The document discusses several new additive manufacturing processes and projects. It begins with Smartdrop, a non-contact patterned coating technology that jets glue to apply functional fluids without waste. It then discusses the UK EB Additive Manufacturing Platform project to develop complex geometries and advanced materials using electron beam wire additive manufacturing. Finally, it summarizes the RoboWAAM project which involves developing a large scale robotic production platform for industrial wire arc additive manufacturing applications with a build size of meters.

1. Topic
1:
New
AM
processes
Presenting
Nick
Allott
Dan
Mace
Will
Richardson
Anita
Ward
Steve
Hudson
Simon
McCaldin
Sarah
Karmel

2. AI DRIVEN
SECURE
INDUSTRIAL IOT
Dr Nick Allott
nquiringminds
Project
ref
103470

3. DREAM
addresses
the
problem
of
error
reduction
on
Selective
Laser
Melting
(SLM)
process
in
order
to
achieve
zero-­‐
distortion
builds
Distortion Reduction and Elimination
for Additive Manufacturing
Project
ref
103470

4. Estimated loss
$100k/machine/year
THEMACHINETHEPROBLEM
THEPROCESS
Example
machines
only
Project
ref
103470

5. Temperature
History
showing
processing
of
layer
33
and
layer
34
with
recoat
in
between
Blue
=
Solid
Metal
Red
=
Unfused
powder
Simulation
predicts
that
processing
parameters
lead
to
lack
of
fusion
/
porosity
at
the
boundary
of
the
column
Solid-Liquid Phase Evolution &
Temperature History
Project
ref
103470

6. DREAM project key data
Parameters, In-process &
sensor information…
Tensile
Fatigue
Creep
Hardness
X-­‐ray
Ultrsonic
CT…
And others…
Complex tests
& inspection data…
Powders, suppliers,
characterization data
Simulation data
Project
ref
103470

7. Data
Aggregation
Benchmarking
Data
Analytics
Workflow
1
Audit, secure and integrate data sources. Either
proxy to original data source or take batched
copies
2 Develop analytical KPIs that measure current
performance of business
3
Develop deep analytics that generate insight,
identify anomalies, optimise performance using
a mix of AI and statistical techniques
4
Present “prioritised” work items for human
inspection/refinement. Use workflow results to
improve ML algorithms real time. Evaluate
performance improvement and iterate.
PROCESS
Common
methodology
Project
ref
103470

8. 1 Visualise to generate insights
2 Basic encoding of input based
3
Use experts and visualisation to encode insights as
heuristics: high level features
Optionally: re encode
4
User unsupervised methods to generate high level
artefacts
Optionally: re encode
5
If training data exists use supervised methods to
generate new “feature detectors
Optionally: re encode
6 Apply optimally encoded and processed data to the
application domain
ANALYTICS
Common
Process
Raw
Data
Heuristic
Features
Unsupervised
/
Clustering/
Bayesian
Visualise
Supervised
/Learning
Encode
Apply
Project
ref
103470

9. PRINTER
SENSORS
Chamber
Temperature
Platform
Temperature
Gas
Temperature
SUPPLEMENTARY
SENSORS
Optical
Camera
Thermal
Camera
Substrate
Thermocouple
MODELS
CAD
STL
ACTUATORS
Laser
power
Hatch
spacing
Scan
vector
Layer
thickness
Wiper
blade
QA
Inspection
3D
scan
Other
inspections
DATABASES
Materials
Database
Machine
metadata
PERCEPTUAL
SYTEMS
ML
SYTEMS
CONTROL
SYTEMSML ARCHITECTURE
FOR AM
Project
ref
103470

10. INDUSTRIAL IOT REQUIREMENTS
SECURE
IOT
• Between
IOT
and
cloud
• Between
installations
• Between
organisations
in
cloud
• Between
IOT
devices
IOT
• Performance
• Predictive
analytics
• Big
data
processing
• Data
fusion
AI EDGE
• High
value
target
• Accidental
infection
• Legacy
challenges
• IOT
challenges
• Impediment
to
SECURE DATA
SHARING
• Legacy
interoperability
• Low
power
modes
• High
velocity
modes
• Resilient
communications
AI CLOUD
• Advanced
control
systems
• Data
fusion
• Adaptive
intelligence
Project
ref
103470

