Advances on DMD
Transcript of Advances on DMD
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Advances in Direct Metal Deposition
Jyoti Mazumder* and Lijun Song
University of Michigan
July 15th, 2010
Presented By S H Lee
*Robert H Lurie Professor of Engineering
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Outline
• Background History of DMD
• Introduction
– DMD System Overview
• Advances in DMD System
– Modeling
– Geometry Control
– Temperature Control
– Composition Prediction
– Microstructure Prediction
• Summary
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Rapid Prototype
Customer
Conceptual Design
Assembly Layouts
Detailed Design
Prototype
Production
Time
Initial CAD Model
SFM
Reduction in
Time and Step
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Additive Manufacturing
• Additive Process
• Originally for Rapid Prototyping
Application
• 3-D CAD data -> 2-D Slicing
• Layer by Layer Build-up
• Low Volume Manufacturing
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Major RP Techniques
• StereoLithography (by 3D System)
• Laminated Object Manufacturing (by Helisys)
• Selective Laser Sintering (by DTM - 3D System)
• Fused Deposition Modeling (by StrataSys)
• 3D Printing (by Z-Corp.)
• Etc.
– Solid Ground Curing, Solder, Light Sculpting, Droplet
Based Manufacturing, Holographic Interference
Solidification, ...
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
New Concept in RP
• Rapid Prototyping
– Intermediate Step
– Design Support or Verification
– Plastic Mold Part, Cast Mold Pattern or “Mock-up”
Part
Rapid Manufacturing/Production
– Near Net Shaped Product or Prototype (accuracy and
finish)
– Functional Part (mold and metallic part)
– Better Part (multi-materials, heterogeneous)
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Metal Deposition - Metallic Additive
Manufacturing• Laser sintering (LS) based
– Selective Laser Sintering (U of Texas, DTM, 1996) - 3D Systems
– Direct Metal Laser Sintering (EOS, Germany)
• Laser cladding (LC) based
– Direct Metal Deposition (UIUC, 1993) - UM/POM
– Laser Engineered Net Shaping (Sandia NL, 1996) - Optomec
– Direct Light Fabrication (Los Alamos NL, 1996)
– Controlled Metal Buildup (Fraunhofer, Aachen, 1996)
• Droplet based
– Droplet Based Manufacturing (UCI, 1991; MIT, 1993)
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
The Vision• Imagine a global society where:
• scientists in Ann Arbor and Aachen, in the security of their laboratories, are analyzing, sharing and using experimental data,
• a global design team is collaboratively creating a new product and submitting it for fabrication to the company facility in Shanghai.
• Global collaboration for innovation over the Internet will cross-pollinate ideas, cut travel and reduce costs.
• A multi-national company designing their product in Detroit and producing in Dalian, China
• If the part is big, take process to the part
• Product on order anywhere any time
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Part on Order Anywhere
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Running to Moon: Mold & Mirrors
0.5 mm wall
thickness in
steel
Polished to 40
Angstroms!
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Application In Tissue engineering
5 mm
Titanium scaffold for implantation study in
a mice spinal column
* Image Provided by Prof. Scott Hollister
X-Ray of the Ti-Scaffold After Subcutenous
Bone Growth
Ti~ Bright White
Bone ~ Blue Grey
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
MR-DMD System
• Paradigm change
– Mobility
• “Process” goes for the
“Part” to be serviced.
• Container: DMD Package, Robot, Laser, HVAC, Utilities, etc.
– Adaptable Integration
• Different robot size
• Different laser power
(1.0-5.0 kW fiber-coupled
Diode Laser, etc.)
