DIGITAL MANUFACTURING
A Year 5 student
of today has
similarly bold
predictions for
the future –
what's not to say
they won't be
commonplace
in 30 years?
available in the OT world
where continuous deployment
and test tools allow new
functionality and updates to
be deployed seamlessly. For
Siemens, this is no longer a
picture of the future. We are
rolling out such technologies in
our manufacturing sites and are
able to help our customers do
the same, increasing machine
availability and transparency
which leads to even higher
productivity and improved
sustainability. Industrial Edge
Computing, for example, enables
today’s automation users to
leverage new technology like
Machine Learning in industrial
automation.
We’re already thinking
ahead to the next level of
digital transformation through
combinational, cutting-edge
technologies such as IoT, AI,
Industrial 5G and Blockchain, as
well as additive manufacturing
and generative design. This is
the Digital Enterprise, a system
of tools to enable the smart use
of data across horizontal and
vertical value chains.
In manufacturing, the way
ideas come to life is changing
rapidly. For instance, generative design technology,
which mimics nature’s evolutionary approach,
off ers innovative design and engineering solutions
which when matched with the geometric freedoms
of additive manufacturing delivers products that
were unthinkable 30 years ago.
Today’s complex products necessitate
comprehensive tools that help engineers design
systems featuring mechanical, electrical and
software components. To aid the engineer, we are
introducing AI to our core design tools for CAD
and Automation engineering to allow this cognitive
engineering approach to support and guide
engineers and increase performance.
Advances in and systems that teach themselves
to respond when exposed to new data are helping
us to progress too. Additive manufacturing
has the potential to transform
design, manufacturing and
logistics support practices, giving
engineers the opportunity to
economically print replacement,
customised or serial parts from
a digital design and advanced
robotics are being deployed more
extensively due to lower costs
and their ability to perform
complex tasks.
Cloud and Edge technologies
together off er greater global
deployment and system
management options. Knowledge
automation is enabling software to
curate information, so people get what is relevant
to them when they need it. Then there is Big Data
analytics, using technology to examine large data
sets to uncover hidden patterns, correlations,
market trends, customer preferences and other
useful business information.
We are living through the smart factory
revolution now, which will further impact the
way we do business. Driven by the need to be
more sustainable and productive, our factories
increasingly need new skills and technology
injections. This trend is set to accelerate as we
adjust to a new normal. But what advances will the
next 30 years bring?
Through a recent exercise for the HVM
Catapult, I had reason to ask this of a few CTOs,
apprentices, engineering graduates and some
schoolchildren. The grown-ups said we would
have captured all human knowledge, we’ll have 8G
technology, and machines will be able to deliver
patient specifi c diagnoses through wearable
devices. But I admit to being inspired too by Daisy,
a Year 5 student, who brought to life her sense
of what the future will look like. She predicted
that we’ll have a rooftop platform for our fl ying
cars, disappearing holographic televisions – and
brain machines that mean you won’t have to go
to school. With high-performance computing and
machine learning, why wouldn’t we, in 30 years’
time, have mapped the way that the human brain
thinks to enable everyday biological interfaces to
technology? I wonder if Daisy will be right.
In that time, we were able to
use collaborative product data
management (CPDM) tools
to design a factory to build
the breather absorber and
fl ow valve sub-assemblies in
close collaboration with the
awesome team at Airbus. We
incorporated social distancing at
two metres between workers in
the simulation and even created
digital training aids for Airbus’
500 makers, meaning they had
clear knowledge of their tasks in
advance of seeing the products
or the factory for the fi rst time.
For manufacturers today,
performance data from products,
their production and use, is
helping derive unprecedented
value. With MindSphere, the
cloud based IoT operating
system, working seamlessly
with Industrial Edge technology
we can collect, analyse and
transform data into important
knowledge. This data is fed into
the entire value chain all the
way back to product design,
creating a closed-loop decision
environment for continuous
optimisation of both the product
and the production process.
We commonly talk now
about the increasing integration
of Information Technology (IT)
and Operational Technology
(OT), which encompasses
Industrial Control and
telemetry systems.
Agile IT development
methodologies are already
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