11. PROJECT OBJECTIVES
UK AM STRATEGY
PROGRESS/OUTCOMES
REQUESTS
• Reduce
wastage/improve
yield
of
the
manufacturing
process
– through:
• Better
collection
of
real
time
data
• Better
storage
and
sharing
of
data
to
inform
innovation
• Better
“more
intelligent”
control
algorithms
• Design/IP:
new
intelligent
control
algorithms
for
defect
reduction
• Test:
quality
metrics
for
machine
learning
• Standards:
define
interoperability
standards
for
control
and
data
sharing
• Share
key
data,
to
inform
modelling
and
algorithm
development
• Generic
control
system
architectures
for
collaborative
systems
Project
ref
103470

12. CloudDB
SLA Machine
Company
1 Company
2
AI (needs) DATA (needs) COLLABORATION
Company
1 Company
2
Project
ref
103470

13. nquiringminds
Dr Nick Allott
info@nqminds.com
@nqminds
www.nqminds.com
Project
ref
103470

14. Topic
1:
New
AM
processes
Pitches

15. Smartdrop
– a
connected
digital
manufacturing
platform
Smartdrop
is
a
non-­‐contact
patterned
coating
technology
for
laying
down
functional
fluids.
We
jet
glue
Applications
include
• shaped
and
programmable
adhesive
• non-­‐contact
coating
with
low
waste
Dan
Mace,
Archipelago
Technology
dan.mace@archipelagotechnology.com
Project
ref
103454

16. Project
Objectives Project
ref
103454
Your
requests
to
UK
Research
(Universities,
UKRI)How
does
this
contribute
to
delivering
the
AM-­‐UK
Strategy?
Progress/
Learning/
Outcomes
• To
create
a
Smartdrop
additive
manufacturing
prototype
system
• To
place
this
system
in
a
lead
customer's
factory
and
establish
digital
connectivity
• To
commission
a
Smartdrop
manufacturing
facility
•Materials
availability.
We
deposit
existing
industrial
materials
without
modification.
•Scale-­‐up.
We
operate
at
industrial
widths
and
speeds
Fill
Jet
• Outline
design
of
prototype
system.
• Options
for
manufacturing
identified
• Scalable
technology
demonstrated
at
narrow
width
• We
monitor
and
measure
the
Smartdrop
process
and
value
novel
real
time
characterization
techniques

17. Project
title:
RAMP-­‐UP
/
MIRIAM
Presenter
name/
company:
Will
Richardson
/
Reliance
Awaiting
approved
slides
Project
ref
103461

18. UK
EB
Additive
Manufacturing
Platform
(EBwireAM)
• Develop
a
UK
EB
wire
AM
platform
• Complex
geometries/advanced
materials
• Industry
4.0
compliant/cloud
based
analytics
• Targeted
for
aerospace,
power
and
mining
industries
Anita
Ward
(TWI)
Project
ref
103472

19. Project
Objectives Project
ref
103472
Your
requests
to
UK
Research
(Universities,
UKRI)How
does
this
contribute
to
delivering
the
AM-­‐UK
Strategy?
Progress/
Learning/
Outcomes
• Upscaling
of
process
• Platform
for
SME
development
use
• De-­‐risk
uptake
• SME
supply
chain
development
• Opportunities
for
artificial
intelligence
and
machine
learning
• CAD-­‐to-­‐part
development
• Microstructure
understanding
LMUK

20. Project
title:
RoboWAAM
Abstract:
“large
scale
robotic
production
platform
with
a
build
size
in
metres
with
a
viable
route
to
market
for
global
machine
platform
manufacture”.
Presenter
name/
company:
Steve
Hudson
/
KUKA
UK
Project
ref
103273
£1.435m
budget
30
months
duration
£931k
from
Innovate
UK