– Cost-effectiveness
• Robot vs. CNC based
platform
Work Stations
Control Room Robotic Work Area
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
MR-DMD System
Work Table
Fiber optic
Rotary Table
Robot
Base Plate
Conduit
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Challenges to achieve the vision
• Remote Manufacturing with hot editing
• Precision for Near Net shape 3-D
components in order of microns
• Approach: Closed loop Process control
to keep outcome to the desired level
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
DMD Process Overview
Copyright 1999 POM Company Inc. All rights reserved
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
OverviewDMD Process Overview
1. Direct Metal Deposition
• High power laser builds parts layer-by-layer out of gas atomized metal powder
2. DMD Characteristics
• 0.005” dimensional accuracy
• Fully dense metal
• “Controllable” microstructure
• Heterogeneous material fabrication capability
• Control over internal geometry
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
OverviewDMD Process Overview
Blending of 5 common methodologies:
• Laser
• CAD
• CAM
• Sensors
• Power Metallurgy
Omni directional concentric laser-powder-gas nozzle
Laser Beam Channel
Power Delivery Channel
Water
Cooling
Shaping
Gas
Changeable Tip
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Closed-Loop ProcessDMD Process Overview
CO2 Laser
CAD/CAM
NC
Feed-back
Controller
Work
Table
Control
Panel
Chiller
Power
Supply
Unit
Example of direct metal fabrication with POM’s closed loop height controller. Left: w/height controller; Right: no height controller.
Closed-loop process
• Improves dimensional accuracy
• No need for intermediary machining of parts when deposit builds irregularly
• Near net shape within fraction of millimeter is possible
• Resulting in significantly reduced post DMD finishing and reduced cost
• Better thermal control and thus better microstructure control
• Better microstructure leading to better mechanical properties
• Significantly reduced distortion and thus post process complication and cost
Left: DMD with feedback control
Right: DMD without feedback control
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Moving OpticsDMD Process Overview
Why moving optics?
• Part mass does not affect the usable work envelop (Velocity, acceleration etc)
• Part handling concerns reduced
• Angular deposition without moving part
10 Tons
Note Complex angles
of deposition
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Energy, Environment, EconomyDMD Process Overview
• Will save energy
• Will provide designed functionality
• Will reduce lead time & Economy friendly
• Environmentally Benign
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
How does DMD Machine Looks Like?DMD Process Overview
Why moving optics?
• Part mass does not the usable work envelop (Velocity, acceleration etc)
• Part handling concerns reduced
• Angular deposition without moving part
10 Tons
Note Complex angles
of deposition
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
DMD System
CO2 Laser
CAD/CAM
NC
Feed-back
Controller
Work
Table
Control
Panel
ChillerPower
Supply
Unit
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
A Laser Workshop on “Laser Based Manufacturing”
Elongation Hardness
(Mpa) (ksi) (Mpa) (ksi) (%) (Gpa) (Mpsi) (J) (ft-lb) (HRC)
H 13 H 13, DMD 1643 238 1407 204 8.4 197 29 12.9 9.5 54
