The role of powder properties on Precision Additive Metal ...

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The role of powder properties on Precision Additive Metal Manufacturing Mirko Sinico m [email protected] PAM 2 | KU Leuven AM Research Group Belgium 20 th September 2019, Padova, Italy INFN AM Workshop 2019

Transcript of The role of powder properties on Precision Additive Metal ...

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The role of powder properties on Precision Additive Metal Manufacturing

Mirko Sinico

[email protected]

PAM2 | KU Leuven AM Research Group

Belgium

20th September 2019, Padova, Italy

INFN AM Workshop 2019

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Mirko Sinico – [email protected]

The PAM2 project (https://pam2.eu/)

Slide 1

• Precision Additive Metal Manufacturing

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Mirko Sinico – [email protected]

The PAM2 project (https://pam2.eu/)

Slide 1

• Precision Additive Metal Manufacturing

➢ with 6 Academic partners

➢ and 6 Industrial partners

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Mirko Sinico – [email protected]

The PAM2 project (https://pam2.eu/)

Slide 1

• Precision Additive Metal Manufacturing

➢ with 6 Academic partners

➢ and 6 Industrial partners

• In the domain of Design for AM

• we develop new practices and models

• to enhance the precision of LPBF

• and…we test them on end-users cases

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Mirko Sinico – [email protected]

The PAM2 project (https://pam2.eu/)

Slide 1

• Precision Additive Metal Manufacturing

➢ with 6 Academic partners

➢ and 6 Industrial partners

➢ & 15 young researchers

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Mirko Sinico – [email protected]

The PAM2 project (https://pam2.eu/)

Slide 1

• Precision Additive Metal Manufacturing

➢ with 6 Academic partners

➢ and 6 Industrial partners

• Our goal is to improve the precision of

the LPBF process, covering all the value

chain of the AM manufacturing

• and…test our research on end-users cases

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Mirko Sinico – [email protected]

The role of powder properties on PAM2

Slide 2

precisionprecisionprecision

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Mirko Sinico – [email protected]

Powder properties influence LPBF part properties

Slide 3

from S. Vock, B. Klöden, A. Kirchner, T. Weißgärber, and B. Kieback, ‘Powders for powder bed fusion: a review’, Progress in

Additive Manufacturing, Feb. 2019.

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Mirko Sinico – [email protected]

The role of powder properties on PAM2

Slide 2

Simulations Characterization Processability

Novel full physical meso-scale numerical model

Characterization of AM Metal Powder with an Industrial Microfocus CT

Influence of the Particle Size Distribution on surface quality

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Mirko Sinico – [email protected]

The role of powder properties on PAM2

Slide 4

Simulations

Novel full physical meso-scale numerical model

Mohamad

Bayat

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Mirko Sinico – [email protected]

Novel full physical meso-scale numerical model

Slide 5

Novel full physical meso-scale model:

• Analyze thermal fields, cooling rates,

formation of voids, surface porosities,

surface roughness…

• Taking into account melting/solidification,

evaporation, keyhole formation, radiation,

ray-particle interactions, particle

distribution, powder deposition….

• BUT: e.g. Maraging 300 no surface tension

and viscosity parameters

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Mirko Sinico – [email protected]

The role of powder properties on PAM2

Slide 6

Characterization

Characterization of AM Metal Powder with an Industrial Microfocus CT

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Medical vs. industrial CT scanners

Slide 7

Manipulator

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Influence factors

Slide 8

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➢ Pushing to the limits our µ-CT Nikon XT H 225 ST by measuring metal powders from 10 µm of Ø

➢ The metrological traceability is maintained by referencing our measurements to Laser Diffraction

analyses (both dry and wet) compliant with ISO 13320-1

Powder particles

Cylindrical

double tape

holder

Specimens preparation µ-CT scan Surface determination MATLAB analysis

• Minimum specimen size to reach high mag.

• Dispersion via dry spraying to avoid

particles in contact

• Powders from Al to W analyzed (various ρ)

• High mag. (69)

• Low power (< 7 W)

• Voxel rescaling via

calibration artifact

• Global ISO 50% thres.

• Our developed local thres.

for comparison

• In-house developed code

• Multiple outputs for particle size distribution

• Multiple outputs for particle shape analysis

Characterization of metal AM powders with µ-CT

Mirko Sinico – [email protected] 9

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Powder particles

Cylindrical

double tape

holder

Specimens preparation µ-CT scan Surface determination MATLAB analysis

• Minimum specimen size to reach high mag.

• Dispersion via dry spraying to avoid

particles in contact

• Powders from Al to W analyzed (various ρ)

• High mag. (69)

• Low power (< 7 W)

• Voxel rescaling via

calibration artifact

• Global ISO 50% thres.