21. Project
Objectives Project
ref
103273
Your
requests
to
UK
Research
(Universities,
UKRI)How
does
this
contribute
to
delivering
the
AM-­‐UK
Strategy?
Progress/
Learning/
Outcomes
an
expandable
flexible
robotic
platform
suitable
for
industrial
WAAM
applications.
‘embedded’
in-­‐depth
process
knowledge
for
building
parts.
feedback
loop
and
algorithms
for
accurate
layer
height
control
laminar
flow
shielding
device
to
facilitate
out-­‐of-­‐
chamber
deposition
of
reactive
materials
such
as
titanium.
concurrent
NDT
and
deposition
processes.
use
KUKA’s
global
footprint,
supply
chain
and
customer
base
to
commercialise
and
increase
market
share
for
‘intelligent’
robotic
based
AM
retain
UK
based
IP
within
Industry
and
Academia
commercial
availability
of
an
‘intelligent’
robotic
WAAM
platform
suitable
for
production
of
metre-­‐
sized
components
in
various
materials.
whole
life-­‐cycle
WAAM
manufacturing
concepts
and
the
demonstration
of
parallel
processing
by
combining
WAAM
with
in-­‐process
NDT
robust
in-­‐process
NDT
methods
and
equipment
multimodal
human-­‐computer
interactions

22. Project
title:
OAAM
– Open-­‐Architecture
AM
Abstract:
To
demonstrate
the
ability
to
manufacture
large
metallic
components
via
Additive
Manufacturing
(AM)
for
the
benefit
of
UK
Aerospace.
Create
three
DED
AM
process
platforms
to
enable
aerospace
manufacturers
and
their
supply
chains
to
develop
advanced
AM
manufacturing
concepts.
Presenter
name/
company:
Dr
Simon
McCaldin
(TWI)
Project
ref
103164

23. Project
Objectives Project
ref
103164
Your
requests
to
UK
Research
(Universities,
UKRI)How
does
this
contribute
to
delivering
the
AM-­‐UK
Strategy?
Progress/
Learning/
Outcomes
•Metallic
parts
with
>1m
dimension(s)
•Scalable
architecture
solution(s),
with
common
CAD/CAM
control
interfacing
(Autodesk)
•Develop
and
deploy
3
DED
AM
systems:
• Arc-­‐wire
/
Laser-­‐wire
AM
@Cranfield
• Electron
Beam-­‐wire
AM
@TWI
(Cambridge)
• Laser-­‐powder
/
Laser-­‐wire
AM
@TWI
(Yorkshire
Technology
Centre)
• n/a
• Materials
and
Processing:
• Equipment
at
Scale
(technical
solution
development
and
economic
assessment/bench
marking)
• New
processes
(and
materials)
• Enable
companies
(especially
SMEs)
to
be
able
to
access
AM
equipment
to
technically
de-­‐risk
and
understand
benefits
to
their
activities:
ð £20-­‐100k
projects
(probably
<3-­‐6
months)

24. Project
title:
3D
printing
of
metal
and
ceramic
parts
Abstract:
Photocentric
have
developed
a
novel
method
of
printing
metal
and
ceramic
parts
using
visible
light
emitted
from
LCD
screens.
The
process
enables
selective
curing
of
high
viscosity,
particle
loaded
photopolymer
resins.
This
method
allows
a
fast,
accurate
and
cost-­‐effective
fabrication
of
a
wide
variety
of
ceramics
and
metals
to
produce
dense
objects
after
sintering,
examples:
Alumina Silica
Zirconia
Nickel
Presenter:
Dr
Sarah
Karmel Senior
Research
Chemist
Photocentric
Ltd.
Project
ref
104048

25. Project
Objectives Project
ref
104048
Your
requests
to
UK
Research
(Universities,
UKRI)How
does
this
contribute
to
delivering
the
AM-­‐UK
Strategy?
Progress/
Learning/
Outcomes
• Optimisation of metal and ceramic printer
process & validate final product properties
• Development
of
suitable
metal
and
ceramic
slurries,
printer
and
process
o Increase
metal
and
ceramic
powder
loadings
while
maintaining
flow
o Optimisation of
high
viscosity
binders
and
the
print
process
• LCD
screens
and
visible
light
enable
potential
large
scale
commercialisation
of
metal
and
ceramic
manufacture.
• Photocentric
is
UK
manufacturer
of
both
resins
and
printers
• Specific
ceramic
and
metal
research
opportunities
• Flash
sintering
/
co-­‐sintering
techniques
• Industrial
applications
Photopolymer
Photo-­‐
initiator
Metal
powder
Materials
Apparatus
LCD
screen
Visible
light
pre-­‐
sintering
post-­‐
sintering