Wrought
H 13
H 13 Wrought (Matweb)
1990 289 1650 239 9.0 207 30 13.6 10.0 53
316L SS 316SS, DMD 678 98 515 75 43.0 177 26 178.0 131.3 23
316L SS
wrought
316SS,
wrought585 85 380 55 45.0 193 28 103.0 76.0 20
Wasp
Alloy
Wasp Alloy,
DMD948 137 683 99 28.0 189 27 127.0 93.7
Wrought
Wasp alloy
Wasp alloy,
wrought aged1276 185 897 130 23.0 146 21
Stellite 21Stellite 21,
DMD1202 174 972 141 7.0 217 31 5.9 4.3 44
Cast
Stellite 21
Stellite 21,
cast620 90 441 64 9.0 207 30 21.2 15.6 35
Ti6Al4V
(Grade V)
Ti6Al4V DMD,
Inert atm1141 165 1045 152 8.0 112 16 53.7 39.6 38
Wrought
Ti6Al4V (V)
Ti-6Al4V (V),
wrought
annealed
950 138 880 128 14.0 114 17 17.0 12.5 36
4047 Alparallel to
deposition288 42 160 23 5.2 74 11 80 HV
413 Al
(cast)241 35 110 16 3.5 71 10
Cu-30 Ni 317 46 240 35 13.9 126 19 120 HV
Cu-30 Ni 375 54 234 34 31.5 165 24 128 HV
Al-alloys
Cu-Alloys
Fe and steel
Co-Alloys
Ti-Alloys
Ni-Alloys
Material
conditionMaterial
Tensile Strength Yield Strength Elastic Modulus Charpy Impact
Comparison of Material Properties: DMD vs. Wrought/Casting
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
DMD System Overview
Conceptualization CAD Data CAM tool path
ProductDMD with Advanced
Modeling, Sensing and
ControlX (mm)
0
1
2
3Y(m
m)
0.5
1
Z(m
m)
-0.3
-0.2
-0.1
0
Y
X
Z
COMP: 1 2 3 4 5
1 m/s
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Direct Metal Deposition
DMD with
closed loop controlDMD Machine
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Mathematical Modeling
• Process modeling of DMD to develop quantitative relationships between parameters for improved process control
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
0
u
t
x
pu
Kuu
t
u
l
l
u
Continuity equation:
Momentum equation:
Energy equation:
t
TCf
t
fTkTC
t
TC psspl
p
Lu
Solute equation: uu slsl ccfccDcDct
c
)(
Convection term Diffusion term Darcy term
Convection term Conduction term Phase change term at S/L
interface
Phase diffusion term Phase motion term
Modeling: Governing Equation
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Z
Y
The computation domain is not symmetric
along laser moving direction
StartFinish
Overlap
TransitionBeam size
Scanning
width
Multiple Track Deposition Model
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Evolution of Temperature Field
Laser power: 1900 W, beam diameter: 1.8 mm, scanning speed: 600 mm/min,
and powder flow rate: 8 g/min.
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Composition and Liquid Velocity Distribution
X (mm)
0
1
2
3Y(m
m)
0.5
1
Z(m
m)
-0.3
-0.2
-0.1
0
Y
X
Z
COMP: 1 2 3 4 5
1 m/s
X (mm)
0
1
2
3
Y(m
m)
0
0.5
1
Z(m
m)
-0.2
0
0.2
0.4
0.6
COMP: 1 2 3 4 5
1 m/s
Computed chromium concentration profile:
x-z surface and x-y surface
y-z surface
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Thermal Cycle
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Geometry Control
DMD Processing
Center (Logic OR)
Laser beam gating signal
Camera 1 2 3
Image acquisition
cards
Over limit
Height Controller Figure 8 Cladding
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Temperature Control: Dynamics
Substrate
bead
powder
Collecting lens
Pyrometer
GPC Temperature
ControllerLaser
0 10 20 30 40
1000
1500
2000
Melt p
ool te
mpera
ture
(0C
)
0 10 20 30 400.4
0.6
0.8
1
1.2
Time (s)
Laser
pow
er
(Kw
)
Experimental Setup Input and Output
H13 powder flow rate: 10g/min; Scanning speed: 650mm/min;