• Our developed local thres.

for comparison

• In-house developed code

• Multiple outputs for particle size distribution

• Multiple outputs for particle shape analysis

Characterization of metal AM powders with µ-CT

➢ Powder distribution, powder shape,

powder porosity, and powder contamination

can be analyzed

PO

RO

SIT

Y

SH

AP

E

Mirko Sinico – [email protected] 9

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Mirko Sinico – [email protected]

The role of powder properties on PAM2

Slide 10

Processability

Influence of the Particle Size Distribution on surface quality

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Mirko Sinico – [email protected]

Starting backwards: an industrial user-case

Slide 11

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Mirko Sinico – [email protected]

Starting backwards: an industrial user-case

Slide 11

M. Sinico, R. Ranjan, M. Moshiri, C. Ayas, M. Langelaar, A. Witvrouw, F. van Keulen, and W. Dewulf, A mold insert case study on Topology Optimized design for Additive Manufacturing, Proceedings of the 2019 Annual International Solid Freeform Fabrication Symposium, 2019.

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Industrial user-case requirements

Slide 12

Mold top surface by SPI standard

SPI, Society of Plastic Industry

• From A-3, normal glossy finish,

0.10 µm Ra down to 0.05 µm Ra

• To A-1, super high glossy finish,

0.025 µm Ra down to 0.012 µm Ra

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Mirko Sinico – [email protected]

Typical surface roughness of metal AM

Slide 13

Where we typically are (LPBF)

Our target (glossy finish)

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Mirko Sinico – [email protected]

Industrial user-case requirements

Slide 12

Mold top surface by SPI standard

SPI, Society of Plastic Industry

• From A-3, normal glossy finish,

0.10 µm Ra down to 0.05 µm Ra

• To A-1, super high glossy finish,

0.025 µm Ra down to 0.012 µm Ra

• Several post-processing operations:

rough-milling, grinding, semi-finishing

plus finishing and a final EDM/polishing

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Mirko Sinico – [email protected]

Industrial user-case requirements

Slide 12

Mold top surface by SPI standard

SPI, Society of Plastic Industry

• From A-3, normal glossy finish,

0.10 µm Ra down to 0.05 µm Ra

• To A-1, super high glossy finish,

0.025 µm Ra down to 0.012 µm Ra

• Several post-processing operations:

rough-milling, grinding, semi-finishing

plus finishing and a final EDM/polishing

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Mirko Sinico – [email protected]

Powder properties influence LPBF part properties

Slide 14

If we ↓ decrease average particle size:

• ↑ Increase in purchase cost of the powder (typically)

• ↓ Decrease in flowability

• ↑ Increase in parts surface quality (lower Ra)

surface

quality

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Mirko Sinico – [email protected]

Research methodology

Slide 15

• GOAL:

Test 3 different distributions of Maraging steel 300

• HOW:

Full powder characterization & repeated build job DoE on a ProX 320A machine

Mar 5-15 Mar 10-30 Mar 15-45

DoE at 3 different Ev

𝑬𝒗 =𝑷

𝒗 × 𝒉 × 𝒕

~ 50 J/mm3

~ 60 J/mm3

~ 70 J/mm3

Standard

Array of specimens

~ 20x10x10 mm

t = 30 µm, h = 70 µm

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Powder characterization

Slide 16

Laser Diffraction

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Powder characterization

Slide 16

Laser Diffraction + Optical microscope

𝑪 =𝟒𝝅𝑨

𝑷𝟐

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Mirko Sinico – [email protected]

Powder characterization

Slide 16

Laser Diffraction + Optical microscope + Industrial µ-CT

𝑺 =𝝅𝟏𝟑(𝟔𝑽)

𝟐𝟑

𝑨

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Powder characterization

Slide 16

+ ASTM B213, B212 and B527 testing

➢ For flowability (Hall Flow),

apparent density ρapp and tap density ρtap

>> 1.25

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Top surface roughness

Slide 17

• Mar 15-45, optimum parameter set

Ra = 12.12 µm

• Optimum at 170 W, ~70 J/mm3 Ev

(1150 mm/s scan speed)

> 99.7 relative density

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Mirko Sinico – [email protected]

Top surface roughness

Slide 17

• Mar 15-45, optimum parameter set

Ra = 12.12 µm

• Mar 10-30, optimum parameter set

Ra = 5.34 µm, 56 % reduction

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Top surface roughness

Slide 17

• Mar 15-45, optimum parameter set

Ra = 12.12 µm

• Mar 10-30, optimum parameter set

Ra = 5.34 µm, 56 % reduction

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Top surface roughness

Slide 17 Mirko Sinico – [email protected]

