SyncTwin Leverages OpenUSD to Transform Microsoft Files into Factory Digital Twins

SyncTwin
GmbH,
a
software
company
specializing
in
optimizing
production,
intralogistics,
and
assembly,
is
on
a
mission
to
unlock
industrial
digital
twins
for
small
and
medium-sized
businesses
(SMBs),
according
to
the

NVIDIA
Technical
Blog.

Innovative
Use
of
OpenUSD
and
Omniverse

SyncTwin
has
developed
an
application
on
the
NVIDIA
Omniverse
platform
utilizing
Universal
Scene
Description
(OpenUSD)
to
enable
customers
to
create
digital
twins
of
their
facilities
from
non-3D
data
formats
such
as
Microsoft
PowerPoint,
Excel,
and
PDF.
Integrating
generative
AI,
the
app
allows
users
to
create
and
modify
digital
twins
through
simple
text
prompts.

The
application
also
employs
the
NVIDIA
cuOpt
accelerated
optimization
engine,
significantly
enhancing
the
efficiency
of
factory
and
warehouse
operations.
This
integration
allows
manufacturing
SMBs
to
simulate
and
evaluate
operational
scenarios,
optimizing
processes
and
resources,
resulting
in
a
projected
30%
savings
in
facilities
planning
and
process
efficiency.

Bringing
Manufacturing
Domains
Together

Factories
are
composed
of
interconnected
and
interdependent
domains.
Traditionally,
the
lack
of
integration
between
these
domains
and
data
sources
has
led
to
resource
wastage.
OpenUSD
enables
the
integration
of
data
between
these
domains
in
a
digital
representation
of
a
factory,
facilitating
a
comprehensive
view
of
factory
operations.

Using
OpenUSD,
SyncTwin
customers
can
combine
visual
data,
production
processes,
product
catalogs,
production
orders,
scheduling,
resources,
and
production
environments.
For
example,
floorplans
from
PowerPoint
slides
can
be
converted
into
digital
twins
using
bitmapping,
and
warehouse
inventory
data
from
Excel
spreadsheets
can
be
accurately
reflected
in
the
digital
twin
environment.

Michael
Wagner,
co-founder
and
CEO
of
SyncTwin,
stated,
“OpenUSD
is
the
common
language
to
bring
all
these
different
factory
domains
into
a
digital
twin.
It
can
be
instrumental
in
dismantling
data
silos
and
enhancing
collaborative
efficiency
across
different
factory
domains.”

Optimizing
Intralogistics
with
cuOpt

SyncTwin
uses
NVIDIA
cuOpt,
a
GPU-accelerated
microservice
for
logistics
and
route
optimization,
to
optimize
intralogistics
for
its
customers.
This
integration
enables
near-real-time
dynamic
decision-making,
improving
human-machine
interactions
for
automated
storage
and
retrieval
systems.
It
also
allows
for
dynamic
routing
of
robots
for
efficient
truck
loading
and
unloading.

Supercharging
Factory
Planning
with
AI

SyncTwin
is
integrating
generative
AI
to
accelerate
workflows
and
enable
planning
teams
to
interact
with
digital
twins
in
innovative
ways.
AI-enabled
digital
twins
support
planners
with
operational
insights
and
recommendations,
helping
them
identify
optimal
material
locations
and
potential
improvements
based
on
historical
data.

AI
facilitates
complex
analyses
and
informed
decision-making
regarding
resourcing,
machine
placement,
and
routing.
Additionally,
AI
can
help
create
a
knowledge
base
for
training,
troubleshooting,
and
decision-making
as
experienced
workers
retire.

Developing
SyncTwin
on
Omniverse

SyncTwin
has
been
delivering
innovative
solutions
for
factory
planning
for
years,
but
the
development
of
their
app
on
the
Omniverse
platform
has
unlocked
new
potentials.
By
leveraging
OpenUSD,
SyncTwin
enables
various
factory
planning
tools
to
contribute
to
a
digital
twin
environment
seamlessly,
breaking
down
data
silos.

The
Omniverse
platform
allows
customers
to
simulate
numerous
scenarios
and
test
various
possibilities,
providing
valuable
insights
and
solutions
directly
within
the
ecosystem.
SyncTwin’s
approach
of
structuring
digital
twin
environments
with
OpenUSD
components
like
Layers,
References,
and
VariantSets
has
proven
crucial
in
their
development
process.

Michael
Wagner
highlighted
the
importance
of
understanding
the
OpenUSD
approach,
stating,
“When
you
begin
to
organize
your
data
pipelines
and
digital
twin
structure
holistically,
the
possibilities
are
endless.”

Image
source:
Shutterstock