggregate results into single values for all
layers per object.
• i.e. 75 600 datapoints to 18 datapoints
• Use these values to model the print
process
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Open source, cost effective, in-process metrology can be used to improve and standardise the Fused Filament Fabrication (FFF)
process.
Different methods which achieves this were presented:
1. Optical feed speed measurement and control
2. Melt pressure based feed speed estimation
3. Link between the G-code commands, in-process and post-process data.
Conclusion