CONTROL & AUTOMATION
SMART TECHNOLOGY
SCHNEIDER ELECTRIC
THE IMPACT OF AI ON THE INDUSTRY
By Martin Walder, VP of Industry at
Schneider Electric
Artificial Intelligence is one technology that
will revolutionise the field. A recent report
by Accenture showed corporate profits are
said to increase by an average of 38% by
2035, thanks to the advanced deployment
of Artificial Intelligence into financial, IT,
and manufacturing applications.
In the UK, we’re at the earliest stages of
AI implementation. We lack in clarity as
to its deployment across multiple use
cases. However, many organisations are
evaluating potential risk and reward
scenarios, and the technology is becoming
more widespread. Investing early, as with
Digital Transformation pay dividends, but
there are some crucial lessons to follow.
COLLABORATION BETWEEN
HUMANS AND MACHINES
Smart technology is encroaching on every
aspect of our lives. Turn on the news and
you’re bound to come across a discussion
of the benefits of the latest technology and
examples of their use.
The manufacturing industry embodies
this evolution. Advances to technology are
having an increasingly significant impact
on the production line. Today, there is a
direct correlation between tech investment
and efficiency. For manufacturers taking
the plunge and modernising their plants
and equipment, they can expect better
quality products and less wastage. The
result? Improved competitiveness and
ultimately profitability.
Industry 4.0 and associated technology,
such as IoT, AI and robotics, have
become part of the manufacturing
vernacular, without many understanding
their potential. Digital transformation
offers great unmatched potential for
manufacturers. Not only does it greatly
improve communication between devices,
systems and personnel both inside and
outside of the company, but it also cut
energy consumption, increases efficiency,
and increasingly delivers even short-term
ROI.
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AI has the potential to exponentially
increase the productivity of our industrial
assets. It represents a new way for
humans and machines to work together
in industrial applications. However, in
these scenarios, many variables need to
be accounted for in order to achieve a
successful and competitive outcome.
On the factory floor, AI technology enables
us to learn and predict tendencies to solve
complex problems. For example, managing
a process with almost countless variables,
such as control of temperatures, pressures
and liquid flows, is very prone to error. In
almost all factory settings, there are too
many variables for any human brain to
analyse successfully. By implementing
AI, crucial operational decisions can be
supported in real-time, greatly improving
safety, security, efficiency and productivity.
The quality of the data that trains the AI
algorithms needs to be combined with
the human expertise, which is always
needed for interpretation and guidance.
For example, in the Food & Bev industry, AI
can improve quality inspection, providing
humans with vision analysis and sound
analysis which goes beyond the ability of a
human alone.
AI AND INDUSTRY 4.0
AI is becoming an important part of
Industry 4.0. It brings with it the great
potential for innovation to dramatically
increase the productivity of industrial
assets, better manage the evolution of the
workforce, and greater energy efficiency.
Let’s take discrete and process
manufacturing as an example. Here,
asset maintenance is one of the industrial
processes that is emerging as an early AI
application. As a result, we’re seeing more
manufacturers understand that predictive
maintenance can be blended with the
more traditional approach or preventative
maintenance. The two, work hand-in-hand.
A great example of how AI is
revolutionising Industry 4.0 and improving
efficiencies on the factory floor is Variable
Speed Drives (VSDs). VSDs are connected
to motors on the factory floor. They
attain data and insights into abnormal
behaviours and thus flag these issues
so that they can be repaired, or where
necessary, replaced. The benefit here is
that a piece of equipment on the factory
floor is only replaced when absolutely
necessary, saving the manufacturer money
and reducing operational downtime.
Machine learning also comes into play
here. It can be executed at the edge to help
in the early identification of many potential
faults including, power generation turbine
blade damage or plant motor coupling
approaching failure.
Going forward, it’s clear then that the
Industry needs to consider the advantages
of automation through the use of robotics,
machine-learning and artificial intelligence.
Currently, there are only 71 robots in
the UK per every 10,000 manufacturing
employees, compared to over 300 in
Germany.
If robots and humans can work
together collaboratively, the benefits to
manufacturers will be huge. No human can
work 24 hours a day – but a robot can. The
productivity gains are massive. Whilst the
journey into Industry 4.0 is yet to begin for
many, those looking to succeed need to
consider investing in technologies such as
AI and machine learning. Ultimately, this
is the best way to increase efficiencies and
enhance productivity.
www.schneider-electric.co.uk/en/