Standoff: 20mm (beam size 2mm)
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Temperature Control: Dynamics
30 40 50 60 70-600
-400
-200
0
200
400
Time (s)
Molten p
ool te
mpera
ture
(0C
)
(mean o
f te
mpera
ture
has b
een r
em
oved)
Step Response
Time (sec)
Am
plit
ude
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450
50
100
150
200
250
300
350
400
450
System: Goe
I/O: u1 to y1
Settling Time (sec): 0.323
From: u1 To: y1
System: Goe
I/O: u1 to y1
Rise Time (sec): 0.165
Dynamic Model Output
Step Response:
1k k k e k X AX Bu K
k k k e k y CX Du
(1a)
State Space Model
Rise time : 165ms
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
GPC Controller with constraints – Simulink Model
1. GPC Controller 2. A/D D/A interface to DMD process
3. State Estimation
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Melt Pool Temperature Control
5 10 15 20 25 30 35 40 451400
1600
1800
2000
2200
Molten p
ool te
mpera
ture
(0C
)
5 10 15 20 25 30 35 40 450
0.5
1
1.5
time (s)
Laser
driven v
oltage (
V)
Red: reference temperature
Black: experimental
0 5 10 15 20 25-400
-200
0
200
400
Tem
pera
ture
(0C
)
0 5 10 15 20 25-0.5
0
0.5
Lase
rpo
wer
(W)
0 5 10 15 20 25-100
-50
0
50
100
150
Time (s)
Noi
se a
nd
dist
urba
nce
(0C
)
• Experimental:
• Weight on control: 2×105
• Prediction horizon: 16
• Control horizon: 5
• Tfilter = [1 -0.8]
• Simulation:
• Weight on control: 100000000
• Prediction horizon: 30
• Control horizon: 5
• Tfilter = [1 -0.8]
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
(a) (b)
(c) (d)
Pictures of the deposition at (a) 10th layer,
(b) 20th layer, (c) 30th layer and (d) 40th layer Cladding height at different layers
Molten Pool Temperature Control
0 10 20 30 400
2
4
6
8
10
Cladding layer number
Cla
dd
ing
he
igh
t (m
m)
With control, a
With control, b
No control, a
No control, b
ba
Substrate
Cladding
y
zA
x3mm step
One Inch Cube Cladding with Temperature Control
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Composition Prediction
Substrate
Collecting lensbead
Laser beam
Signal processing
unit
spectrometer
Hopper1
Hopper2
Alloys without Phase
Transformation
Cr-Fe
Ni-Fe
Alloys With Phase
Transformation
Ti-Fe
Ni-Al
Ni-Ti
Experimental Setup
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Composition Prediction: Cr-Fe Alloy
• Calibration Curve
0 10 20 30 400.4
0.6
0.8
1
Cr-
I 428.9
72nm
/Fe-I
430.7
901nm
0 10 20 30 400.5
0.6
0.7
0.8
0.9
1
Cr-
I 428.9
72nm
/Fe-I
432.5
761nm
0 10 20 30 400.2
0.3
0.4
0.5
0.6
0.7
Cr-
I 434.4
51nm
/Fe-I
430.7
901nm
Cr weight percentage
0 10 20 30 400.2
0.3
0.4
0.5
0.6
0.7
Cr-
I 434.4
51nm
/Fe-I
432.5
761nm
Cr weight percentage
5 10 15 20 25 30 35 403700
3750
3800
3850
3900
3950
4000
4050
pla
sam
tem
pera
ture
(K
)
Cr weight percentage
Line Intensity Plasma Temperature
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Prediction of Cr% in the Alloy
• Composition Variation < 5%
5 10 15 20 25 30 35 40-40
-20
0
20
40
60
80
100
Cr weight ratio percentage
com
positio
n v
ariation (
%)
from single line ratio
from temperature
from electron density
from four averaged line ratio
from seven averaged line ratio
from seven averaged line ratio and electron density
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Composition Sensor for Time Domain Prediction
• Cr % for 19.80% Cr % for 22.36%
0 10 20 30 40 50 6014
16
18
20
22
24
Cr
com
positio
