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