• Surface roughness is inversely

proportional to Ev, directly

proportional to the laser power, at

the same Ev

• On average, ~40 % Ra reduction

with Mar 10-30

• Stability zone seems wider for the

Mar 10-30 distribution

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Mirko Sinico – [email protected]

Typical surface roughness of metal AM

Slide 13

Our target (glossy finish)

5.34

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(extra) Novel remelting strategy

Slide 18

5.34 µm

• Exploit fine powder possibilities

combined with remelting

Mirko Sinico – [email protected]

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(extra) Novel remelting strategy

Slide 18

5.34 µm

Base at

optimum

parameter set,

t = 30 µm

Top at t = 10 µm

Remelting step

• Exploit fine powder possibilities

combined with remelting

Mirko Sinico – [email protected]

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(extra) Novel remelting strategy

Slide 18

5.34 µm

Base at

optimum

parameter set,

t = 30 µm

Remelting step

• Exploit fine powder possibilities

combined with remelting

Mirko Sinico – [email protected]

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(extra) Novel remelting strategy

Slide 18

5.34 µm

Base at

optimum

parameter set,

t = 30 µm

Top at t = 10 µm

• Exploit fine powder possibilities

combined with remelting

Mirko Sinico – [email protected]

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(extra) Novel remelting strategy

Slide 18

5.34 µm

Base at

optimum

parameter set,

t = 30 µm

Top at t = 10 µm

Remelting step

• Exploit fine powder possibilities

combined with remelting

1.5 µm

Mirko Sinico – [email protected]

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Mirko Sinico – [email protected]

Future steps: acquisition of surface topographies

Slide 19

• Through a Sensofar S neox 3D surface profiler

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Future steps: acquisition of surface topographies

Slide 19

Sa = 12.54 µm Sa = 5.31 µm Sa = 1.98 µm

• Through a Sensofar S neox 3D surface profiler

• Step 1: Acquisition (CLSM) and F-operator (form removal, plane)

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Mirko Sinico – [email protected]

Future steps: acquisition of surface topographies

Slide 19

• Through a Sensofar S neox 3D surface profiler

• Step 1: Acquisition (CLSM) and F-operator (form removal, plane)

• Step 2: S-filter (8 µm) and L-filter (140 µm) to highlight scanning tracks

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Mirko Sinico – [email protected]

Future steps: acquisition of surface topographies

Slide 19

• Through a Sensofar S neox 3D surface profiler

• Step 1: Acquisition (CLSM) and F-operator (form removal, plane)

• Step 2: S-filter (8 µm) and L-filter (140 µm) to highlight scanning tracks

• Step 3: Rescaling to the same Z range

7 µm

-7 µm

7 µm

-7 µm

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Mirko Sinico – [email protected]

The role of powder properties on PAM2

Slide 2

Simulations Characterization Processability

Novel full physical meso-scale numerical model

Characterization of AM Metal Powder with an Industrial Microfocus CT

Influence of the Particle Size Distribution on surface quality

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Thank you!

Mirko Sinico1,2, Wim Dewulf1, and Ann Witvrouw1,2

1 Department of Mechanical Engineering, KU Leuven, 3001 Leuven, BE2 Member of Flanders Make - Core lab PMA-P, KU Leuven, 3001 Leuven, BE

Any question?

Mirko Sinico – [email protected]

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Mirko Sinico – [email protected]

A digression in the decrease of flowability

+

from A. B. Spierings, M.Voegtlin, T. Bauer, and K.Wegener, ‘Powder flowabilitycharacterisation methodologyfor powder-bed-based metaladditive manufacturing’, ProgAddit Manuf, vol. 1, no. 1–2, pp.9–20, Jun. 2016.

Powder with

particle sizes < 5 µm

μ-PBF, modified SLM-50

machine from Realizer

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Future steps

Slide 12

• Complete powders characterization (SEM, rotatory drum flowability test)

• Establish the evolution of surface quality for angled surfaces, and downfacing surfaces

Example for vertical surfaces (90º)

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Mirko Sinico – [email protected]

Future steps

Slide 12

• Complete powders characterization (SEM, rotatory drum flowability test)

• Establish the evolution of surface quality for angled surfaces, and downfacing surfaces

• Establish melt pool variability through the analysis of cross-section micrographs

• Understand the development of surface texture through full 3D topographic measurements

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Mirko Sinico – [email protected]

Conclusions

Slide 11

• Three Maraging 300 powders with different PSDs where tested

• The Mar 5-15 was deemed unsuitable for the ProX 320A recoating system

• A decrease > 50 % of top surface Ra was obtained for the Mar 10-30 distribution

• A novel remelting strategy was developed, resulting in top surface Ra of 1.5 µm

Mar 5-15 Mar 10-30 Mar 15-45

Standard

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(extra) Novel remelting strategy

+

5.34 µm