n (
%)
Measurement point0 20 40 60 80 100 120 140 160 180
18
20
22
24
26
28
30
32
Cr
com
positio
n (
%)
Measurement point
Resolution = 2×δ = 4.1%
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Calibration Curve for Fe-Ni Alloy
10-1
100
10-1
Ni 346nm
/ F
e 3
63nm
Ni/Fe weight ratio
10-1
100
10-1
Ni 346nm
/ F
e 3
64nm
Ni/Fe weight ratio
10-1
100
10-1
Ni 349nm
/ F
e 3
63nm
Ni/Fe weight ratio
10-1
100
10-1
Ni 349nm
/ F
e 3
64nm
Ni/Fe weight ratio
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
55 60 65 700
0.5
1
1.5
2
Fe-I
404.6
nm
/Ti-II
416.4
nm
Weight percent Ti
55 60 65 700
1
2
3
Fe-I
407.2
nm
/Ti-II
416.4
nm
Weight percent Ti
55 60 65 700.5
1
1.5
2
Fe-I
404.6
nm
/Ti-II
417.4
nm
Weight percent Ti
55 60 65 701
1.5
2
2.5
3
Fe-I
407.2
nm
/Ti-II
417.4
nm
Weight percent Ti
Microstructure Sensor: Ti-Fe Alloy (Patent Pending)
• Calibration Curve
Eutectic Ti67.5Fe25.5
Hypereutectic Ti56Fe44
Hypoeutectic Ti73Fe27 Hypereutectic Ti62Fe38
Hypoeutectic Ti70Fe30
10 um
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Calibration Curve for Ti-Fe Alloy
• Ti-Fe Alloy
Plasma Temperature Electron Density
55 60 65 70 754600
4800
5000
5200
5400
5600
5800
6000
6200
Weight percent Ti
pla
sm
a t
em
pera
ture
(K
)
1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.80
0.5
1
1.5
2
2.5
3x 10
16
Cr/Fe weight ratiopla
sm
a e
lectr
on d
ensity (
/cm
3)
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Ni-Al Alloy Phase Transformation and Line
Intensity Ratio
60 70 80 900
20
40
60
80
Al-I
394.4
nm
/Ni-I
349.2
96nm
Atomic percent Ni
60 70 80 900
10
20
30
40
Al-I
394.4
nm
/Ni-I
352.4
54nm
Atomic percent Ni
60 70 80 900
20
40
60
80
100
Al-I
396.1
5nm
/Ni-I
349.2
96nm
Atomic percent Ni
60 70 80 900
10
20
30
40
50
Al-I
396.1
5nm
/Ni-I
352.4
54nm
Atomic percent Ni
10um
? Ti67.5Fe25.5
B2 Ni65Al35
Gamma Prime Ni65Al35
B2 Ni65Al35
Gamma Prime Ni80Al20
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
XRD Pattern of Ni80Al20 Sample as Deposited
(111)
(200)
(220) (311)
(100)
20 30 40 50 60 70 80 90 100 110 120
Two-Theta (deg)
0
2500
5000
7500
Inte
nsity(C
ou
nts
)
[Z02639.raw] NI80AL20
03-065-3245> AlNi 3 - Aluminum Nickel
(110)
(210)(211) (300)
(222) (400)(321)(320)
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
• Ni-Ti Alloy
Ni-Ti Alloy Phase Transformation and Line
Intensity Ratio
80 85 900.05
0.1
0.15
0.2
0.25
0.3
Tl-I
416.4
14nm
/Ni-I
344.6
26nm
Atomic percent Ni
80 85 90
0.1
0.2
0.3
0.4
Tl-I
416.4
14nm
/Ni-I
346.1
65nm
Atomic percent Ni
80 85 900
0.05
0.1
0.15
0.2
Tl-I
417.4
07nm
/Ni-I
344.6
26nm
Atomic percent Ni
80 85 900
0.05
0.1
0.15
0.2
0.25
Tl-I
417.4
07nm
/Ni-I
346.1
65nm
Atomic percent Ni
100 um
Ni90Tl10
Ni87Tl13Ni79TI21
Ni84TI16
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Summary and Conclusion
• Process Model
– Simulate melt pool temperature, velocity, fluid interface
thermal cycle, and composition evolution and distribution
• Process Sensor and Control Design, Optimization and
Implementation
– Geometry Control
– Melt pool temperature dynamics and control
– Composition sensor
– Microstructure sensor
• First time in the world one will have the capability to
predict the microstructure during the process from
plasma, leading to considerable cost and lead time
saving
Center for Laser Aided Intelligent Manufacturing
University of Michigan, Ann Arbor
Thank you for your
attention!
Any questions or
comments?